Rakesh (Rah-kay-sh) sat in the small break room in the Amazon warehouse, fidgeting with his lunch. He smiled as he looked down at the small post-it note poking out from inside the crumpled brown bag that read “Good luck at work today, Dad!” He loved when his kids snuck him little notes in his lunch. They always knew how to make him smile. He wanted to give them a stable life so he worked 15-hour days and woke up early to make his kids breakfast before going to work. It was hard being a single dad.
", - "Even though his kids were older and in 7th grade and high school, it still felt like all the world’s burdens were on his shoulders; but seeing them happy helped. Raising his kids on his own had been difficult ever since Sorayah (So-raa-yaa), his wife or… well…ex-wife, and him split up. That left little time for Rakesh (Rah-kay-sh) to destress and have “me” time. But it was worth it if it meant he could eventually be promoted to manager. A higher pay and more stable hours would mean more time with his kids. As he looked at the note, Rakesh remembered the conversation he had with his kids that morning.
" + "Rakesh (Rah-kay-sh) sat in the small break room in the Amazon warehouse, fidgeting with his lunch. He smiled as he looked down at the small post-it note poking out from inside the crumpled brown bag that read “Good luck at work today, Dad!” He loved when his kids snuck him little notes in his lunch. They always knew how to make him smile. He wanted to give them a stable life so he worked 15-hour days and woke up early to make his kids breakfast before going to work. It was hard being a single dad.
Even though his kids were older and in 7th grade and high school, it still felt like all the world’s burdens were on his shoulders; but seeing them happy helped. Raising his kids on his own had been difficult ever since Sorayah (So-raa-yaa), his wife or… well…ex-wife, and him split up. That left little time for Rakesh (Rah-kay-sh) to destress and have “me” time. But it was worth it if it meant he could eventually be promoted to manager. A higher pay and more stable hours would mean more time with his kids. As he looked at the note, Rakesh remembered the conversation he had with his kids that morning.
" ] } }, { - "id": "tlvHCWX2a-MiE2ZQ", "title": "Text 4", "content": { "type": "Text", "format": "html", "text": [ - "Ajay (Uh-jay): Ugh. I just can’t study for this math test.
", - "Zainab (Zay-nab): Just do it.
", - "Ajay (Uh-jay): Okay, genius.
", - "Zainab (Zay-nab): I know, I’m so helpful, right?
", - "Rakesh: What’s going on? What’s the issue?
", - "Ajay: Dad... I can’t focus in class. Ms. Ross will put the equations on the board and next thing I know she got to the answer but I just don’t know how.
", - "Rakesh: Well, you need to pay more attention when she’s teaching! Math is important so you have to try harder. You kids have opportunities that I never had. You have to make use of them.
", - "Zainab: Like what, appa (father in Tamil)?
", - "Rakesh: You’re going to a good school, with good teachers, and you actually have a chance to learn, for free! You can get a degree and do what you want to do with your life here. I never got that in India. There, you have to pay for private school if you want a good education and you know our family couldn’t afford that…
", - "Ajay: Wait. What did you want to be when you were younger?
", - "Rakesh: I wanted to be an aerospace engineer since I was very young.
", - "Zainab: What’s that?
", - "Rakesh: It’s someone who designs planes.
", - "Zainab: So why not just become that now?
", - "Rakesh: No... My time for studying and all is done.. It’s your turn now. You need to study hard so that you can grow up and become what you want. That will make me the happiest. So you better go now and make sure you (Rakesh points to Ajay) study for that math test.
", - "Ajay: Okay, dad. Fine.
" + "Ajay (Uh-jay): Ugh. I just can’t study for this math test.
Zainab (Zay-nab): Just do it.
Ajay (Uh-jay): Okay, genius.
Zainab (Zay-nab): I know, I’m so helpful, right?
Rakesh: What’s going on? What’s the issue?
Ajay: Dad... I can’t focus in class. Ms. Ross will put the equations on the board and next thing I know she got to the answer but I just don’t know how.
Rakesh: Well, you need to pay more attention when she’s teaching! Math is important so you have to try harder. You kids have opportunities that I never had. You have to make use of them.
Zainab: Like what, appa (father in Tamil)?
Rakesh: You’re going to a good school, with good teachers, and you actually have a chance to learn, for free! You can get a degree and do what you want to do with your life here. I never got that in India. There, you have to pay for private school if you want a good education and you know our family couldn’t afford that…
Ajay: Wait. What did you want to be when you were younger?
Rakesh: I wanted to be an aerospace engineer since I was very young.
Zainab: What’s that?
Rakesh: It’s someone who designs planes.
Zainab: So why not just become that now?
Rakesh: No... My time for studying and all is done.. It’s your turn now. You need to study hard so that you can grow up and become what you want. That will make me the happiest. So you better go now and make sure you (Rakesh points to Ajay) study for that math test.
Ajay: Okay, dad. Fine.
" ] } }, { - "id": "XMsmlOIb74cTshR8", "title": "Text 5", "content": { "type": "Text", "format": "html", "text": [ - "Working for Amazon was never Rakesh’s first choice of career. Being an immigrant without a degree made it hard to find a job. It was even harder, because Rakesh’s ex-wife Sorayah (So-raa-yaa) was still back in India which meant Rakesh had to provide for their kids by himself.
", - "Rakesh and Sorayah met in high school in India and were married soon after graduating. Sorayah was from Iran but had lived in India almost all her life. Soon after they were married, Rakesh and Sorayah had two little children for whom they wanted a better life. So, they decided to immigrate to America. Rakesh left India first with the children so that the kids could start school in America.
", - "Sorayah was supposed to follow once her visa was approved by the U.S. Immigration Services. But, to their surprise, Sorayah’s visa application was denied because of a new rule that prevented people from muslim countries coming into the U.S. This meant Sorayah couldn’t immigrate to America because she had an Iranian passport. Even after all these years, Rakesh still had a lot of anger for the U.S. Immigration rules that broke up his family. Back in the lunchroom at work, Rakesh was zoning out, pushing the rice in his container around, when one of his co-workers, Nicole, came in.
" + "Working for Amazon was never Rakesh’s first choice of career. Being an immigrant without a degree made it hard to find a job. It was even harder, because Rakesh’s ex-wife Sorayah (So-raa-yaa) was still back in India which meant Rakesh had to provide for their kids by himself.
Rakesh and Sorayah met in high school in India and were married soon after graduating. Sorayah was from Iran but had lived in India almost all her life. Soon after they were married, Rakesh and Sorayah had two little children for whom they wanted a better life. So, they decided to immigrate to America. Rakesh left India first with the children so that the kids could start school in America.
Sorayah was supposed to follow once her visa was approved by the U.S. Immigration Services. But, to their surprise, Sorayah’s visa application was denied because of a new rule that prevented people from muslim countries coming into the U.S. This meant Sorayah couldn’t immigrate to America because she had an Iranian passport. Even after all these years, Rakesh still had a lot of anger for the U.S. Immigration rules that broke up his family. Back in the lunchroom at work, Rakesh was zoning out, pushing the rice in his container around, when one of his co-workers, Nicole, came in.
" ] } }, { - "id": "Jt2L_vV5XHqePXML", "title": "Text 6", "content": { "type": "Text", "format": "html", "text": [ - "Nicole: Hey. Did you hear about Deaundre?
", - "Rakesh: No.What happened? Is everything alright?
", - "Nicole: He had a heart attack while he was here. He’s at the hospital right now.
", - "Rakesh: WHAT! WHEN? I just saw him clock in this morning and he looked fine!
" + "Nicole: Hey. Did you hear about Deaundre?
Rakesh: No.What happened? Is everything alright?
Nicole: He had a heart attack while he was here. He’s at the hospital right now.
Rakesh: WHAT! WHEN? I just saw him clock in this morning and he looked fine!
" ] } }, { - "id": "vbmKHXWxDC6W-HrZ", "title": "Text 7", "content": { "type": "Text", @@ -102,35 +73,24 @@ } }, { - "id": "oxuSlTxkgkNJ5kIp", "title": "Rakesh Visits Deaundre at the Hospital", "content": { "type": "Image", - "url": "curriculum/bio4community/images/Rakesh_S1.jpg", - "filename": "curriculum/bio4community/images/Rakesh_S1.jpg" + "url": "bio/images/Rakesh_S1.jpg", + "filename": "bio/images/Rakesh_S1.jpg" } }, { - "id": "0nGiS4DXgDANMxcb", "title": "Text 8", "content": { "type": "Text", "format": "html", "text": [ - "[“Knock knock,” Rakesh entered with the bear held up to his face. Deaundre still had that smile plastered on. The two of them sat and talked for a while. ]
", - "Rakesh: Man, I am so glad to see you. How are you? I couldn’t believe it when I heard the news.
", - "Deaundre: I couldn’t believe it either. One minute I was working, the next I felt like my chest was so heavy and tight. It’s a good thing I wasn’t alone. I heard they called the ambulance right away, otherwise I don’t know what woulda happened.
", - "Rakesh: Did the doctors tell you what’s wrong? You look so healthy!
", - "Deaundre: Yeah, the doc keeps saying I’m too stressed and it’s causing blockages or something like that in my blood vessels. Somethin’ about stress causing all this bad stuff.
", - "", - "[This caught Rakesh’s attention.]
", - "", - "Rakesh: “Wait. Your stress led to your heart attack?”
" + "[“Knock knock,” Rakesh entered with the bear held up to his face. Deaundre still had that smile plastered on. The two of them sat and talked for a while. ]
Rakesh: Man, I am so glad to see you. How are you? I couldn’t believe it when I heard the news.
Deaundre: I couldn’t believe it either. One minute I was working, the next I felt like my chest was so heavy and tight. It’s a good thing I wasn’t alone. I heard they called the ambulance right away, otherwise I don’t know what woulda happened.
Rakesh: Did the doctors tell you what’s wrong? You look so healthy!
Deaundre: Yeah, the doc keeps saying I’m too stressed and it’s causing blockages or something like that in my blood vessels. Somethin’ about stress causing all this bad stuff.
[This caught Rakesh’s attention.]
Rakesh: “Wait. Your stress led to your heart attack?”
" ] } }, { - "id": "qP9YiY4vQWonn0cz", "title": "Text 9", "content": { "type": "Text", @@ -141,48 +101,36 @@ } }, { - "id": "pU7njUZzQ2LsYh8r", "title": "Text 10", "content": { "type": "Text", "format": "html", "text": [ - "", - "Can you help him figure this out?
", - "Discuss with your group--What do you think is the connection between stress and blocked blood vessels?
", - "" + "Can you help him figure this out?
Discuss with your group--What do you think is the connection between stress and blocked blood vessels?
" ] } }, { - "id": "k5RAu6GQ25j0ynvM", "title": "Text 11", "content": { "type": "Text", "format": "html", "text": [ - "Continue reading to find out what happened next:
", - "Rakesh left the hospital even more stressed. When he got home he did his best not to show his children how worried he was.
" + "Continue reading to find out what happened next:
Rakesh left the hospital even more stressed. When he got home he did his best not to show his children how worried he was.
" ] } }, { - "id": "O52To-oPV_xkTrl4", "title": "Text 12", "content": { "type": "Text", "format": "html", "text": [ - "Zainab: Hi Appa! Ajay already made the rice - the curry is just heating up now.
", - "Rakesh: Thanks, I’ll just wash my hands and come.
", - "Ajay: Hurry up dad, I’m so hungry! Coach ran us SO HARD at track. You remember we have the track meet this weekend right? Are you coming?
", - "Rakesh: Yes Ajay, you know I’m gonna try. It all depends on whether I can find someone to cover my shift.
", - "Zainab: Ok everybody come, dinner’s ready. Ajay you better not take all the rotis this time. I don’t care how hungry you are!
" + "Zainab: Hi Appa! Ajay already made the rice - the curry is just heating up now.
Rakesh: Thanks, I’ll just wash my hands and come.
Ajay: Hurry up dad, I’m so hungry! Coach ran us SO HARD at track. You remember we have the track meet this weekend right? Are you coming?
Rakesh: Yes Ajay, you know I’m gonna try. It all depends on whether I can find someone to cover my shift.
Zainab: Ok everybody come, dinner’s ready. Ajay you better not take all the rotis this time. I don’t care how hungry you are!
" ] } }, { - "id": "Z8V_OV-2o1DEht_l", "title": "Text 13", "content": { "type": "Text", @@ -193,15 +141,12 @@ } }, { - "id": "vgCFRLd5bNqzz2FX", "title": "Text 14", "content": { "type": "Text", "format": "html", "text": [ - "Overview:
", - "In this lesson, you will be introduced to emerging technology that helps people with neurological conditions or missing limbs.
", - "Learning Objectives:
", - "This activity is intended to help you come up with questions about how body systems interact with one another and with technology. We will explore these questions throughout the unit.
" + "Overview:
Throughout this unit, we will explore how bionic arms work. Bionic arms are designed for people with limb differences (e.g., people who lost a limb as a result of an accident). With recent developments in science and engineering, these individuals can now directly control a prosthetic arm as if it was their own biological arm.
Learning Objectives:
This activity is intended to help you come up with questions about how body systems interact with one another and with technology. Throughout the unit, you will also learn about the engineering design process: what do engineers do and how their work can help people.
To start off, please drag the following tile into your workspace and answer these questions:
" ] } }, @@ -21,9 +18,18 @@ "type": "Text", "format": "html", "text": [ - "To start off, please drag the following tile into your workspace and answer these questions:
", - "1) What do you know about bionic arms? (e.g., what do they look like, why people might use them, in what ways are they connected to the person’s body, how do they work)
", - "2) If you were tasked to design a bionic arm, what do you think the people who use them would like in terms of appearance and function?
" + "To start off, please drag the following tile into your workspace and answer these questions:
1) What do you know about bionic arms? (e.g., what do they look like, why people might use them, in what ways are they connected to the person’s body, how do they work)
2) If you were tasked to design a bionic arm, what do you think the people who use them would like in terms of appearance and function?
" + ] + } + }, + { + "id": "5N9jxYdxdFR4-N-n", + "title": "Text 1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" ] } } diff --git a/curriculum/brain/investigation-1/problem-1/labWork/content.json b/curriculum/brain/investigation-1/problem-1/labWork/content.json index 06d961557..73a7f9975 100644 --- a/curriculum/brain/investigation-1/problem-1/labWork/content.json +++ b/curriculum/brain/investigation-1/problem-1/labWork/content.json @@ -8,24 +8,82 @@ "type": "Text", "format": "html", "text": [ - "Meet Tilly
", - "Tilly is a real-life bionic teen. At only 15 months old, Tilly had both her hands amputated at the wrist because of a very rare infection. For years she used basic silicon arms, but in 2018 she became the first child in the UK to have bionic arms. These high-tech, 3D printed arms give Tilly a much fuller range of movement. In class, you will watch a video about Tilly, who is now a model, public speaker and make-up vlogger. In the video, Tilly showcases her colorful arm cases, before applying a full face of make-up - and trying out a new edgy look.
", - "This video received over 2M views on YouTube! You can read more about Tilly here
", - "While watching the video, think about the following questions: (drag these questions into your workspace so you are ready to answer them after watching the video):
" + "Meet Tilly
Tilly is a real-life bionic teen. At only 15 months old, Tilly had both her hands amputated at the wrist because of a very rare infection. For years she used basic silicon arms, but in 2018 she became the first child in the UK to have bionic arms. These high-tech, 3D printed arms give Tilly a much fuller range of movement. In class, you will watch a video about Tilly, who is now a model, public speaker and make-up vlogger. In the video, Tilly showcases her colorful arm cases, before applying a full face of make-up - and trying out a new edgy look.
This video received over 2M views on YouTube! You can read more about Tilly here
" + ] + } + }, + { + "id": "9k2YhXILrCaG09h7", + "content": { + "type": "Text", + "format": "html", + "text": [ + "- How does Tilly control her bionic arm?
Write your thoughts and other questions you may have on the sticky notes your teacher gives you. These will form a Driving Question board for you to refer to at any time through this unit!
" ] } }, - {"id": "9k2YhXILrCaG09h7", "content": {"type": "Text", "format": "html", "text": ["- How does the bionic lower arm appear to be physically attached to Tilly’s upper arm?
", "- How does Tilly control her bionic arm?
"]}}, { "id": "ULWVknRyAIhw-jUC", "content": { "type": "Text", "format": "html", "text": [ - "How does Tilly control her bionic arms?
", - "Create a model on paper or a whiteboard or in a drawing tile that explains how Tilly's bionic arms work. If you worked on paper or a whiteboard, take a picture of your model and upload it to your workspace in an image tile.
", - "Reflection
", - "At the end of the activity, please record your current thinking and learning in your Learning journal (see Reflection tab).
" + "How does Tilly control her bionic arms?
Drag this tile into your workspace and answer the following questions
-What challenges might come up if you were using bionic arms?
" + ] + } + }, + { + "id": "VdAiT8NSjSK7-XoX", + "title": "Text 1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Now, choose one challenge you came up with and think about what is needed to solve this challenge. This is the first step of the engineering design process, called a “need statement.” Your statement should be in the following form (drag and drop this prompt into your workspace):
“People using a bionic arm need X in order to do Y.”
" + ] + } + }, + { + "id": "BnMKCNJn1Jf7Mluh", + "title": "Text 2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Next, let’s dive deeper into how bionic arms work.
Create a diagram or a flowchart that explains how you think Tilly is controlling her bionic arms.
You can create the diagram on paper or a whiteboard, or in a ‘Sketch’ drawing tile here in CLUE. Be sure to add anything you think is important to how Tilly controls the bionic arms:
How does the bionic arm connect to Tilly’s body? What does Tilly need to do to make the bionic arm move? Can Tilly know how hard or soft an object is when using the bionic arm? What might happen if Tilly accidentally touches a hot surface using the bionic arm? What happens if Tilly’s bionic arm gets wet?
" + ] + } + }, + { + "id": "insZMAlarK_8CmV9", + "title": "Text 3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "If you worked on paper or a whiteboard, take a picture of your work and upload it to your workspace in an ‘Image’ tile.
" + ] + } + }, + { + "id": "oJlCuTXa-E6V6wjz", + "title": "Text 4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "To help you develop the model, you can read more about Tilly and her bionic arms here.
" + ] + } + }, + { + "id": "-1r_bo8VFfrwv8Nr", + "title": "Text 5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Reflection
At the end of the activity, please record your current thinking and learning in your Learning journal (see Reflection tab).
" ] } } diff --git a/curriculum/brain/investigation-1/problem-1/reflection/content.json b/curriculum/brain/investigation-1/problem-1/reflection/content.json index 6023b72f8..b17fdf57c 100644 --- a/curriculum/brain/investigation-1/problem-1/reflection/content.json +++ b/curriculum/brain/investigation-1/problem-1/reflection/content.json @@ -2,30 +2,13 @@ "type": "reflection", "content": { "tiles": [ - { - "id": "P7m0jRM_FltsX8Gt", - "content": { - "type": "Text", - "format": "html", - "text": [ - "As you recall, throughout the neural engineering unit, you will keep a learning journal.
", - "To access your journal, click on "My Work" >> "Learning Journals"
", - "Click on "My First Learning Log" and click "Edit" .
", - "Then, come back to this tab, drag the template below into your workspace, and answer the following questions.
" - ] - } - }, { "id": "YMXYngGJlN6ss7na", "content": { "type": "Text", "format": "html", "text": [ - "Lesson 1.1 Journal Entry
", - "1. Today's date:
", - "2. Today's topic:
", - "3. Based on the video and the class discussion, please describe your current understanding of how bionic arms work.
", - "4. What questions would you like to ask Tilly (the teen with the bionic arms from the video)?
" + "Lesson 1.1 Journal Entry
1. Today's date:
2. Today's topic:
3. Based on the video and the class discussion, please describe your current understanding of how bionic arms work.
4. What questions would you like to ask Tilly (the teen with the bionic arms from the video)?
" ] } } diff --git a/curriculum/brain/investigation-1/problem-4/labWork/content.json b/curriculum/brain/investigation-1/problem-4/labWork/content.json index 9048e8d71..903d1224a 100644 --- a/curriculum/brain/investigation-1/problem-4/labWork/content.json +++ b/curriculum/brain/investigation-1/problem-4/labWork/content.json @@ -8,94 +8,303 @@ "type": "Text", "format": "html", "text": [ - "Visualize and Record Muscle Activity
", - "Let’s measure your muscle activity! In order to make muscle activity usable as data to drive Bionics, we need to be able to measure it. For this, we will use EMG sensors, which measure the electrical activity that occurs when you contract or expand your muscles.
", - "For this activity you will need the following materials:
" + "Visualize and Record Muscle Activity
Let’s measure your muscle activity! In order to make muscle activity usable as data to drive Bionics, we need to be able to measure it. For this, we will use EMG sensors, which measure the electrical activity that occurs when you contract or expand your muscles.
For this activity you will need the following materials:
" ] } }, [ - {"id": "PodHYZ4go3HA1HYi", "title": "SpikerShield", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/1.jpg", "filename": "curriculum/neural-engineering/images/1.jpg"}}, { - "id": "2gcDnEdA3OTheS9w", + "id": "scY3qeK6fevx-N_M", + "title": "Arduino Board + Muscle SpikerShield", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "h7P3h8mhehe_Cuzr", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Muscle SpikerShield (yellow board) coupled with an Arduino board (blue). The Muscle SpikerShield allows you to record your muscle's electrical activity (known as Electromyography or EMG). The yellow board has a small switch that reads 'EMG' on one side and 'Control' on the other. The switch should be on the 'Control' position.
" + ] + } + } + ], + [ + { + "id": "c2Nc8ld4a9i2pmbx", + "title": "Muslce Electrode Cable", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "3TxP81BNLdqAWksC", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Orange Muscle Electrode Cable with 3 alligator clips (two reds, one black).
" + ] + } + } + ], + [ + { + "id": "SIr0NWdgdwv44aE2", + "title": "USB Cord", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "Kh590E5YLoZa_HR-", "content": { "type": "Text", "format": "html", "text": [ - "Muscle SpikerShield (yellow board) coupled with an Arduino board (blue). The Muscle SpikerShield allows you to record your muscle's electrical activity (known as Electromyography or EMG). The yellow board has a small switch that reads 'EMG' on one side and 'Control' on the other. The switch should be on the 'EMG' position.
" + "A USB cord that connects the Arduino board to a computer.
" ] } } ], [ - {"id": "4pWC3KJXXdYoa5vv", "title": "Alligator clips", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/2.jpg", "filename": "curriculum/neural-engineering/images/2.jpg"}}, - {"id": "h7P3h8mhehe_Cuzr", "content": {"type": "Text", "format": "html", "text": ["Orange Muscle Electrode Cable with 3 alligator clips (two reds, one black).
"]}} + { + "id": "s49R8O845npMyLLG", + "title": "Electrodes", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "XPhporOEXVAjaiKE", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Electrodes - used to pick up electrical signals from your muscles.
" + ] + } + } ], + { + "id": "hB0y5oGIJC8z8tgZ", + "title": "gripper", + "content": { + "type": "Image", + "url": "brain/images/6.png", + "filename": "brain/images/6.png" + } + }, + { + "id": "hRL2PzfJH5u7ohJD", + "content": { + "type": "Text", + "format": "html", + "text": [ + "1. Connect the Arduino board to your computer using the blue USB cable.
" + ] + } + }, [ - {"id": "vn4aa8kjXblKIQSA", "title": "USB Cable connects Arduino to Computer", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/Lesson1_4img2.jpeg", "filename": "curriculum/neural-engineering/images/Lesson1_4img2.jpeg"}}, - {"id": "3TxP81BNLdqAWksC", "content": {"type": "Text", "format": "html", "text": ["A USB data cable that connects the Arduino board to a computer.
"]}} + { + "id": "snpApQ6yy3fTMz19", + "title": "Electrode Placement", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "AIaXlh5Jt6mO1ko4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "2. Decide who is going to be the study participant (you can take turns). Place two electrode stickers on the participant’s forearm close to each other and another one on the participant’s elbow (this is the reference electrode)
" + ] + } + } ], [ - {"id": "I_o28skM9_9QVzEu", "title": "Sticker Electrodes", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/4.jpg", "filename": "curriculum/neural-engineering/images/4.jpg"}}, - {"id": "Kh590E5YLoZa_HR-", "content": {"type": "Text", "format": "html", "text": ["Sticker electrodes - used to pick up electrical signals from your muscles.
"]}} + { + "id": "wd_J3rIeqseIg0GA", + "title": "Connected Arduino", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "Xf1VSQp7lP4Hckuo", + "content": { + "type": "Text", + "format": "html", + "text": [ + "3. Connect the orange muscle electrode cable (the one with the three alligators) to the Muscle SpikerShield orange connector:
" + ] + } + } ], [ - {"id": "Twbv6PU3nxhlG4qd", "title": "SpikeRecorder App", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/5.jpg", "filename": "curriculum/neural-engineering/images/5.jpg"}}, - {"id": "XPhporOEXVAjaiKE", "content": {"type": "Text", "format": "html", "text": ["A computer desktop with the Backyard Brains Spike Recorder app.
"]}} + { + "id": "2up07sY25_eJd8nj", + "title": "Alligator Clip Placement", + "content": { + "type": "Image", + "url": 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" 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Connect the two red alligator clips to the electrodes on your arm. The black cable should be connected to the reference electrode:
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H6DoG7x1vRavaRvNDYXexn4jpZeGI6Bu8db0Wr2kbzR2F3sZ2I6WXhj9B0Dd463otXtI3mjsLvYzsR0svDH6DoG7xxvRavaRvNDYXexn4jpZeGI6Bu8cb0Wr2kbzQ2F3sZ+I6WXhiOgbvHG9Fq9pG80Nhd7GfiOll4YjoG7x1vRavaRvNDYXexnYjpZeGI6Bu8db0Wr2kbzQ2F3sZ2I6WXhj9B0Dd463otXtI3mhsLvYzsR0svDEdA3eOt6LV7SN5obC72M7EdLLwx+hS+SXKg4fJzZ2QENrJs7Z6pVv7ge24U0VKz6NuKbLF3n3W3V1O62mhsMdxmt2kviVGRPV2F7Cn8pFbc5ztt4rY6ZGBsGl8q4Y+OtnKLNU3Xkaiqsfyc75jp2dX1gSEXRN8mecfO6Qq2dtHCxsa7Iw8vNxrMLaFmdU1eDdg0ZCXG7B2e9Vm9tCg1hEuV1FurVlVDgW1f1i/wBD/DybL0Eesyop8cn1EY1GAj902WNb3lz/AKN9yAIldbaBUsVRpqT2SEW5F8hto4+dU1qLk1hXKbr5dxY6KrFgFuPejeA1+EGAWDk/Xum9AWKpfou+7OQODSdN5yzaaknt8MAytsbZpx62uvtrpqQavZa61oo+Es5AH+c+dSpCnFzm1FLlbtq95Jw2Fq4mcadGEqk5O0YwTbberQrmjsj3X2FbtDEwMCt8nujKqofKbWqlFdwrGsMOJaQNdDuoh6jvMOo6v9oaNSvChQWe5TinN6IrS7ru7+RnVaX+HGNo5Pr5Qx8o0VSoyqRorzqknZWznqhr1PzvZym/ZthyEQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQCj86Oc6LRuO6amzXcZl10Caa7pGukAoHTt/y93nbPWgDp2/5e7ztnrQB07f8AL3eds9aAOnb/AJe7ztnrQB07f8vd52z1oA6dv+Xu87Z60AdO3/L3eds9aAOnb/l7vO2etAO3F2nkuwVLb2ZuoAW2En/1dgHWSeoAEnsgHGVtTJRir3XKw7QbX8IBHY2mhBBBHUQQR2wDqG37/l7vO2etAMirOymUuLbyg3u+4z6d4FZv63gDKf8Ar8+gGP09f8vd8H9K/rQDNptzGQ2q+Q1Y3tWFrn9EAt1b2uihgSdNADqTAMRNtZB1IuvIUatpbYd0ahdT33UN5lXU+EgeGAfI29f8vd51/WgHPTt/y93nbPWgFg5H7LvyuJZbm242LSypZcbiGaxgpFaGxuGmgdCzurg76KqkligGyPelTx7aPpCexgD3pk8e2j6QnsYBz70iePbR9IT2MAe9Inj20fSE9jAHvSJ49tH0hPYwDFz+bS6pS+JnZJtXrFeU62UWf8jbtaum9+iLBvBNddx9NIB98mNujJpWzdKNqyWVntrtQlbKz1nrVgQRqdD1anSAatt/ZbZv0bYf8XhSbjuM1u0l8SlyJ6uwvYU/lK9zs8g9pbYz9odz49aV4WGuBgX5jZGMa8+5sfaFu0MMdyX1ZYpspwKls1RFsx76w/fWhIRdExsblDZl7b5O5NuPdi238mtvWW419bV20Wtncl+LU6OAQa7N5ddNGADDUEGAbXH6xf6H+Hk2XoI9ZlRT45PqI+tmYquuWjDVXvtRhqRqrVVqRqOsdRPWOuQi3IHkDzeV4t2Tcte5vuaqFJLlKE0Gu8xY63uvEOp1ChB1dagCw7IHfZXg/Pnr+D8xT1zDV1/vQek7a9Kunb3a1+Z5A90V7nzb1trZRybNr0KSyVD83djr1kBMNNKXKgkb9A4zDQFT2zm2W8k42blVz3WgtObypab+atdu98x+n9xO7DINClDDOjHA1mknVazoVXo11pJzV2lol/w07u8TQHN9su+3aOJj0WnFyWyqqq7GUh8e7eGjMhAYMh0JQgHyTT8HRqcJhTi3Tln6G1pT0q/5ajsmW8Vh6eTMRiK0FiKCoynKMZJxqR0KymtFntK56/HMXyq/tQfMf/xM6Z5NyhyYj/tkfmv7V7lnrySv1pfuOTzJcrP7T/8AYH/vWZjyblHp/wDtZj7U7lP/AKT/AP2l+4495fld/aYeYX2BmFk/KS/6/wD2yM/afck//lT/ACrS/edmJzPcrldS3KRHUOpZeAo3lDAsuox/CNRr1aT3HA5STWdXVrq65bHyrbotyc6c4wyXKM3CajLfpPNk4tRlbP02dnblPSBm26eX2aefRpOKXT1f29y92pnEGBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAoHO1+jj/APms+xIBrmAIAgCAIAgCAIBmbIyxXYrlmXTe75UWw98pXQo5Cup13WViAVLCAWbD5UYqb2lbgGyttwIgTVGoYuFFmiFjXYdzvwvECqyje3gOzZnK+tmQWagBQd5kQgOrZHfaeE8J6ax8O4AdAAYBj2crqiACrsQrAuyoGdzXjpxGG+2jE1NroWOm6dSS2gErsjlXS5cuwrfeYIzqvVU1zOi6Ky76VroGpDd9qoUOAdAK7gco0SjglSWPdP50KpdOMlSqULMOp9xksGincfqYEQCSy+WFJVkTigGpk1ZV1YcWqxEbSz9HdSxCV3Qu+Stf9WAQ/KrbiXuCg0A3tAU3CoLaqmvFt3gg6hpw1A6gijQACEgF85vL6MjHyNnXGtLLbeLjtYqsGJROtAxAN9LozAAhgjIy/ovugWnl9zQWZuW2SuVwA2NXjsgpNhcV22WlHZ7dzgWlwltVddZtQFbHtHCFIGTyA5rnwrja2Ql+tK16mmxbV0rxqxVXY2RYExEOO1leMa2KWX2EWDVt8DYmsAawBrAKXyq2NiUOc3IueqpWW22jeAoyMivd4FrVbpstyawgWuuttLWFRau16MZqQILkFjOKXssUo2TkZGVwzprWL7DYqHTUaqD1kHr7fDAIzmu2DVk7B2bTetVlNuy8VLKrQGV0NC6hlIIIP/8AdJNx3Ga3aT+JS5E9XYXsKfymV7yGy/F6vPX+vIRdElyd5s8HEsa3HpoqsZOGbAzM/D3gxQM+8VQsFYqpAYqpOu6ugHbVUTtJwOsnD0/2JNl6CPWZUU+OT6iM+3kQCzN+dUud5tzItQFtANd1LQuugHYJCLc+f5Df82R6Xf7aAZez+S5qBCq3fNvMWsLsW0C6lndm7FA7fBAMroqz4PrX75m4Kpyh5l8TKycfMtxazlY1qW05C7qWhkOqh3Ug2J/yWby/BodCK+rgaFWcakoLPi1KMlod1yO2taeXQbBhMvY/C4ethKdWW8V4OFSi/Oi02ndZ11F6NcbO2jUWvomz4v1r98nWNfHRNnxfrX75kDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98AdE2fF+tfvgDomz4v1r98Ajts8iFyN0W1ltzXd0crprpr+iw17B2wCL96PH+RPnX9pAHvR4/yJ86/tIA96PH+RPnX9pAHvR4/yJ86/tIA96PH+RPnX9pAHvR4/wAifOv7SAPejx/kT51/aQB70eP8ifOv7SAPejx/kT51/aQB70eP8ifOv7SAPejx/kT51/aQB70eP8ifOv7SAPekx/kT55/aQB70eP8AInzr+0gD3o8f5E+df2kAe9Hj/Inzr+0gD3o8f5E+df2kA+beZ3GYFWo3ge0NYxB+cF9DAPj3mcXxcecb14A95nF8X/7jevAHvM4vi/8A3G9eAPeZxfF/+43rwB7zOL4v/wBxvXgHfs/mlxqnFi4yb6/osx3yvzbzED/KAWPomz4v1j74BpvZG3rcbkzs+2gqt3cGzKq2dd9UbIfHx+IU1UPwxaXCEgMVAPUTJuO4zW7SXxKXInq7C9hT+UwMTldaxyeJtjMxasWvItsyczZWJjYrU4tvCvtqvtpWuyuttNWBA3WVhqDIRdHbyI5ynt2nh41W0qdq4ebs7amUMiuvHXhX7My9lY5rV8bRGDjaT76uCyNSmmm+0A2Uh/nF/of4eTZegj1mVFPjk+oib4p+E/5mQi3Kdzvc5g2Rs7I2g9b3jH4Q4SvuFzdfVQo3yGCgNaGJ3W70HQE6CW2ScnSyhioYaLUHO9pPUrJy029i7yBjsWsLRlVacs3NVlr85pf1PNv/ANoqv7ps9PX8LOjf5fVVrrx8Ema39o49HLvS+LMvZH//AEAe+xKqdiZV9jnRaqMxbLW0BZtxDjqpIUFiXdEABLOgBYRsRuFlh6cqtTEU4RiruUlJRXNfl06kkm3qSbPrSy+qslCNOV217bK6V3bTZX0nrdb9esNqD2ENqCPhBB0IM5azbU7q5902nUdZ7R4T8MwZJHlTnvXUprIVnuoqDEb26LrkrLAHqJAYka9Wunb2QCu8ptqX4zYqtk2P3VlJiqVpoARnV2DtqvWo3CNB16kQCVWy+q7HV7+MlzWIQ1aJu7tT2BgUA8KaEHUaGAWWAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAQGS11t9laWmlKkrOqJWzu1m+TqbVdQihRoAupJJ1GgBA+ugr/Hb/N4n4eAc9A3+O3+bxPw8AdA3+O3+bxPw8AdA3+O3+bxPw8AdA3+O3+bxPw8AdA3+O3+bxPw8A68O22rISl7TcttNtis6Iro1T0qV/NqiMrC4EaoGUqetg2igSO0NoFN7QA7iGxidT3o16lA62Y7p8I8HbrAIZ+VzDtpuHUT149vYNNT8w1Gp8GogGbgbdZ9SUKgMqkMj1t35AVgG7RqfJ4fg6wJqAcwBAPNVx05KYDaEivC2Pa+gJ3a6cjEttchQTu11o7sQDoqk+CTcdxmt2kviUuRPV2F7Cn8pH5POXsTcYDlBs2wVm18atsyqhN6203FMkq9qX1nXc7/GfcHfhSwUyEXRg8h9vVZvKPGyca/EylTZm3WyWwbzlY+K+Vk8mkxarL+HV+cvTAybVVq0J4dgAbhliBuwfrF/of4eTZegj1mVFPjk+oiZkItzXfuhOQGRtTY+Zg4vD493c5r4rFK9acqm9gzKrkarWQO9PWR2do2HIGOp4HG0sRWvmQzr5qu9MZLRdrn5ysyjh54jDypwtnNpq7stDT12fNzHjT8hbb/wYHpj/hp2V7usmPpvBH95o/kHGc0PG/2lk5u/cocpNm5S5VVezLDw3qauzMtVHrsA3lLpis9Z3grB1VyCv6LgsjUuWN0+ScpYaWHm60U2mmoR0NXSut80rS76Sfg8k43D1o1UoaND85vzW1eyzVp0aO661nuLZuzlprWtNd1BoNTqe0nr/wCpnFHbkd/ab2vaZlPaPnH2zBkzeWX9HV9Lwv4qqAUrl5zJ4+TdRdXQm+2YluYzW2g2UbtnECjeI3ixQ6KE6gesdhAsdHJynEfBpx04dYvvIXeZtC2PcWOrlm6yfhgFwgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgELs3/xWV/5cf7LIBDc6GPfbXjY9CMxvy6RYQ9tSJTRvZb8a6pXauq4464x707/ABwn9cwCpYI2hhpcnFtemjIqqH/C5GS//FWnIvtqJN2Rfi4lWVXi0KikVtjObGZFeusCH983aW+1YG89S5JSsY1nEynrXMyKcdtK2rqy3xejmesvQKnsywVJWutAJjlFyn2rVZwsdbMmypLha74T1491hwrbKGodFdeEMx8Sn+mLqq5IZbd3iVgT/JPaO0Gyt24s2NpnDebG4J/4e/HpoYtr1m4nKsr0AV8daWGp1stA7+bRmezaFzHLIty/zQy6smllqTHoQCuvIrqC1m3jMvCQKVKltXLsQJ3O/wDG4/0bM/3MKAd21KC3HUDUtj7oHV1k8UAdfV1n4eqAU/bmfVVZXW6qHsWxes468MHdKs4AbQMRoCWXsPWOuAWLBwmRH1Xd1ejT9Aa6Ouv6BI/6nrMAsggHMAQDU/Mtu9DbJ1LA9HYfYB8ivwkSbjuM1u0n8SlyJ6uwvYU/lRc99fjWf5D1pCLo4Yp8L/5L60Ar/wD8Rs+h/h5Nl6CPWZUU+OT6iJiQi3KVzp8mr8mmtaAxZGsbQWhAWamyus2KTWz1q7hy1N+PkVMq2VPvJusBVszk/wAoX4+mYlbB8hqBWmPwz+a2j3JWXtrvsanfs2aLt5abd+izQshta9pBJLs3bXFOt2tfdNjKdcVdKjfjsi2JwrGfHXGXJr1R0yHexDuUd69K4LpyO2ffViY1eTc+RkpTWMi+zhB7bt0cViKKqKR3+oArprUKB3vwgTdPaPnH2wDJ5c1k0oASpOViAMum8pOTUAy7wZdV7RvKRqOsHsgH1/Jy3x7K/wAsT8LAMDI2U9eThlsi67W20AWCkAf8Nd1jhU1nXwdZI8kAt8AQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAgszBvS57aBVYLVRXS2x6t017+jK6VXahg2hUoNCNd46kQDjuvO8XxPTLvwMAd153i+J6Zd+BgGNXj5QdrBiYIsYANYMqwOwHYGfuDeIHgBJAgGT3VneL4npl34GAO687xfE9Mu/AwB3XneL4npl34GAc4Oz72uW68VJw67K0Sp3t14rVs7M710/JIFUV9XfEsdQFAlL8Ult5W3TpodRvAjXUdWo7NT16+GAYOXsHfdLH4bPWSUY19akjTq7//AKjXsPWOsAwDK7iY6bzggEHQLu6kEEanU9WoB0gGbAEAQDzFtPnV6E5J4O0eB3Rwdn7MTcNhqqTjmmjj5Fy1XNTi0cTi32rTYUqRiFMm47jNbtJfEpciersL2FP5SI2Z7r3Hq4Nm0n2bRivsxs98jZ2bl7Yr1O2KdkUih8fZldV1NtmRSWO+uRVa5Q45Wq21YRdF35B+6U2NtPKXCxMm1slkyWFV2Dn4p1wrEqzKS2VjUoMnFeysXYpYX1B1ZqwGBgF2H6xf6H+Hk2XoI9ZlRT45PqImZCLcr3OBy4p2bh3Zt4saqgJvLUqtYxssSpFUMyLqXdR3zqAOskSwwGCnja8aFOylK9nJ2WhN6X+RXZQxsMFQlXqXcY2uoq70tJWXvf10GlD7ufZXim0/NYf46bp9icZt0vG/2mj/AG5wS/greCP7juxfdvbLdlVcPahLEABaMZ26/gRMxrGP/KiMx8AM+NXcdi6UJTlOklFNvz3ye9WPtQ3a4SrOMIwrNyaSWbF6/YpN6NbstR6HImgtW0HQk7pPn0n1T2j5x9sGTN5Zf0dX0vC/iqoBgcrOQ75Tq65+dibqbm5i21ojdZO+weqwl+vTXXTQDqgGXtOrduwF1LaWWDePWTpi3DU+U9p8sAsUAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBANBclOSr5vJ7ZdFebl7Pc4Gz3XKwmoF6GtEfdAyKMil67NNyxLKmDoSOrWTcdxmt2kviUuRPV2F7Cn8pRcr3Dmy3pFJytoAdzmmxw+KHusfbePt+3KcdybguszcZVKVJVQtDui1Idx0hF0XLkx7nDCxM+naFd2W11OVt7LVHek1GzlDfTkZisBQr7lVlC8ABwyqWDtdqCAL8P1i/0P8PJsvQR6zKinxyfURMyEW5rv3QvJPIztj5mNi18W+wUFKwyqW4eTTa2jOyqCERiNWGpGnaRNiyBi6WFx1KtVebCOdeWl2vGS1K71vkRre6DBVMXgatGks6cs3NjdK9pKXLo5OU8Xfky7e/dtnnsX287N9qsm9MvDU/acRW5TKdvQP8AOUP3Fp5suZjbuBlpkHZFlo3LKyO6MRGUWjdL1ubyFcfCeooXUld7eFFlrLGTcfhZ0I4jNb0pqFR3avaLvFKzvr5HYv8AImSMo5PxMa0sM5pXi/PhoTa0rTyW/M9w7J2dwa0qDF9wbu83aesn/oOvQDwDQeCcVenSdyWpL2GdT2j5x9swZJ/auy1uTcfXTVWBVirKyMHVlYdYKsAQfJAI8clB4xlefaAdmJyYRXWwvdYya7nFtZwpYFSQD1alSRqdeomATEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBANP80u1Kqdh7MstNaV17LxXstsfcREWhSzOxZVVVAJLMQAPDJuO4zW7SfxKXInq7C9hT+Uifyq+S/7/ANgf/nGF+KkIuiz8i+dnZW0uJ0dnbOz+Fpxe4s2nK4e92b/Aus3NfBvaawDJ1/nGz6H+Hk2XoI9ZlRT45PqImJCLc17y3TaS5QsxRZbj8LCpehWpUE3ZlgyMlGsKsLMOkUu67wFmM94VbbVqSARVW2tvWmndprxgO5lvNuOlhZms2SmU1e7mjdSqu7azIxD6vjUtpYihMoDGxtt7eWvXudWd9HtDoFFBamlt3H3bbmuU3G1GQqTUAO+I/OsBsbklblNUzZYVbWtt3a0UAV1LYy1DUWWb5asLYX1Gu/poNNIBO09o+cfbALXAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQDzVaoPJXZwPWDi7EBB7CDl4QII8II1BHhEm47jNbtJfEpciersL2FP5TXXKw5ytkWJtTaSd5tK9UW+oVoaLfzSIv8nn0qUNu7nHt71QO6Oou8Iuif5A1uvKDZq2XXZDV7K5SoLshg9xTuvklYqu4w8HUIbG3f+Gr0B/r/psBvQfrF/of4eTZegj1mVFPjk+oiZkItyO5RcoacSl8i9tyqsAu26zabzBF71AzHVmA6ge2ScNh54moqVJXlLUrpfzejkIeMxdLCUpVqzzYRtdpN63bUtL1lG/KM2R4y/o2T7KbB9msfsL9SBrP2tyZ0kv0ahz+UZsjw5LgfC2PkqB5STVoAO0kzzLc5j4ptwWj/wDJH+mk9R3W5Mk0lOWlpL/hTWl87krI2URNZasbendXPqntHzj7ZgyWuAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgHxbcFGrEAfCToP8AMzKTbstLF7GP0rV8pX/rX759N6nsvuZ4z4867x0rV8pX/rX743qey+5jPjzrvHStXyif61++N6nsvuYz4867zkbVq+Ur/wBa/fG9T2X3MZ8edd5x0rV8on+tfvjep7L7mM+POh0rV8on+tfvjep7L7mM+POh0rV8on+tfvjep7L7mM+POh0rV8on+tfvjep7L7mM+POh0rV8on+tfvjep7L7mM+POh0rV8pX/rX743qey+5jPjzrvOelavlK/wDWv3xvU9l9zGfHnXefVe0EJ0V1J+AMCfqM8unJaWmvemjKmnoud4M8Ho5gCAIAgCAIAgCAIAgCAIAgCAIAgGgeTPJl8zk3s7HrsWqxtnbOeux0NiLbRwb699AyFqy9ShwrK26ToQdJNx3Ga3aS+JS5E9XYXsKfykfnc0+Xbvb9eziHW9GAyNqAbmQd65Ru3DQOQOzQroN0rIRdEjyU5qr69pVbQvfHXgYedjJTj90PxG2hds2y622zIdiNxdl0JWiKB39hJ1A1Auw/WL/Q/wAPJsvQR6zKinxyfURMyEW5Rue/Ztl2y8qupHssPBIRFLO27kVM2iqCToqk6Aa6CX+QqsKWOpym1FK929CV018Wa1ujozq5Pqwppyk820Yq7dmnoXu0nk48gc/xHM9Gu9Sdj8p4TpYeJHC3krGvVRqeFlg5DcmsujISy3Z+ay6MoIxbC1bsNFsUOqrqvWOtl0DFgdVWUeV8TRxGGnCjWhGWh/fWlK91o5y8yLhsRhsXTqVsPUlBaLON0m2rS/LT3nr/AGTiPXWiO/EdRoz9ffHU/CSToOrUnU6antnGnrfvO+J3Sa5Vczqe0fOPtmDJa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAed/d37Qsr5P3tXY9bHIxFLVuyNutkVKy6qQdGUlSNesEjsJm8bjKcKmU6cZpSWZU0SV1og2tD5ma9l2Uo4VuLaedDVo1ySPzj2JmX3X0U903px76aN/iXPuca1a9/cRi9m5vb24gLvpuqCSBO9YmlQoUalVUqcsynOebmRV82Lla9tF7WvyazncalSU1HOkryS+89F3Y2Vh8x208gVWYWb3Rj3ivg3WZS1C5ntethS2Hl7TxbUrCLY1q5nWr7gU212UjT4bo8nw83EUFCabzo06WfZJJq++RoyTveNs16Yt3zWmW7yfiXpjNtarynKLzldWsnJcnPdcqurEfTzP7Wao3rm0tSFFhtXNy2QUcBMlsljwAUx0qs6zYqWuyWCuq7d1Mj7Q5Lzsx0ZKWrNdCCednZuZ977za0clrXktNvnwLE2zlPRa6e+ys1rv7rab/wAuV4G0OQWdRlYOLk56VNnugrdMjLv4dVlxoqyHREB4d7g8FQQ7D+kXH0bdm0spYSvQr16GHzlQi3LOpwheSV5RT06Yr73/AG52i8epRr06kKc6ls9pLz5StnaE3q0N6Fz+zTam7Q2nkJZZX3TeeHY9evGtGu45XXTf6tdNdNTpr2mX9CjQqU4VN6prPhGVsyOjOV7auQhzqVIylHPn5ravny02bV9fLY6RtzI8Yv8APW+tPvwah0dPwR+h536ptz8cvqBtzI8Yv89b60cGodHT8EfoN+qbc/HL6g7cyPGL/PW+tHBqHR0/BH6Dfqm3Pxy+oO3Mjxi/z1vrTCwtDo6fgj9Bv1Tbn45fUdO5HjF/nrPWjgtDo6fgj9Bv1Tal45fUytlbZtNtYe+7cNiB97JtrXdLANvOCxQaa6uFYr2gHTSfOrhaWZJwpwzktFqcW7+6x9IVZ3TcpWvb77X9Td3udtqqnKbZdeLl33Y9nEDM99jGz8zexFtTBRWQyJpXo3eoj72rmaVl+hfJdedSnGE1ZrNgo2WhaGtPL3l1k+bWMpxjOTWm6cm763qeg/ThZ+e0dKOZkCAIAgCAIAgCAIAgCAIAgCAIAgGk+bzlUmHyf2bkWlhXXs3CJCIXdmautEREALO9jsqKo7WYDq7ZNx3Ga3aT+JS5E9XYXsKfykj76tn7t2r8H/hqfxHVIRdHfsTnVS7JXDarKxcl6LcmqrKpWs3U0WU1XvUVexWFL5FCuCVI4ydRB1AGdr/ONn0P8PJsvQR6zKinxyfURMiQi3NI7M5y9p1UVu+NmZN701NlI+HwqsLJNdz301rXVW9lYvQYyBcjObcNV/GuDp3SBKbY51dpVK7dGM/5y3hhEyW0SuzaSItulQYteMLHIsqRtzu1NKsjSkZQGPyr50dp1fm68J9+yvJZLVxMq+ujcq2hZQ1gXQu+uHWrVBVV3y6lWwNwkyALNsDlpmXZIpOKK6e/Z7nryECbrWJ3ON9VDXALXZxVJpdbtE3tzfcC/U9o+cfbALXAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQDzh7vz9nrvpOH/ABVU33cT60p9Wp8kjW90HFH16fzo/ODk7sq+/IopxVdsm26tMda23HNxccMo+q8NlfRhYWUV6b28u7qP0Bi69KhRnVrW3uMXn3Wcs21mnHlT1W5dRzqFOVSahD7zei2h39j/AJ35NZ6Ot9zPy3ZmY23Evw94jaw6+Ed6rstGm42rDTTrJPhM5tHdBudVkqatG9v+Xu7vXe70+y97chscsmZTk3p0PWt85tVtGj22tfludGD7lnlnUi11tZWiMrIibVVVVkCqhAFugCqiAKO90Veo7q6Znui3PTblKn5zum94V2nrevXy31mFkrKKVlqWpZ/JycnNyaveYOb7jjlZbYt1lYsuQ7yWPtGt7EbiNbqjmwsh4rvb3pHfszdrEmXT3WZEpwlTgpKElaUFRtF6M27Sem8Uk/YrHzlkfHuSk7OWpXnfVq020JGC/uHuUxJJxKSSSSTm0Ekk6kk7+pJPWSfDJEd22SkklKdkrJKnoSWpL2Hh5Exr05sfH/Y+fyGuUvilHplHrTP23yXtVP0/7mPIeM2Y+P8A0nJ9w1yl8Uo9Mo9aPtvkvaqfp/3M+Q8Zsw8f+kfkNcpfFKPTKPWj7b5L2qn6Y8h4zZh4/wDSPyGuUvilHplHrR9t8l7VT9P+48h4zZj4/wDSPyGuUvilHplHrR9t8l7VT9P+48h4zZj4/wDSUvnP9z1tfY1Vd+0MZa6bbOClld1Vy8XdZwjBGLKWVHIJG73hGoJUNc5M3Q4LKVR0sPJ56jnZsouLaWhtPU7c2v8AnaDisn18MlKrFJN2undX9uhW9+r87Xl/ckftJsr++u/hb5H3Vu+TK/uj80T7ZJ43T97+Vn6wz8yI6sJkCAIAgCAIAgCAIAgCAIAgCAIAgHmqz9ltm/Rdh/xeFJuO4zW7SXxKXInq7C9hT+U1ptT3S3J3YSbaGzHe/aFu1cprse2y0o+eTuX279h73EpsRq3C6MXTcUbrVvIRdGVzC86l+2do7BzMkVcboXlTS7U9Vdhp2lyYUOF1O4WGm8oYjeBI0BCgD0eP1i/0P8PJsvQR6zKinxyfURMyEW50Z2elal7GCIvazHQDr06yfhJA+cz3CEptRgs6T1Jaz41a0KMHUqNRitbehLkX8yI/l/heNU+cEm+T8T0cu4rPLOB5a0PEBy+wvGqPOCHgMQlfe5fmeo5YwLdt+p3ehedyk+ZXlvr0rlPqntHzj7YBa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAecPd+fs9d9Jw/4qqb7uJ9aU+rU+SRre6Dij69P50eF/c3fr/Y/0+n7TOxbp1/6Xiez/APcjS8mcbpddr/tZ+kfO/tXLraoU6BPzf6WRdiVMTegyDZk0V2WLZTja2Y9GqpkObARYUVR+ccHCk775e1nZpKbzs2WYs2TXmudlOV24rTZ6n0vESkmrX/J2X/nmR88rOU2VRsiu7jNTdx8Os32iimwY9ufVTxbhfQ1GPdZisHtD0btNjMNxN0BfWHp0513FpOKjUeatKzowbSWa02lLmd2tR4qzlGkndpuUVfls5WfOk7a9BRdq86G0K2trx8pclb9nVVYl+7jZQq2pfk7RC3vZiU49FtFWPjM9iblar3KF757mLTqWHoSzXUi041XKolJxzqKUPNipXalnNq/na72tEizxFSP3WmnBWdtU23e9rX0W5F73eyndh85VxyMUXZb8W2+uh8BUxABTZTXw8h0ZUzNLmfjceq00IPzRqLKdY0sPHMm4pWUc5Tblpd9Mb/d0arWu3pTPtGtLOjnN3cs3NSVrW18/53N4qJTFnY50gWGkCw0gWIblftHIpx7LcXHGXdWAy43FWlrlDLxErscGsXGvf4S2Gut7dxXtpVmtT60YxnNRnLMi3Zyte3ta1257abaUm9B4m3GLcVdrUuc8ve78yLn5PYD5Fa03NtHHNtSWcZa3OJmFkW3cr3wp6t7cUE66dWhPQtw+b5Tmou6VGpZ2s3Zxto5DWcvXeFV9Duro8s+5I/aTZX99d/C3zqW6r1XX/L5kankjjVL3v5WfrDPzMjqwmQIAgCAIAgCAIAgCAIAgCAIAgCAaR5AcklzeT2zceziBLNm4Xf1MFsR0SuyuytiCA9diI66qy6qAVYEgzcdxmt2k/iUuRPV2F7Cn8piNzBZJ1J25tsk9ZJq5P/8A7FIRdEtyR5lRi5K5lmVnZ2RXj3Y1L5fcaiinJsx7cha0wcPCrJufFxizWpYw4KhSgLBgJ3T+cbPof4eTZegj1mVFPjk+oiYkItyp86qk4GRoCf6M9XX2XVk/5DrlvkppYmDbVtP9TW90MXLAVUk2/NejT/FE88cM/Af8p0bfIvTdd6OJqhUt92XhZI7BCCz84uoKsF3kLqHP6JZArFh29W63WQSCARK/H58qUt6klLrLVyrWXOSKcI4qPCYScG9h6+RnpjZVdgrQXMGtA79l7CdT5B16aakAAnXqnM3r06+X3nd7p6VqM2ntHzj7ZgFrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIB5w935+z130nD/iqpvu4n1pT6tT5JGt7oOKPr0/nR+e3NfygtxNpYOVTSci2jKpsTHGu9cwYDhKQCQzgkK2h3ToSGAIPc8rYeGJwdejVkqcZQtvj1Q5bvns1pXLqWk0PBynHEU5Qjnyv5sVrk9VuTn0adGt6Ln6CD3VO0/wCy20fS8T75+f1kPB/jqHgqfQ6i547XwSr4ofuH5VO0v7LbR9LxJ68g4T8dR8FT6C+O/CVfHD+sgfdV7S/sttH0vEjyHhPx1HwVPoL438JV8VP9wPuqdpf2W2j6XiR5Dwn46j4Kn0F8dr4JV8VP9wHuqtpf2W2j6ViR5Bwj/wDjqPhqfQZ2O/CVPFT/AHIflU7S/sttH0vEmFkLCfjqPhqfQZ2P/CVPFT/cx+VVtL+y20fSsT748g4P8dR8NT6DOx/4Sp4qf7x+VTtP+y20fSsT74eQcH+Oo+Gp9BnY/wDCVPFD94/Kq2n/AGW2j6ViTPkHB/jqPhqfQZ2P/CVPFD95ob3YPPdm7RwcXHv2Nk7OqXMF3GvurtDulFyLUoqG6pIsZyXYHRNArakpu+5HJWHw+LlVp4mFeSpuOZTjJaG1dtzto0cn/nWcu1MTvUFVoTpRztc3Fp6NStJ2f5Gq/ckftJsr++u/hb5uG6r1XX/L5ka9kjjVL3v5WfrDPzKjqwmQIAgCAIAgCAIAgCAIAgCAIAgCAaC5M8p2w+Tez8hKxdYmzdnpVU1hqR7bhTRUHsCWFK+JapdxW7KgYhWIAM3HcZrdpL4lLkT1dhewp/KSFu0tvKCWxdigAEknaWfoAPCf5q6pCLogubTnwfNysWhlwbKs7Bzc7EytnZl2TURs/JwcbJquXIxMV67N/PpKab36FoYIQhYDYY/WL/Q/w8my9BHrMqKfHJ9RFd5wOU+ZjWq1VmKMdcLNybK7MW625nxOAQEtTOx61V1tI3WoYggHf7RIRbkbl89DVo1j4ZCa1hCMjeOt7UiprQKPzdSrabL7BxDUiEhbNe9LRqMNX1mZgc6b341l9dG4O6Nm4tTNYLd6zaJwhxSiBRwKO7q2LC3W1UsOlI3S3rOlzvvPG9w5l3IxMPnuDsu7jjdIFlh7pX8xSbceoraOF3mbUchWuxGIFQHXad5RMZz533mcyPMu5EZtTnlyTWUx6MfujXHYcexwErttwmZbqKwbamNGcldVpcrZdVcxRVRK7sHsvPNxyhvyEcZIp49NlCWNQHWpmtw8TLO6tjWMu4ck16GxiwRX73f3VA2pAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQDzh7vz9nrvpOH/FVTfdxPrSn1anySNb3QcUfXp/OjwPzID+edmfS6/wD3naN0Xq7E9n/U1TIXrDD26R37me/9r7Z4b0KAp4lhRyWAKLwbrAyj+sd6tV3ervWLf1TPwdl3dRRyZXhRelxiqlVJX8xzhFRT5JWk5aeSJ+oo05aLaU3/AEIDlDy4ai5xvVbldYsGPw7GycleFY7PRYtgRK6ym6xamwAq289W9XrvlKcKsIzg1KMoqSktTTV0/wA0V1StOMmnqWi1nd+73GPic5dln9Hib2tnBRuP+assFtNe+rik64rrdxa8gKS9a68Nd7QfTNR8+EvZfKY2zeeAWturiumroim61a9S7MoQgIzLe5UPVToeLSwsDr1qGbExwtv+F/noPjI50rkXGs7m4ldmAuRfwt9lXJuoa+imu8hU3DwbKm3698vkYhAQFwVl7DLxDTj5r0rSd1XOvpdbXZUqhTXUm7ZvMbzk2471vqi6MQgvSoDe4A4hID6Ves2PJYxwuTlZxdv7nzg87DEV7+KyF93dJfd3xxrscrWpRv8AiHelrKsbfbiVEHighhPOajKxOm1n/bm9527U5yraLsmqzHWzhu/AFblbLa1xhYNA6kWMLFsFrKVSlHx+qwsxjNR6liJQb0X0ru/r7ST2py0ai24W1O1dNAufgVtdYNGpWwqAQbBWLGsKV1m1kRt1WbdraVhsPv8AUjTTjFt2Tk0l+bdkl7b25zFbFOjnTlFtRjneanJ+5JJtv2JGpfdeZot2NiWbllfEzaHCWruWKGx8kgOmp3W07VJ1HYdCCB03cLS3rKVWF082m1eL0Oz51odzQd2lTfcnU52avOMkpaGvY1r0czNL+5I/aTZX99d/C3zpu6r1XX/L5kcoyTxun1n8rP1hn5mR1YTIEAQBAEAQBAEAQBAEAQBAEAQBAPNN668ldnDXd1xNiDe6u9/4vC77vgV6u3vgR1dYI1Em47jNbtJfEpciersL2FP5SJ5xuTu2dsPVs9N/EwCdcvLeqyrIC97YpRGqWi7J3HWhDW3Cx8mm/IKNphmqEXRM/wAmqMTlHsajHrWtBsLlI5AABeyzaXJl7brCAN+26wtZZY3fO7MxJJMA2YP1i/0P8PJsvQR6zKinxyfURNSEW58W2BQSxAUAkkkAAAdZJPYNNddeqYbsYbtpZE5XKDDdWR8jGZWBBBvq0IP/ANf+RHWPBppPG+Q2o958OEUtuPedy8p8YnQZOOST1AXVdZPg0DeH4I3yPI13mVXpP+KPeSWk9p3PufOFjKp70Abz77adrMdAWJ7SdAB19gAA0AAGQXCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgHnD3fn7PXfScP+Kqm+7ifWlPq1Pkka3ug4o+vT+dH53cgeUi4ediZbKzrj312si6BmVT3wXe0Xe010BIBOgJHaO7ZTwjxeGq0E1F1IOKb1J+22m3uNHyfi1hMTTrtOSpzzrK13yaL6L+9r3o9XH3ZuyvF8/wAzj/ipwap/hriKrzpuhK+i8k22lZa3H2HZvt1glozavttFNfybPtfdobL+Q2h5rH/FSSv8PMdFWjOilzJu3dm6DD3b4J6cyf5xOfy0dl/IbQ81j/ipn/L3KG3R8UvoZ+22C2J+Eflo7L+Q2h5rH/FR/l7lDbo+KX0PK3bYLYqeED3aWy/kNoeax/xUf5e5Q26Pil9D19tsFsT8JwPdp7L+Q2j5rH/Fx/l7lDbo+KX0PD3b4Jf9Op4V/Vo5/LR2X8htDzWP+Lj/AC9yht0vFL6GVu3wT05k/wA4/S5x+Wlsv5DaHmsf8XH+XuUNul4pfQS3b4HYqP3RX9WgPdo7L+Q2h5rH/FR/l9lBf9SkvdKX0H23wNtMKlubNV/jb+Zq73QnuhcTa2HVjY1OSjJkrez3rUi7qVWoFUV3WkkmzXrAACnt1m6blty+IyViJ160oTTg0lC7el+2xqO6TdLQylh4UaMZRefe80lyciTfxRXvckftJsr++u/hb5sG6r1XX/L5kafknjdP3v5WfrDPzMjqwmQIAgCAIAgCAIAgCAIAgCAIAgCAab5rdhU5Owdm05CU203bLxa7abk4ldlb0KGR0ZWVkYEgqwIIk3HcZrdpP4lLkT1dhewp/KdI9zZyf/dOyfQ6vZSEXRO8k+ajZuAzvhYeDiPaoSx8fHWp3RSWVWZKwSoYkhSdNTrAO/T+cbPof4eTZegj1mVFPjk+oiYkItyoc4ZXTH14mvF73c/RLaD9Ly66aburab2gM8y1P3M8Tdov3P4H5hbYrXjXby0hhdaGFQHCB4jair/5Wv6H/Juznkoq71a3q95wavm75O6X35/M/wCXN7LE9zZbM2bblqm0WqTFNdpPEs4NTWBfza23KyNVWe+JcOnfBFLKrMZIw0KbqJVdEeXmvzP2a7k3JlPDVMTGNeyhZ+y8k1mpvkWt8mlL3P8AUTZdlprQ3ALaR34HYDqfKevTTUanQ6zffdq5PcduSSStzGbT2j5x9sGS1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA84e78/Z676Th/xVU33cT60p9Wp8kjW90HFH16fzo/ND/wDz5yToB85PVpP0Q2ldvQlpbehJc9zm3L+ZYdl7FvrLcTZl9+umgsozk3SNddODwydf+bUdXVpKypi6E/u4inG2u1Wm7+JvV7CTGFRa6c3/APrmrd0SQ7nf9yP5vavtpH3+l+Kh46P1Pr5/RT8E/wBoFDfuR/N7U9rG/wBL8XDx0fqPO6KX5xn9AMdv3I/m9q+1jf6X4uHjo/UxmvopeGf0Bx2/cj+b2r7WN/pfi4eOj9TNpdFLwz+gNDfuR/N7U9rG/wBL8VDx0fqPO6KXhn+0dzt+5H83tX20b/S/Fw8dH6jz+ilbqzv8px3O37kfze1fbRv9L8XDx0fqZs+in4J/tOjPfcRmfZHCUA62ONpIqdR74tZduDTt77q6uue41YSaUcTGTbVkp0rv2Kzb0+w+cs7U6Ukudxmrd8UiqAy6dyJc2/7kg/8A3k2V/fXfwt81HdV6rr+5fNEt8k6MVS97+Vn6waz8yo6sczIEAQBAEAQBAEAQBAEAQBAEAQBAPO+zdtXY/JjZ9lD8O7o/ZlSWbquazkPj4/EVHDIzVi0uqurIWUbysNVM3HcZrdpL4lLkT1dhewp/KYGDyOy7LbaE5Yba4tLojo+DybrOtj2V17hs5OqLVeym2tXqLqXqsUHVWAhF0RvNVy8ubaeLjJtfL2vh5mBta82Z2Jg41tGTsvL2RQFp7h2fs7WuxNpWb/Grt1NdRRkG+HA3EP1i/wBD/DybL0Eesyop8cn1ETMhFudeUgKsGAZSp1VgCrDQ6gg6gg9hBEBpPQ1dcxobYHOVs+yqmy7Y2MjNhC66qmvEtevMUr3Rg1CyvHFxorYX8XWs2UvW61neIX47xT2URuC0diPcWPkvyiwL8kUjZFValtKrxRhsuvH2jWjOF0etbF2e1iFRYwZ911q3VaxvNPZXcFhqK/gj3G2p9iSfdPaPnH2wC1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA84e78/Z676Th/xVU33cT60p9Wp8kjW90HFH16fzo8J+50rB2/scEAg7Qo6iNRqCWB0PhBAI+AgHwTsm6VtZLxTWh5i7nJJruNIyfxqiueb/lGTPeGxCbrbjfftexnyNruBh5t68OrAzsfGWuvHRhvd5kBu8O9pWQFdnAnAast7UVCNJJRp/egm25pu7k78xv8ATSldyc7tyfmvRosv6kzt/YqUVYGZh7Q2jal2bgoDZnZF1VlN9gVg1djaHVToQQCp+Ajq8UKjqyqU6kKazac3opxi7xV0018eU+tWkoxjOEpfeS0y/oX/ALrf47f6j98i5kVyLuJTkO63+O3+ozGZHmXcYzn/ALQ7rf47f6j98ZkeZdwzn/tGvH5537tsx1x7Wxqc+nZd+Xx9015t+HTmVhaGUGzG3cnHoa9bd8ZFu7wStdlq+NF9S7j1ptf4WJXlvyrbGW297bhXTQ1z8MuzbtaM7bqKdWbRToANSeqT6NKGa24p6ebmXvPi27251/UqLc89KjWzLuq/SGjtaW/N8QWdSF9OG9OQjBtDvY9xAKpvn2o0eVR7v7mPPXKyVxOcfesStMl3L7+nfl03kNgNbhie/PBv73Q9VNmu7ou97UKL0KK961nluXL/ADPLfuzOZ/FxlxtrYdSY65V7Y2XRUoWrugpZdXkVoui1m1a7RaqjddwjgKzWmzp+5DKladSeBrSc8yGfRlJ3lmpqLg3ypXTi9aSa1Wtp+WcJCFq0FbPebKP8N7N53vdrP8nrvfq9y9zXdzPh7audzYC9uJjLuqprZbKeLkOVYkWAs1ddYXvNxy53+GtXuw3Rpupk6lFNJ2qTevO0O0fdazvr5la7mZEyW2o4uTavphHXota8uZP+FLUteuy9+8huWq5tbMFKOhAdCd7TX9EhtBqG0PgBBBHwE8dN5LNAEAQBAEAQBAEAQBAEAQBAEAQBAPNjVMeSuAVV33MHZFrKiNY3DpvxLrWCIGZtytHfRQSQp0B7JNx3Ga3aS+JS5E9XYXsKfymQdu7Ca2227JOS1mQmTpkVWWCuyvqThHuZXWtV0UVlmQKBoAWctCLoqPNdyUxqds4A2fbflYuPsvb/AHRkWIyiq/aGdyfsoqLmqpSbEw8gooBbdqYntBIG8h+sX+h/h5Nl6CPWZUU+OT6iJmQi3BgEZk8k8V13Xxcd1113WorZdQEGujIRrpWg+ZEH9UaeM9c67zF0d+NsGlDqlNSEkElK1U6qCqnUAdahmAJ6wGYeEzOcudd4ujMnoyfdPaPnH2wC1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA84e78/Z676Th/xVU33cT60p9Wp8kjW90HFH16fzo8Ke5zsA2/sfU6fzhR2/CSQB85JAHwkgeGdk3TJvJWKtsL+Uk33LSaRk5/8AOUes/wCcZHuTDtzMa5mqryqLqcrbA1fYmbtGi6jPy6MhHrfGysMKQMdOvfsB3iCFI1nAqihVjpcWpRpf9aNNqUFJO6kpPl9hv8HKDurpqUv4HJNO3M4rk9pzjjIs3K+58hnt2ph5TGnYu0Nm41Yrue3ItdcnMzKQ9hYu71Ck2OSX4rMCvqmowk5OUUlSnBXrRqSbazYpZqi7c172Rl3azbNtzUlaDgra3e7en+vIbi7kf4rf5H7pAz4PlWvnJlmO5H+K3+k/dGfDnXeLMdyP8Vv9JjOhzrvFnzFDs5mh3Y2Ut+UlVubVtG/DCVGi7MpxEwq7C71m5KxXTj2mmp0U5GPXZr316XfG8b3uu893ZLcrOS73h62pd6rajU4G8u8rqUdd5SrDVSRqpBGuoI6jJ9GrTUWpSWl858pJtprmKp7zynf3sa1g72tpvWKFFoyeIo3XA0Jzcs6kajjdv5usr9c+hzp/mY8/mMjZ3NRw7eJXQ9ettuQwJbdN9ta0taS7Nu6VhhurohNjuVLMWON8orSmn7FrMedZ3R5g92hzu42QuNsjEtS8Yt7ZOZfUwaoZAremvHRl1Ww1iy1rSp3Uc1pqzLYK+pbj8mVoTnj6ycFKnvdKMlZtNpuenSloSV/vJt6tem5ZxcJqNCDzs2V5NPRdJrNvy69OnRYyvc3c5tWZXibJc8PNReBj6qxqyaq1d00sRWFVtVS7jC7cVwisrsztWmtbrtz1anWq4+laVKbzp6UnCTdnodm027rNTstDta7tMi5ThmQw07qUVmQkk7SSV+S9mktOda71cy9vc2vIdsNHNhU22ld7d1Kqq67qgkDU98SToB2Dr01PLjcS5wBAEAQBAEAQBAEAQBAEAQBAEAQDU/Mtu9DbJ13tejsPs0+RX4ZNx3Ga3aT+JS5E9XYXsKfyl11X/wCZ9UhF0fLlPDxPqgFe/wDiNmnif4eTZegj1mVFPjk+oiYkItyp84F+gpHFavecgoASLBoAQ+h03RroQwZTvdYOk+dT7r9z+B5mrxfufs5DwdtLalwttG/bWRZYDWLnIrIcjhg73WE/R18Oms/NuIxNbfaiz5x8+fm75LR5z0Ozto1aOQ4/VrVFOavJec9Cm+f2Mneb2g5OUlV2TfWpV2G5eyPY6jVa0ckhWY9YIBYhSq98ykWeRU8ViqdOtWqQi9N98lpaatHXyq/tsn71OwDdetGFSpKMXyqTWnRZHvbZWW9laPYnDdhqyHtU6nwHrGvboesa6GfoJKyS1+3n9p1TkXuM2ntHzj7ZkFrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIB5w935+zt30nD/AIqqb7uJ9aU+rU+SRre6Dij69P50fmgO3XrBGhBHUQR1gg9oIPWCOwz9ENJpppNPWmrp/kc21O61+zR3PWn7SV/lZmeOZnpWR7SQuA4boaX6MP2n136ptz/Un+4fytzPHMz0rI9pDwGF6Kl+lD9o36ptz/Un+4fyszPHMz0vI9pHAcN0VL9KH7Rv1Tbn+pP9xz/K3M8czPS8n2scBw3RUv0oftG/VNuf6k/qcfytzPHMz0vJ9rHAcN0VL9KH7Rv1Tbn+pP6j+VuZ45mel5HtI4DhuipfpQ/aN+qbc/1J/U4/lZmeOZnpeR7WOA4XoaX6UPoY32ptz/Ul9R/KzM8czPSsj2kcBw3RUv0oftM79U25/qT/AHHVlcocmxSlmTk2IwIZLMi50YHtDKzlSD8BE9RwlCLTjTpprSmqcE0/ZZGN9nyym1ypzk0/em9JgASX/v8A3ydx89SstRt33JP7R7K/vrf4W+anuq05Lre5fMi4yS/+ap9Z/Kz9YBPzMdVOYAgCAIAgCAIAgCAIAgCAIAgCAIB5rdyOSuAAzrxMHZFLFHat+Hffi02qHQq679VjoSpDAMdCJNx3Ga3aS+JS5E9XYXsKfyk5sbmt2bZbmI2FUBj5K0puvfqUOLjXktvPpvB7nA3Sw3QvYd4CEXREY+xK8HlFs/HxFNFGVsXbV19KvYa7bcTN2CmPYyuzDfqTLyVVhodLmB16tANkD9Yv9D/DybL0Eesyop8cn1ETMhFuRHK/NqpxcjIuQ2JjUXZDKoG+RTW1h4ZJXdsIUhWDLodOsdow0pJp6mrMw1dWZr3bfInk7jvuXYVCtuBzpj32Aby3Oil60deLYtFvDq14lhUKqsXrDUfkLJ710YeFafeVjyZhW23Ti29baMbA5J8nbXCLs+pmZ2rCdx5DNvV2ii021GstVXVcRW73Kta6gsd3vo8hZPWlUIXWrQtfceVkrCLSqcb+43GTLxJJJLmLbRyaj6p7R84+2ZBa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAQvK7kbjZ9DY2XTXkUPoWqsUMhKnUEggjUEAj4CAfAJJw2Kq4WoqtGThNamnY+NajCtFwqJSi+R6jXf5JXJ3904fmU9WXv2myp09TxMr/ACTg+ih4Ucfkk8nf3Th+ZT1Y+0+VOnqeJmPJOD6OHhQ/JJ5O/unD8ynqx9psqdPPxMeScH0cPCh+STyd/dOH5lPVj7T5U6ep4mPJOD6OHhQ/JJ5O/unD8ynqx9psqdPPxMeScH0cPCh+STyd/dOH5lPVj7T5U6ep4mPJOD6OHhQ/JJ5O/unD8ynqx9psqdPPxMeScH0cPCh+STyd/dOH5lPVj7T5U6ep4mPJOD6OHhQ/JJ5O/unD8ynqx9psqdPPxMeScH0cPCh+STyd/dOH5lPVj7T5U6ep4mPJOD6OHhQ/JJ5O/unD8ynqx9psqdPPxMeScH0cPCiZ5J+562Ng3rk4mz8ai9AQttdSKyg9uhAB65ExWW8diob3WqynDR5sndH3pYDD0XnU4RjLnSSZsUCUhYHMAQBAEAQBAEAQBAEAQBAEAQBAEA877L2Jbkcmdn1UKHu7g2XalbMEFhx3x8g1h20VWsWoorMQoZgSQNTJuO4zW7SXxKXInq7C9hT+Uwu68viX2dC7eBvtNrCvaeyawCaqqf8A8PbCakLUujHVlGiggKJCLo7+SvJ/Mu2viZ1uFl4VGHs3auIe78rFyb7rtpZeysheEcbKy92qldnWBha6AcWtUXQHdA2OP1i/0P8ADybL0Eesyop8cn1ETMhFudGfgJbXZVYoeu1HrsQ9jo6lXU6eBlJB8hgFb2nzZ4lqsCLA5qepbmusvsTeW1Fcd1Nej2Ui60UtclnCFtoXdFjhgGyOa7DqFXeNbZU72i6yxza9ll3dLtaUKLaGyAt246snErqfd3q0YAWuAfdPaPnH2wC1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA1NzL3abG2T3qn+bsPt1+RX4CJNx3Ga3aT+JS5E9XYXsKfylz4//Iv/AKvWkIujjukfET/1etAIDX+cbPof/vjybL0Eesyop8cn1ETEhFuVfnDznFHCra2t72CLdT+lUQVbXwalhqugKkje0I0lblKjOth6lOnN0pSjoqK1420306OS3ufOfOavFrV7TzVk8u89WZe7so7rFdVyLSDoSNQd7rB01B+CflSvl3KdGpOnwio8yUo3T15rtdex2uipdSd7X1aCT5L8ps6+0Ic/LUBWfqud2O4Nd1VZtCfCddQFDNod3Q7Fuex2UcpYyGHlip09Ge5XWlJpZqurXd+VNaNR6g5SdnKx6g2VtHjVpbulN8a7rdo6yPJqOrUHQajQ9Ws/TSVkk3eySvz+0uDNp7R84+2ZBa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAaj5l202Psj/DsP8A2Vk3HcZrdpL4lLkT1dhewp/Kad5B+5BVlf8AlBkNtixBXXh3nLz0sxqkXdKoOMNH1AYXAtYxLbzHQEwi6Lx7nfat5o2hh3ZFmYuytqZGzsfMtbiXX49VdFqC63r4t2ObmxbLCSztSS3fb0Av4/WL/Q/w8my9BHrMqKfHJ9REwzdR6tfIO0+QeWQi3KLncvNn5NbY+TZ3NxjfWtWRdXj3XHFyFxsjgqlxsdaclqqGZRus9tSjfFyb0XFYaniqUqNW+ZNWlmycXa6eiUdK1ch5cVJWZU8fkrybbe3crHfcVGbcz97dWxKbayd2w9T15OPYP+TIobstrLaS9wmR27unL9Wb/qfB4eP+3Y6cbY/JxRbY16ULjtfvPdmmkBcXi8e4FrgRVXwMj84d0Fce5xqlZefWluKyVRnGdOE4yi001Vne61cq0Gd4gjZmy+cbAvt4NObi23EleFXfW1m8ptDDcDb2oOPeCNNdaLh21WBd6SskuZW7iQWSntHzj7ZkFrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIBqLmb/U+yf8Nw/wDZWTcdxmt2kviUuRPV2F7Cn8pFcruZWrLyLMlc/a+G9yIl6YW0LaqbVQBVHCcWJQQuo38YUudWJYsSxhF0WrkfyPxtn41eJiVCmioEKgLMSWJZ3d2JeyyxyzvY5ZnZiSSTAOR+sX+h/h5Nl6CPWZUU+OT6iJmQi3Kvn82+NYhQ8VQWvYlbCDrkZtefaCDqro+RWu9VYr1vVvVMro7qwEYOZTAFFeOK3FVVYqQF9/dQLhIOq0WKxVdn4u6zqxUoWGjHeAGTdzS4ba6i7dbfLpx7N13Y5JDvqSzMndmRuktod9Swc1UtWBIYXN/jV2i5VcWC17tS7EcR7doXMdD4DZtPLIHYA6DsrWAWWntHzj7YBa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAa45iGPQmyf8ADsT/AGUk7HcYq9pP4lLkT1dhewp/JEs20eVNFLbll6I3xSesf+bTXd/+rSQS6M7Hz1fUo6vp27rBtNQCOwntBB+Yg+GAU679Z2/RD9tEmy9BHrMqKfHJ9REtIRbkDys2ldWKuFwxvvuuXIB06tAgJG8T19gdtQNFOpE+VW+ZKza816UrtaORcv8Auxhmn7uc3ODEDIbQE6a1Ug6a9Wo4fUdO0eAz85V91WVI1JxjWaUZSSWYr2T0XvpvbXzcuk+Db5zJ2XzgZ9jad06BQXYmmk96ungFYJ1JA0BHb2qASLPI2W8r5RxUMPGslpvNuC+6mrr3v2HtO5uzZm0VurW1Nd1xqNRoe0jQjyEeAkeUzvy1K+vl959TMp7R84+2ZBa4AgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAa45iP1Lsn/D8T/ZSTsdxir2k/iUuRPV2F7Gn8kTI5KGng2rayLfv2jJLbocMWbRjv6jd3CCmuq/XIJdEtyV2DVRURS5dLDxAxZW11UDqKgDTQQCEt/Wdv0Q/bRJsvQR6zKinxyfURLSEW5G7Z5O15G4LASUOqkHTQn4fAQdB1H4PnnmUc5NJ2bWh83t/IGvV5uMCwh+7LTxUNwJapQyM4Tf1akAA2MFA6tSQAJzOpuCwdScpyq1byk5P7uuTu39zlbufNwR2YHN3giyvh5lwdrLq0AesMz0m1LlA4Wuimm5WJAHesNTqNfth9w+Gw9WNWnWqxlFp6HFX9j8zU+UZiNnogA0AAA7AOoAfAB8E6Ra2g+h2U9o+cfbALXAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQDXPMQv8AMmyf8OxP9lJOx3GKvaT+JS5E9XYXsKfyRLXncnabSGsprdh1Asqk6fBqe0eQyCXRmpRoNAAABoANAAPAAB2AfAIBSrv1nb9EP20SbL0Eesyop8cn1ESshFucgwDXF3MVh/mzWOE6K6s60454xdL6me9WqK2vw8m4AuDozBuvQg4uLEhsHmqpxrq7UttPDe6wK4rdi1vdA67Sgt3FXIYBAwBZVc6sXLDNi7TJg+6e0fOPtgFrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIBrLmVygmwtlu2u6mzMZjp26LjqTp5dBJ2O4xV7SfxKXInq7C9jT+SJZMbIyLd9ksqRVsdFDUs50Q6alhcgJPb1KNJBLoyNlZVha1LCjGspoyIUBDoG0Kl36wdevXr+CAVy39Z2/RD9tEmy9BHrMqKfHJ9REtIRbkFyy261FJNbVi99FpFu9uM2o3td3sAUnrJVd7d1I1lZlOWKjhpywai6yXmKo7Rb5btadCu/bq0XJ2CjQlWgsQ2qd3nuOu3Jb87GnbOfDPBIK44IJBBqfqIOhH9L4DPz3U/xCyxTlKEo0U4txazJPTF2eqXOjrUNyGAnFSTqWkk1q1PSuTmPhuffOHXu45A69OG/Xp4NeL1TFP/EXKrmoyjRldrQoyWi/O5NLuZme4/BRi2nUTSfNze49BkT9KU3eKfOk+9JnGZKz7/iz6p7R84+2fQ8FrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIBqfms/ZzB/wir+EEnY7jFXtJ/EpciersL2FP5Ilo2RtRaw6uLQeLY3VTcwKsdVIZUKnUfAZBLoydi3b9mQ4DBWNYBZHTXdr0OgdVPUerXTSAQVv6zt+iH7aJNl6CPWZUU+OT6iO7J5Q46WpQ99CX2AGul7a1usB3tClRYOwO4/Wqn9FvgMhFudfKTk/wB0VFAQlg667TWLOG2oOoVtAdR1dvh17QJBxtGrWozp0p71OUbRmldxfPZ6GSsNVhSqRlUjnxT0xva/56TWL+57OupzDqdSSaO0+E9d041P/DN1JOU8U22223SV23pbenlbZ0eG7VRioqhZJWX/ABORav4eYwNj8ytGSpajaVWRWG3Geha7QDoCV3kuZQ26wbQ+Ag6aETMP8M0pJvEO11e0Em1cT3atxaVHS01ffL2bVuZfE3gjhgGHWD1gjrB+YjqM7fCOaktdklfnsrHL29Pf/N3PrHsBbQEEqwBHwHqOh+A6EHQ+Ag+ET2YLbAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQDW3MbSG2HspW0IOzcUEEagg0KCCNOsEdWknY7jFXtJ/EpciersL2FP5Iln/kljfJJ/6vvkEuiTrxwoAGgAAAHX1ADQD/oIBS7v1nb9EP20SbL0Eesyop8cn1EQPKTkFZfktaL60qsXZ62VnHL3a7PzL8xGquNypWXe1V1aiw1hCyneZSkItys7B5iTWlaZGY2Tw2Q6slq7+hwOKXXullL5AxLRadNH7ru3hYXvbIAk9j80jrRfRfmWWrkYNuFZaivXe/GQI19lj3XB7KRvJjEKhqrdgxuPfTFzJzkc2+W9rZDZlC32U1Y1nBxLa6eBVq2qVd2syZBsewrabXWuo117jcM2WZMERyc5msjHJFeRTSlNuMcbcot0erHGz2FdqLlIq0lsW5TSgH5y6y3e0d67ALbzT8grNn08K26vIsc4rWXpQ1DW2U4GHh2W2hr8hne2zFa4EvqqWLWTYazdaBt2AIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgGpeazLZOT2zGQ7rdH4Kg6Akb61ISNdRqAxI1BGunUeyTsdxir2k/iUuRPV2F7Gn8kSaz9oLU9iW5WXWUUMpYUaWqdNeFpQd4gndK9TeHTSQS6M7ZORYLalZ7ittFlhS8V79bI1IA/NooHVYdQdewdnXAI239Z2/RD9tEmy9BHrMqKfHJ9REtIRbkDy25QvjY72U1Lfd3oqoaxa+KxZQwDN4VUl9B1tu7o1LAGBjq1ajRnUoQ32pFXjC9s7n08mi7LDA0KNevCnXnvUJO0p2vm82j2uyNCt7rfIHbg0gjtBusBHkI4fUR8E5S93tZNp0YprQ06krp8zWbrXKdXW4CjJJqvJ8zVOLTXI076U0fD+6+vALHBpIAJIF7gkDwA8PQE9g16plbvqjaToRtfpJP4xPUtwFK2itK/ZpfCR6cInYoyzknzpfA4u1ZtczPqntHzj7Z6MFrgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIAgCAIBqLmyrJ5O7M0BYjAwG0UEkhBS7aAdZIVSdB1nSTsdxir2k/iUuRPV2F7Cn8kSX2wKb7Ge26/vQBjhMfIXgt1E2f0Z3nLAaE6DTq08Igl0SOysk2XUtqzmvHuWyw02UqXd8fTQWAdbbjHQa9ng7IBgW/rO36Iftok2XoI9ZlRT45PqIlpCLcr/Lbk8+RSRTwhkJ10tcHNSsSu9vishiCo7O+G9ukhgCDDxca0qUo0GozatFy0xXPe2nVexMwkqMasHXTdNO8lH7z03Vvzt+R56v9yptBizNlYhZiWZi13WzHUk/me0k+TrM45U3CYupKU51abcm23mvS27t6GuX2HZ4bu8DCKhGlUUYpRSutCStznXZ7kfPIKnJxACNCQbiQD1E6cIa6fBqNfhEzDcFirq9aFrq/mvUZlu+wdnalUbs9draj1VO2RVklzJLuVjhkndt87b/AJn1T2j5x9s9GC1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA15zCU67E2T/AIfif7KSdjuM1u0n8SkyI/8A0/C9hT+RIvnco+EyCXY7lEAoeQP5zt+iH7aJNl6CPWZUU+OT6iMTl1se6+hVoFTWplYOQFuseqtlxc2jIdTYlV7KSlTBdKn7/dB3QSwhFuVLanIzarva1WTVQty2WNUl9xCXhVSmtLBjowqtW3I414VbEbHwXSpzxQgHftPkLk2U4nGrxM96Eyktxs252x3N+nCs4zYd72WY1anGD2Y2+9N+Q7MXOlgEFmc3u1Uxq6hkC44VX5ixcvKS/ItWiutXZChCtUwsNaWZF4uJUO6b7ugHftvkDta6m6jj1rVk0W1Mh2hms+Prj59aqmQMZbr+LbkY1j2saHpWndUWiuvUDbuN/V8H6PVvFtOzq3j1t856zALbAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQCgcwP6k2T/h+J/spJ2O4zW7SfxKPIfq/C9hT+VF/kEvBANe5P6zu+it9tEmy9BHrMqKfHJ9REpIRbiAIAgCAfdPaPnH2wC1wBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEAQBAEA//2Q==" + } + }, + { + "id": "Mo17A3If3LtSFuUG", + "content": { + "type": "Text", + "format": "html", + "text": [ + "5. Place a Dataflow tile in your workspace under Activities. Then, drag a Sensor block into the Dataflow. On the “select a sensor type” dropdown menu, choose “EMG.”
" + ] + } + } ], - {"id": "hRL2PzfJH5u7ohJD", "content": {"type": "Text", "format": "html", "text": ["1. Connect the Arduino board to your computer using the blue USB cable.
"]}}, { - "id": "AIaXlh5Jt6mO1ko4", + "id": "BfEcsBHvG1mVwV4H", "content": { "type": "Text", "format": "html", - "text": ["2. Decide who is going to be the study participant (you can take turns). Place two electrode stickers on the participant’s forearm close to each other and another one on the participant’s elbow (this is the reference electrode)
"] + "text": [ + "6. Click on the lightning bolt in the top left corner of the Dataflow tile. Select the option that appears as a compatible device, then click “Connect.” Then, on the “select a sensor” dropdown menu of the Sensor block, choose “EMG.”
" + ] } }, - {"id": "2hcaL4NZmS-uOSsY", "title": "Place electrodes", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/9.jpg", "filename": "curriculum/neural-engineering/images/9.jpg"}}, - {"id": "Xf1VSQp7lP4Hckuo", "content": {"type": "Text", "format": "html", "text": ["3. Connect the orange muscle electrode cable (the one with the three alligators) to the Muscle SpikerShield orange connector:
"]}}, - {"id": "hGLe_2Xa-uVW069o", "title": "Connect Electrodes to shield", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/10.jpg", "filename": "curriculum/neural-engineering/images/10.jpg"}}, - {"id": "ubWseUhinUcs1rwC", "content": {"type": "Text", "format": "html", "text": ["4. Connect the two red alligators to the electrodes on your arm. The black cable should be connected to the reference electrode:
"]}}, - {"id": "2r6t0lkN0WkyPi2i", "title": "Connect Electrodes to arm", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/11.jpg", "filename": "curriculum/neural-engineering/images/11.jpg"}}, + [ + { + "id": "lT_qM8V07tMB7C8y", + "title": "Click Lighting Bolt", + "content": { + "type": "Image", + "url": 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" + } + }, + { + "id": "Kubah9H3VRFyEHvZ", + "title": "Click Compatible Device and Connect", + "content": { + "type": "Image", + "url": 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" 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" + } + }, + { + "id": "UTH0xYHSmUG6IFIT", + "title": "Text 1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "7. Click the Graph tile and drag into your workspace next to your dataflow tile
" + ] + } + } + ], + [ + { + "id": "9Cc3LhvODCJn_kZq", + "title": "Image 2", + "content": { + "type": "Image", + "url": 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AABBBBAAAEEEAgpQKA5JA0XEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBNwIEGh2o0QbBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgZACBJpD0nABAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAwI0AgWY3SrRBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQCClAoDkkDRcQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEE3AgQaHajRBsEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBkAIEmkPScAEBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEDAjQCBZjdKtEEAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAIKUCgOSQNFxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQTcCBBodqNEGwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIGQAgSaQ9JwAQEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQMCNAIFmN0q08YRASUmJbN++3RNzYRIIIIAAAggggAACCCCAAAIIIIAAAgggcFCAQPNBC448KLB8+XK58847pVevXlJYWCgtWrSQNm3ayK9+9SuZO3euB2fMlBBAAAEEEEAAAQQQQAABBBBAAAEEEEg/gez0e2SeOFkEFi9eLH369JGNGzf6TVnPx48fb75ef/11ufjii/2uc4IAAggggAACCCCAAAIIIIAAAggggAAC8RVgR3N8vRnNpUBpaalfkPnhhx+WiRMnyvTp0+XJJ5+0e7nttttkw4YN9jkHCCCAAAIIIIAAAggggAACCCCAAAIIIBB/AXY0x9+cEV0IfPrpp/ZO5ueff16uu+46+67OnTtL8+bNTV1RUZG8/fbbcvvtt9vXOUAAAQQQQAABBBBAAAEEEEAAAQQQQACB+Aqwozm+3ozmUkB3Lltl0KBB1qH96UyXMWvWLLueAwQQQAABBBBAAAEEEEAAAQQQQAABBBCIvwCB5vibM6ILgdWrV5tWXbt2ldzc3Ep3ZGRk2HVlZWX2MQcIIIAAAggggAACCCCAAAIIIIAAAgggEH8BAs3xN2dEFwJPPfWUzJw5U8aMGRO0tabWsEq3bt2sQz4RQAABBBBAAAEEEEAAAQQQQAABBBBAIAEC5GhOADpDRhZo1qyZ6Few8u2338rgwYPtSxdddJF9zAECCCCAAAIIIIAAAggggAACCCCAAAIIxF+AQHP8zRmxmgLFxcUyfPhweeaZZ+weXn31VWndurV9Hniwa9cu0fvcFG2rpVWrVrJixQo3t9DG4wKlpaVmhqynxxfK5fRYT5dQSdKM9UyShXIxTdbSBVISNTn//PPNbPlvZxItWpip8uczDE4SXmI9k3DRwkyZ9QyDk4SXWM8kXLQwU2Y9w+BEuESgOQIQlxMvUFFRIe+++67cc889snHjRjOhJk2ayOjRo+WMM86IOEErgBypIbmeIwlxHQEEEEAAAQQQQAABBBBAAAEEEEAAgeACBJqDu1DrEYF169bJDTfcIJ9//rk9o7vvvluGDRsmeXl5dl24g8aNG4e7bF/Lyckxx/oiwjZt2tj1HCSvgLUbi/VM3jV0zpz1dGok/zHrmfxraD0Ba2lJpMbn448/bh7E2tmcGk+Vvk/Bn8/UWnvWk/VMLYHUehr+fLKeySswPapTJ9AcVU46i6bAwoUL5ZRTTpGioiLTbf/+/U3ajMMOO8z1MHXq1HHdNjubPw6usWiIAAIIIIAAAggggAACCCCAAAIIIICAQ4DImgODQ+8IbN++XQYOHGgHmV955RUZNGiQdybITBBAAAEEEEAAAQQQQAABBBBAAAEEEEDAFiDQbFNw4CWBzz77TJYtW2amNGbMGOnbt6+XpsdcEEAAAQQQQAABBBBAAAEEEEAAAQQQQMAhQKDZgcGhdwSmTp1qJtOuXTvJzc2VyZMnh5xcs2bN5Igjjgh5nQsIIIAAAggggAACCCCAAAIIIIAAAgggEFsBAs2x9aX3agpMmjTJ3Km7miPtZv71r38tL730UjVH4jYEEEAAAQQQQAABBBBAAAEEEEAAAQQQqKkAgeaaCsb4/rFjx8rFl1xS41GWLF4srVq1qnE/8ehAX/43b94810NlZma6bktDBBBAAAEEEEAAAQQQQAABBBBAAAEEEIi+AIHm6JtGtcey8vKo9FdWVhaVfuLRSV5enpSUlMRjKMZAAAEEEEAAAQQQQAABBBBAAAEEEEAAgSgIEGiOAmIsu+hx3HHy2quv1niIwsLCGvdBBwgggAACCCCAAAIIIIAAAggggAACCCCAwP+zdyfwdk334sBXIipCTDVPEdMz05pCqy3e60PVK4rS4SFmWo2+qqF0UI9SVUVRpVQVranFq6FqaOlAzDXFFE9aEVMESUn4399+9vmfe3PPzbk3555z9j7f9fnce/a81/quM+z922uv3ZuAQHNvKm00bfnll0+77757G+VIVggQIECAAAECBAgQIECAAAECBAgQINBdQOe23T1KN/bdk05K6663Xvrzn/9curIpEAECBAgQIECAAAECBAgQIECAAAEC7SGgRXN71EO/czFz5sx09913p4ceeii99dZbva4/s6tf5gsuuCA9/fTT2d+YMWN6Xc5EAgQIECBAgAABAgQIECBAgAABAgQIzI2AQPPc6LVo3bfffjvtueee6Yorr6w7Bx/96EfrXtaCBAgQIECAAAECBAgQIECAAAECBAgQ6I+ArjP6o9Umy15+xRU1g8wjR47slssYP/+889Kyyy7bbboRAgQIECBAgAABAgQIECBAgAABAgQINEpAoLlRkk3czi9+8Ytsbx/5yEfSA/ffn56dODHlAea/dXWl8eorr6Qbb7ghLbHEEmnatGlp5ZVXbmLu7IoAAQIECBAgQIAAAQIECBAgQIAAgU4TEGguYI0//PDDWa4PPPDAtPrqq6cll1wyfWK77bJp0W/z8OHDUwShr7nmmmzaLrvummZ19dcsESBAgAABAgQIECBAgAABAgQIECBAYDAEBJoHQ3WQtzlp0qRsD+utu25lT6NHj86GJzzxRGXaBuuvn9btWmbKlCkpD05XZhogQIAAAQIECBAgQIAAAQIECBAgQIBAgwQEmhsE2czNRJcYkaa9/npltyuuuGI2fH9XVxrVacyYMdnoXXfdVT3ZMAECBAgQIECAAAECBAgQIECAAAECBBomINDcMMrmbWiDDTbIdnbaaadVusRYZ511smnRXcbMmTMrmbn7vQDz85MnV6YZIECAAAECBAgQIECAAAECBAgQIECAQCMFBJobqdmkbe25557Zni655JK0UleXGbfddlvaeOONs24y4uF///mf/5n1z3xAVx/O9953X7bsv/zLvzQpd3ZDgAABAgQIECBAgAABAgQIECBAgECnCQg0F7DG/2OHHVIebI7+l5955pmsFAd1BZYjXXHllSkeAHjBBRdk49F/87bbbJMN+0eAAAECBAgQIECAAAECBAgQIECAAIFGCwxr9AZtb/AFhg0bls760Y/Srrvsku66++605pprZjvdbbfd0p//8pd04YUXVjIR8y7++c/TiBEjKtMMECBAgAABAgQIECBAgAABAgQIECBAoJECAs2N1GzitoYMGZK22mqr7C/fbQSTzzn77PSd445LTzzxRIqHBkZr5nnmmSdfxCsBAgQIECBAgAABAgQIECBAgAABAgQaLiDQ3HDS1m8wAszxJxEgQIAAAQIECBAgQIAAAQIECBAgQKAZAgLNzVAepH289dZb6bHHHkuvvPJKiuG+0hZbbJHmm2++vhYxjwABAgQIECBAgAABAgQIECBAgAABAgMSEGgeEFvrV7r44ovTl8eNS9OmTasrM493BaRXXHHFupa1EAECBAgQIECAAAECBAgQIECAAAECBPojINDcH602WfbqX/86jd1nnzbJjWwQIECAAAECBAgQIECAAAECBAgQINDpAgLNBXwH/OqXv6zk+sQTT0xjNt00a60cDwislZZeeulas0wnQIAAAQIECBAgQIAAAQIECBAgQIDAXAkINM8VX2tWvv0Pf8h2/P1TTkkHHXRQazJhrwQIECBAgAABAgQIECBAgAABAgQIEHhPYCiJ4gksuOCCWabXW2+94mVejgkQIECAAAECBAgQIECAAAECBAgQKJ2AQHMBq3SzzTbLcv3www8XMPeyTIAAAQIECBAgQIAAAQIECBAgQIBA2QQEmgtYo3vsvnuW66O//vX097//vYAlkGUCBAgQIECAAAECBAgQIECAAAECBMokoI/mAtbm5ptvnr5y2GHplO9/P206Zkw6+qij0tprr50WXXTRNM888/RaotVWWy0NG6a6e8UxkQABAgQIECBAgAABAgQIECBAgACBuRIQeZwrvtasvN9++6XLr7gi2/mUKVPSl8eNm2NGHn/ssbTiiivOcTkLECBAgAABAgQIECBAgAABAgQIECBAoL8Cus7or5jlCRAgQIAAAQIECBAgQIAAAQIECBAgQKCbgBbN3TiKMXLiiSemr33ta/3K7LLLLtuv5S1MgAABAgQIECBAgAABAgQIECBAgACBegUEmuuVaqPlll9++RR/EgECBAgQIECAAAECBAgQIECAAAECBNpBQNcZ7VAL8kCAAAECBAgQIECAAAECBAgQIECAAIECCwg0F7Dyjj322DR8/vn79bfKqqumHXfaKf3sZz9LM2fOLGCpZZkAAQIECBAgQIAAAQIECBAgQIAAgXYV0HVGu9ZMH/l65513+pjb+6xJkyal+Pvtb3+bbrn11nTuj3+chg1T/b1rmUqAAAECBAgQIECAAAECBAgQIECAQH8ERBr7o9Umyx588MHp3vvuSzfffHOWo/333z996EMfSostumj6xz/+kR544IF05VVXZYHlWCCCyjNmzEi33XZbuvyKK9Ill1yS5ptvvnT2WWe1SYlkgwABAgQIECBAgAABAgQIECBAgACBIgsINBew9p588sksyDxy5Mj0h9tvT2usscZspTjq6KPT5z73uWy566+/Pl188cVp3333TVtuuWU6+JBD0gUXXJBO/+EP07zzzjvbuu06Ibr80Aq7XWtHvggQIECAAAECBAgQIECAAAECBDpZQB/NBaz9G2+8Mcv10V3B5N6CzDFz0UUWSRd2BZMjXXHllemtt97KhseOHZtGjx6dDT/66KPZazv/mzx5cvra176WRo0alRZaaKHsNcoQrbIlAgQIECBAgAABAgQIECBAgAABAgTaQ0CguT3qoV+5+P3vf58tv/pqq/W53uKLL57WXXfdbJnqoPKYMWOyaQ8++GCf67d6ZvQp/eEPfzidfvrpacqUKVl24jWCzBFsPuGEE1qdRfsnQIAAAQIECBAgQIAAAQIECBAgQKBLQKC5wG+D8ePHzzH3L7/8crbM213dTuTp7fdaNw9r824z9t5770o/04d0dfdx0003pSu7Wmdvt912WVGOO+64dP755+fF8kqAAAECBAgQIECAAAECBAgQIECAQIsEBJpbBD83u40H/0X68bnnpnvuvbfmpqIf5mgVHGnN9/pxjvF4IGCkFVdYIXttx3933nln+sMf/pBl7aCDDkonnXRS9sDDbbbZJv3sZz9La665ZjYvWjW/++677VgEeSJAgAABAgQIECBAgAABAgQIECDQMQICzQWs6v322y/FgwCjG4nNN988HX744enCCy9Mf/zjH9P4e+5Jv7nmmvTZz342HXDggVnp9thjjzRixIh02S9/mVZZddVs2nLLLZc22mijti39NV1lyFOUrzpFWQ477LBsUgTO62nZXb2+YQIECBAgQIAAAQIECBAgQIAAAQIEGiswrLGbs7VmCKyyyirZg/522nnnbHc/7OrDuFaKgPL3Tj45m33/ffdVFvv+97+fhg1r3+q/+eabs7xusskmackll6zkOx+IAHue/vKXv7R10DzPp1cCBAgQIECAAAECBAgQIECAAAECZRXQormgNRv9FD/15JNpzz33rFmCw7/61RTB5cUWWyxbZomugO3uu++ebrzhhvQfO+xQc71Wz4iuMB566KEsGxtuuGGv2Rk9enRl+gsvvFAZNkCAAAECBAgQIECAAAECBAgQIECAQPMF2rdJa/MtCrfHZZddNp191lnprB/9KE2ePDk9++yzKR7wN2rFFdP73//+2coz7stfnm1aO0544403KtlafPHFK8M9B5ZYYoms+5DoQqRWmjVrVq1Zs01/5513ZptmAgECBAgQIECAAAECBAgQIECAAAECcxYQaJ6zUdsvMWTIkLT00ktnf22f2Toy+Nprr1WWWnTRRSvDPQcWWWSRLND86quv9pxVGX/77bfTSy+9VBnva2D69OnZ7A984ANpn3326WtR8woikF88GDrUzRsFqbI+s6k+++Qp3Ez1Wbgqq5lhdVmTppAz8uMhx0KFrL7ZMu3zORtJoSeoz0JX32yZV5+zkRR6gvosdPXNlvmOqs91t52t/HMzQaB5bvSasO5f//rXdPL3vpft6eijj04brL9+Ovfcc9ONN93Ur71Hy+feWjn3ayNNWni++ear7KmvFsl5gDkCzn2leeaZp6/Z5hEgQIAAAQIECBAgQIAAAQIECBAgMJcCAs1zCTjYq//9H/9I11xzTbabfcaOTakr0PzAgw9WptW7/1O6gtVFCTRXt2Kubt1cXdboxznvMiO60KiVhg8fXndL7wUWWCDbzL333ptuvfXWWps0vUACEydOzHI7atSoAuVaVmsJqM9aMsWcrj6LWW+95Vpd9qZS3Gl5S+af/OQnxS2EnFcEfD4rFKUYUJ+lqMZKIdRnhaIUA+qzFNVYKUQn1edWp11RKXcjBgSaG6E4iNtYrqsf5p132inbw1Jd3WNEilbN+bRsQh3/FlxwwTqWao9FopuDvP/lp59+utdMTZ06tTJ9ya6HHEoECBAgQIAAAQIECBAgQIAAAQIECLROQKC5dfZ17XnjjTdOF198cbdlx3a1bI6/MqcNN9wwXX/99emWW27ptZi33357Zfrmm29eGTZAgAABAgQIECBAgAABAgQIECBAgEDzBTwhq/nm9liHwK677potNWnSpHT55ZfPtsYvfvGLbFq0fF6/q4W3RIAAAQIECBAgQIAAAQIECBAgQIBA6wQEmltn3+89z5w5Mz322GPpf/7nf2ZbN/qP+epXv5o+8tGPpnXXWy/ts+++6fzzz0+xThHTJz7xiUq2Dz744HT//fdn41GeE044If3mN7/Jxg844IAUXW1IBAgQIECAAAECBAgQIECAAAECBAi0TkDXGa2z79eer7322vTpXXaprDNj+vTK8Ph77knbbLNNmjZtWmXahAkT0s9//vPsoXbnnXdemnfeeSvzijAwcuTIdN1116UIOEe5Nttss6zf5hkzZlTKudpqq6VDDz20CMWRRwIECBAgQIAAAQIECBAgQIAAAQKlFtAUtADVe9FFF3ULMvfM8pFHHlkJvi633HLp3//93yuL/PJXv0rf/e53K+NFGthyyy3TL3/5yxRB50hTpkyplHOrrbZKv/vd79KIESOKVCR5JUCAAAECBAgQIECAAAECBAgQIFBKAS2a27xaowXvUUcfXcnll7ta8O7yXv/FMTG60sgfjLf11lunX3UFZiP4Or2rxfOOO+2UtWg+7Yc/zLrVmG+++SrbKcrA9ttvn55//vmsnHfddVcaPnx4WnvttdNaa61VlCLIJwECBAgQIECAAAECBAgQIECAAIHSCwg0t3kVX3XVVVlL3shmtGze5dOf7pbjyy67rDL+zW9+s9LCd/75509nnnFGWnuddbJWwLfeemu3ls6VlQowMGTIkLTGGmtkfwXIriwSIECAAAECBAgQIECAAAECBAgQ6DgBXWe0eZU/+OCDWQ4/sMEGswWZY8YtXQHkSEsssUTaaMMNs+H83yqrrJKiH+NITz31VD7ZKwECBAgQIECAAAECBAgQIECAAAECBBoqINDcUM7Gb+zJJ5/MNrre+uvPtvHoHuNPf/pTNn2HHXZI0fK3Z1qnq5uJSBMnTuw5yzgBAgQIECBAgAABAgQIECBAgAABAgQaIiDQ3BDGwdvI62+8kW18ya4Wyz3T+PHjK5M232yzynD1wMxZs7LRt95+u3qyYQIECBAgQIAAAQIECBAgQIAAAQIECDRMQKC5YZSDs6GVV1452/BzkybNtoPbbr+9Mm2jjTaqDFcP3HPPPdnoql3daEgECBAgQIAAAQIECBAgQIAAAQIECBAYDAGB5sFQbeA2V1111Wxr1157bXr55Ze7bfnSSy/NxqN/5tVXX73bvBiJ/p0nvRegHj169GzzTSBAgAABAgQIECBAgAABAgQIECBAgEAjBASaG6E4iNvY8VOfyrY+bdq0tMuuu6aHH344vfzKK+mYY45JEyZMyOZ9+tOfnq1/5pdeeil9ascds/kjR45Mm44ZM4i5tGkCBAgQIECAAAECBAgQIECAAAECBDpZQKC5zWt/xRVXzILKkc077rgjfXDDDdOyyy6bTv7e9yo532/ffSvD1113Xdq5K/C83PLLV1ozf/tb30qLLbpoZRkDBAgQIECAAAECBAgQIECAAAECBAgQaKSAQHMjNQdpW0cecUQ66aSTet36ZZddltZcc83KvEsuuSRFsDlPe+yxRxo7dmw+6pUAAQIECBAgQIAAAQIECBAgQIAAAQINFxjW8C3aYMMFhg4dmr70xS+mXXfZJd17773psccfT9HSedNNNknLLbfcbPuLrjI26Zq35557pl26WjdLBAgQIECAAAECBAgQIECAAAECBAgQGEwBgebB1G3wtpdeeum07bbbZn+1Nn3OOeekBRZYoNZs0wkQIECAAAECBAgQIECAAAECBAgQINBwAV1nNJy0tRsUZG6tv70TIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrHVlJkCAAAECBAgQIECAAAECBAgQIECAQAMFBJobiGlTBAgQIECAAAECBAgQIECAAAECBAgQ6EQBgeZOrPWClvnNN99MU6dOLWjuZZsAAQIECBAgQIAAAQIECBAgQIBAeQUEmstbt6Uo2TPPPJPGjRuXNt9887T44ounZZZZJo0aNSrttNNO6W9/+1spyqgQBAgQIECAAAECBAgQIECAAAECBIouMKzoBZD/8go88cQTaeutt05TpkzpVsgYv/7667O/Cy+8MO2yyy7d5hshQIAAAQIECBAgQIAAAQIECBAgQKC5Alo0N9fb3uoUmD59ercg87HHHptuvfXWdPfdd6fjjz++spVDDjkkvfDCC5VxAwQIECBAgAABAgQIECBAgAABAgQINF9Ai+bmm9tjHQI33HBDpSXz6aefnsaOHVtZa6211kpLL710Nm3atGnp0ksvTV/60pcq8w0QIECAAAECBAgQIECAAAECBAgQINBcAS2am+ttb3UKRMvlPO2+++75YOW1uruMBx54oDLdAAECBAgQIECAAAECBAgQIECAAAECzRcQaG6+uT3WITBp0qRsqXXWWSeNGDFitjWGDBlSmTZr1qzKsAECBAgQIECAAAECBAgQIECAAAECBJovINDcfHN7rEPgxBNPTPfff3+6+uqre106utbI0/rrr58PeiVAgAABAgQIECBAgAABAgQIECBAoAUC+mhuAbpdzllgqaWWSvHXW/rrX/+a9tprr8qsT3/605VhAwQIECBAgAABAgQIECBAgAABAgQINF9AoLn55vY4QIE33ngjnXzyyemkk06qbOH8889Pyy+/fGW858CMGTPS22+/3XNyr+NvvfVWr9NNJECAAAECBAgQIECAAAECBAgQIECgbwGB5r59zJ1LgVtuuSW9+OKLdW9lhRVWSGPGjOm2/Lvvvpsuv/zy9F//9V9pypQp2bwlllgiXXDBBWnLLbfstmxvI6+99lpvk2eblgekl1tuuTRx4sTZ5ptQPIHp06dnmVafxau73nKsPntTKe409VncuuuZc3XZU6TY4zvssENWAL+dxa7HPPc+n7lEOV7VZznqMS+F+swlyvGqPstRj3kp1Gcu0f9Xgeb+m1mjHwLHHntsGj9+fN1r7Lzzzt0Czc8//3zab7/90u9+97vKNr7yla+kww8/PI0cObIyra+BepcbNszHoS9H8wgQIECAAAECBAgQIECAAAECBAjUEhBZqyVjekMEVlpppVRvi+LYYbQmztPjjz+etthiizRt2rRs0nbbbZd1m7Hyyivni8zxdfjw4Sn+6knzzTdfttikSZPSqFGj6lnFMm0ukLfGUp9tXlF1Zk991glVkMXUZ0Eqqo5sqss6kAq0yHHHHZflNm/ZXKCsy2ovAj6fvaAUeJL6LHDl9ZJ19dkLSoEnqc8CV14vWe+s+ry7F4GBTxJoHridNesQuOiii+pYavZFpk6dmnbcccdKkPm8885Lu+++++wLmkKAAAECBAgQIECAAAECBAgQIECAQMsFBJpbXgUy0JvATTfdlJ5++uls1tVXX50+/vGP97aYaQQIECBAgAABAgQIECBAgAABAgQItIGAQHMbVIIszC5w5513ZhNHjx6dRowYkf74xz/OvtB7U5Zaaqm02mqr1ZxvBgECBAgQIECAAAECBAgQIECAAAECgysg0Dy4vrY+QIHbbrstWzNaNc+pNfPnP//5dM455wxwT1YjQIAAAQIECBAgQIAAAQIECBAgQGBuBYbO7QasT6DRAvHwv0ceeaTuzQ4d6m1cN5YFCRAgQIAAAQIECBAgQIAAAQIECAyCgBbNg4Bqk3MnMHLkyPTmm2/O3UasTYAAAQIECBAgQIAAAQIECBAgQIBA0wQ0BW0atR0RIECAAAECBAgQIECAAAECBAgQIECgnAICzeWsV6UiQIAAAQIECBAgQIAAAQIECBAgQIBA0wQEmptGbUcECBAgQIAAAQIECBAgQIAAAQIECBAop4BAcznrVakIECBAgAABAgQIECBAgAABAgQIECDQNAGB5qZR2xEBAgQIECBAgAABAgQIECBAgAABAgTKKSDQXM56VSoCBAgQIECAAAECBAgQIECAAAECBAg0TUCguWnUdkSAAAECBAgQIECAAAECBAgQIECAAIFyCgg0l7NelYoAAQIECBAgQIAAAQIECBAgQIAAAQJNExBobhq1HREgQIAAAQIECBAgQIAAAQIECBAgQKCcAgLN5axXpSJAgAABAgQIECBAgAABAgQIECBAgEDTBASam0ZtRwQIECBAgAABAgQIECBAgAABAgQIECingEBzOetVqQgQIECAAAECBAgQIECAAAECBAgQINA0AYHmplHbEQECBAgQIECAAAECBAgQIECAAAECBMopINBcznpVKgIECBAgQIAAAQIECBAgQIAAAQIECDRNQKC5adR2RIAAAQIECBAgQIAAAQIECBAgQIAAgXIKCDSXs16VigABAgQIECBAgAABAgQIECBAgAABAk0TEGhuGrUdESBAgAABAgQIECBAgAABAgQIECBAoJwCAs3lrFelGojAkCFpyEDWsw4BAgQIECBAgAABAgQIECBAgACBDhcQaO7wN4DiVwm8+256t2rUIAECBAgQIECAAAECBAgQIECAAAEC9QkINNfnZCkCBAgQIECAAAECBAgQIECAAAECBAgQqCEg0FwDxmQCBAgQIECAAAECBAgQIECAAAECBAgQqE9AoLk+J0sRIECAAAECBAgQIECAAAECBAgQIECAQA0BgeYaMCYTIECAAAECBAgQIECAAAECBAgQIECAQH0CAs31OVmKAAECBAgQIECAAAECBAgQIECAAAECBGoICDTXgDGZAAECBAgQIECAAAECBAgQIECAAAECBOoTEGiuz8lSBAgQIECAAAECBAgQIECAAAECBAgQIFBDQKC5BozJBAgQIECAAAECBAgQIECAAAECBAgQIFCfgEBzfU6WIkCAAAECBAgQIECAAAECBAgQIECAAIEaAgLNNWBMJkCAAAECBAgQIECAAAECBAgQIECAAIH6BASa63OyFAECBAgQIECAAAECBAgQIECAAAECBAjUEBBorgFjMgECBAgQIECAAAECBAgQIECAAAECBAjUJyDQXJ+TpQgQIECAAAECBAgQIECAAAECBAgQIECghoBAcw0YkwkQIECAAAECBAgQIECAAAECBAgQIECgPoFh9S1mKQLtIzB16tQ0Y8aMtNBCC6X555+/fTImJwQIECBAgAABAgQIECBAgAABAgQ6VECL5g6t+KIWe/LkyWn11VdPo0ePThdccEFRiyHfBAgQIECAAAECBAgQIECAAAECBEolINBcquosd2HeeeedtP/++6dp06aVu6BKR4AAAQIECBAgQIAAAQIECBAgQKBgAgLNBauwTs7uWWedlW688cZOJlB2AgQIECBAgAABAgQIECBAgAABAm0pINDcltUiUz0F7r///vTVr36152TjBAgQIECAAAECBAgQIECAAAECBAi0gYBAcxtUgiz0LfDGG2+kL3zhC9lC48aN63thcwkQIECAAAECBAgQIECAAAECBAgQaLqAQHPTye2wvwJHHHFEmjBhQlpnnXXSMccc09/VLU+AAAECBAgQIECAAAECBAgQIECAwCALCDQPMrDNz53A1Vdfnc4777xsIxdccEEaPnz43G3Q2gQIECBAgAABAgQIECBAgAABAgQINFxAoLnhpDbYKIHnnnsu7b///tnmTj311LTWWms1atO2Q4AAAQIECBAgQIAAAQIECBAgQIBAAwWGNXBbNkWgYQIzZ85Me+21V5o2bVr6+Mc/nvbdd98BbXvGjBlp6tSpda375ptvZsstt9xyaeLEiXWtY6H2Fpg+fXqWQfXZ3vVUb+7UZ71SxVhOfRajnurJpbqsR6k4y+ywww5ZZv12FqfO+sqpz2dfOsWbpz6LV2d95Vh99qVTvHnqs3h11leO1WdfOn3PE2ju28fcuRS45ZZb0osvvlj3VlZYYYU0ZsyYdMopp6Q77rgjjRw5Mp199tlp6NCBN76PoHU96d13361nMcsQIECAAAECBAgQIECAAAECBAgQINBDQKC5B4jRxgoce+yxafz48XVvdOedd06LLbZY+ta3vpWtc8ABB6Tnn38+++u5kWeeeSbdd999ad55501rr712z9nZ+LBhw9JSSy3V67yeE/P+nydNmpRGjRrVc7bxAgrkrbHUZwErr5csq89eUAo8SX0WuPJ6ZF1d9gAp+Ohxxx2XlSBv2Vzw4nR89n0+y/UWUJ/qs1wC5SqNz6f6LK7A3Q3NukBzQzltrKfASiutlF577bWek2uOR7cVkydPrsw/+eSTU/z1lk4//fQUf9HquXqd6mUj0Fxvmmeeeepd1HIECBAgQIAAAQIECBAgQIAAAQIECFQJ1B+Fq1rJIIF6BS666KJ6F60sd9ddd6UIONdK0eI4T7Hcoosumo96JUCAAAECBAgQIECAAAECBAgQIECgBQICzS1At8u+BTbeeOM0YcKEmgtFNwhTpkzJ+nE+8MADay5nBgECBAgQIECAAAECBAgQIECAAAECzREY+BPWmpM/eyFAgAABAgQIECBAgAABAgQIECBAgACBNhcQaG7zCpI9AgQIECBAgAABAgQIECBAgAABAgQItLuAQHO715D81RQYOtTbtyaOGQQIECBAgAABAgQIECBAgAABAgSaKKCP5iZi21VjBCZOnNiYDdkKAQIECBAgQIAAAQIECBAgQIAAAQINEdAktCGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNkKAAAECBAgQIECAAAECBAgQIECAAIHOFRBo7ty6V3ICBAgQIECAAAECBAgQIECAAAECBAg0RECguSGMNtIMgenTp6cXXnghxatEgAABAgQIECBAgAABAgQIECBAgED7CAg0t09dyEkvAjNnzkznn39+WnvttdP73//+tNJKK2WvW2+9dbrxxht7WcMkAgQIECBAgAABAgQIECBAgAABAgSaLSDQ3Gxx+6tb4J133kn77rtvOuSQQ9LTTz/dbb0//elP6VOf+lS69NJLu003QoAAAQIECBAgQIAAAQIECBAgQIBA8wUEmptvbo91Cpx11lnpsssuy5beZptt0q233pqeffbZdPnll6eRI0dm0w899ND0+uuv17lFixEgQIAAAQIECBAgQIAAAQIECBAgMBgCAs2DoWqbcy3w5ptvppNOOinbzhZbbJF+8YtfpE022SQtvvjiabvttkvnnHNONm/atGnpnnvumev92QABAgQIECBAgAABAgQIECBAgAABAgMXGDbwVa1JYPAEovXylClTsh18/etfT8OHD++2s2233TYdeOCB6d13300jRozoNs8IAQIECBAgQIAAAQIECBAgQIAAAQLNFRBobq63vdUpEH0wR1puueXShz/84cpa0W/z0KFD03zzzZdOOeWUynQDBAgQIECAAAECBAgQIECAAAECBAi0TkDXGa2zt+c+BP785z9nczfeeOP05JNPpv333z+tv/76acEFF8xeDzrooKy/5j42YRYBAgQIECBAgAABAgQIECBAgAABAk0S0KK5SdB20z+BF154IVvhiSeeSB/60IdS9MWcpwkTJqT4u+CCC9IVV1yRohsNiQABAgQIECBAgAABAgQIECBAgACB1gkINLfO3p77EHj++eezuQ899FD2Onbs2LTzzjtnw3fccUc6/vjjs+E999wz3XfffWmZZZbJxnv+e+utt3pOqjk+a9asmvPMIECAAAECBAgQIECAAAECBAgQIECgtoBAc20bcxogcMstt6QXX3yx7i2tsMIKacyYMd1aMJ944onpS1/6UmUbH/vYx9ISSyyRvvzlL2fLXXbZZdlwZYGqgejT+aWXXqqaUntwxowZ2czoF3rixIm1FzSnMALTp0/P8qo+C1NlfWZUffbJU7iZ6rNwVVYzw+qyJk0hZ+ywww5Zvv12FrL6Zsu0z+dsJIWeoD4LXX2zZV59zkZS6Anqs9DVN1vm1edsJHVPEGium8qCAxE49thj0/jx4+teNVotR6A5gr2TJk1KI0eOTAcffPBs6++4446V4PIjjzwy2/zqCfHgwHrSPPPMU89iliFAgAABAgQIECBAgAABAgQIECBAoIeAQHMPEKONFVhppZXSa6+9VvdGI8AcadVVV80CzauvvnrqLQAcLZo32GCDrNuMp556qub2hw8fnuKvnpQvFwHuUaNG1bOKZdpcIG+NpT7bvKLqzJ76rBOqIIupz4JUVB3ZVJd1IBVokeOOOy7Lbd6yuUBZl9VeBHw+e0Ep8CT1WeDK6yXr6rMXlAJPUp8Frrxest5Z9Xl3LwIDnyTQPHA7a9YhcNFFF9Wx1OyLjB49Ot12220p76t59iVS+uc//5lNXm211XqbbRoBAgQIECBAgAABAgQIECBAgAABAk0SGNqk/dgNgX4JbLbZZtny0br4j3/842zrxkMC8y4z1ltvvdnmm0CAAAECBAgQIECAAAECBAgQIECAQPMEBJqbZ21P/RDYfffdU95Sea+99kr3339/Ze3nnnsu7b333tl49OH8mc98pjLPAAECBAgQIECAAAECBAgQIECAAAECzRfQdUbzze2xDoFhw4alk08+OX3qU5/K+mqOFs4ReI7peUvm2MwZZ5yRFllkkTq2aBECBAgQIECAAAECBAgQIECAAAECBAZLQIvmwZK13bkW+PjHP57uvPPOSsvmCRMmVILM8TDAG2+8Me2yyy5zvR8bIECAAAECBAgQIECAAAECBAgQIEBg7gS0aJ47P2sPssAGG2yQ7rnnnvTUU0+lBx98MM0zzzxprbXWSvGwwGjdLBEgQIAAAQIECBAgQIAAAQIECBAg0HoBkbrW14EczEEggsvRbUbeZ/McFjebAAECBAgQIECAAAECBAgQIECAAIEmC+g6o8ngdkeAAAECBAgQIECAAAECBAgQIECAAIGyCQg0l61GlYcAAQIECBAgQIAAAQIECBAgQIAAAQJNFhBobjK43REgQIAAAQIECBAgQIAAAQIECBAgQKBsAgLNZatR5SFAgAABAgQIECBAgAABAgQIECBAgECTBQSamwxudwQIECBAgAABAgQIECBAgAABAgQIECibgEBz2WpUeQgQIECAAAECBAgQIECAAAECBAgQINBkAYHmJoPbHQECBAgQIECAAAECBAgQIECAAAECBMomINBcthpVHgIECBAgQIAAAQIECBAgQIAAAQIECDRZQKC5yeB2R4AAAQIECBAgQIAAAQIECBAgQIAAgbIJCDSXrUaVhwABAgQIECBAgAABAgQIECBAgAABAk0WEGhuMrjdESBAgAABAgQIECBAgAABAgQIECBAoGwCAs1lq1HlIUCAAAECBAgQIECAAAECBAgQIECAQJMFBJqbDG53BAgQIECAAAECBAgQIECAAAECBAgQKJuAQHPZalR5CBAgQIAAAQIECBAgQIAAAQIECBAg0GQBgeYmg9sdAQIECBAgQIAAAQIECBAgQIAAAQIEyiYg0Fy2GlUeAgQIECBAgAABAgQIECBAgAABAgQINFlAoLnJ4HZHgAABAgQIECBAgAABAgQIECBAgACBsgkINJetRpWHAAECBAgQIECAAAECBAgQIECAAAECTRYQaG4yuN0RIECAAAECBAgQIEB+JXmKAAA8bElEQVSAAAECBAgQIECgbAICzWWrUeUhQIAAAQIECBAgQIAAAQIECBAgQIBAkwUEmpsMbncECBAgQIAAAQIECBAgQIAAAQIECBAom4BAc9lqVHkIECBAgAABAgQIECBAgAABAgQIECDQZAGB5iaD2x0BAgQIECBAgAABAgQIECBAgAABAgTKJiDQXLYaVR4CBAgQIECAAAECBAgQIECAAAECBAg0WUCgucngdkeAAAECBAgQIECAAAECBAgQIECAAIGyCQg0l61GlYcAAQIECBAgQIAAAQIECBAgQIAAAQJNFhBobjK43REgQIAAAQIECBAgQIAAAQIECBAgQKBsAgLNZatR5SFAgAABAgQIECBAgAABAgQIECBAgECTBQSamwxudwQIECBAgAABAgQIECBAgAABAgQIECibgEBz2WpUeQgQIECAAAECBAgQIECAAAECBAgQINBkAYHmJoPbHQECBAgQIECAAAECBAgQIECAAAECBMomINBcthpVHgIECBAgQIAAAQIECBAgQIAAAQIECDRZQKC5yeB2N3CBV199Nf3zn/8c+AasSYAAAQIECBAgQIAAAQIECBAgQIDAoAgINA8Kq402SuDRRx9Nu+66a1pqqaXSsssumxZddNG09tprp2984xvptddea9RubIcAAQIECBAgQIAAAQIECBAgQIAAgbkQEGieCzyrDq7Addddlz74wQ+ma6+9Nk2bNq2ys6effjqdfPLJacMNN0wvvvhiZboBAgQIECBAgAABAgQIECBAgAABAgRaIyDQ3Bp3e52DwEsvvZT23nvvbKklllgiXXjhhWn8+PHpzDPPTB/60Iey6ZMmTUrjxo2bw5bMJkCAAAECBAgQIECAAAECBAgQIEBgsAUEmgdb2PYHJPCnP/2p0or529/+dtpll13Smmuumfbaa690ww03pNGjR2fbveKKK9LMmTMHtA8rESBAgAABAgQIECBAgAABAgQIECDQGAGB5sY42kqDBaJv5jxtv/32+WD2OnTo0LTTTjtVpr3++uuVYQMECBAgQIAAAQIECBAgQIAAAQIECDRfQKC5+eb2WIdAPPgvTxMmTMgHs9dZs2alK6+8MhuObjQWWWSRbvONECBAgAABAgQIECBAgAABAgQIECDQXAGB5uZ621udAv/2b/+WRo4cmS292267pdNOOy09/PDDKR4QuPvuu6d4IGCk6pbN2QT/CBAgQIAAAQIECBAgQIAAAQIECBBousCwpu/RDgnUIRAPAIyg8s4775ymTJmSjjzyyOyvetV99903jR07tnqSYQIECBAgQIAAAQIECBAgQIAAAQIEWiAg0NwCdLusT2DSpElpxowZNReOBwY+/vjjaZ111qm5TKw/ffr0mvOrZ+T7Wm655dLEiROrZxkuqEBe9+qzoBXYI9vqswdIwUfVZ8ErsCr76rIKowSDO+ywQ1YKv50lqMyuIvh8lqMe81Koz1yiHK/qsxz1mJdCfeYS5XhVnwOvR4HmgdtZsw6BW265Jb344ot1LPl/i6ywwgppzJgx6aqrrkqf/exns4mjR49Oxx13XFp//fXTtGnTsnknn3xyeuihh9InPvGJ9MADD6SFF1645j7efPPNmvOqZ0TfzxIBAgQIECBAgAABAgQIECBAgAABAv0XEGjuv5k1+iFw7LHHpvHjx9e9RnSVEYHm/GF/0U/zzTffnJZeeunKNjbYYIMUweeDDjoo61bj0ksvTfvvv39lfs+BRRddtOekXsff9773ZdOjJfWoUaN6XcbEYgnkrbHUZ7HqrVZu1WctmWJOV5/FrLfecq0ue1Mp7rS4uB8pb9lc3JLIeQj4fJbrfaA+1We5BMpVGp9P9VlcgbsbmnWB5oZy2lhPgZVWWim99tprPSfXHI9uK2bOnJluvPHGbJk99tijW5A5X/Fzn/tcFmiO8XhIYK00fPjwWrNmmz7vvPPONs0EAgQIECBAgAABAgQIECBAgAABAgTmLCDQPGcjS8yFwEUXXdTvtadOnZp1kRErLrTQQr2uP2zYsBQPDIwHBb7zzju9LmMiAQIECBAgQIAAAQIECBAgQIAAAQLNERjanN3YC4H6BaK/5WjZHOm3v/1t1sK559rPPPNMFmSO6X09DLDnesYJECBAgAABAgQIECBAgAABAgQIEGi8gEBz401tsQEC2223XbaVeODf4YcfnvIH+kW3Grfffnv6/Oc/X9nLv/7rv1aGDRAgQIAAAQIECBAgQIAAAQIECBAg0HwBgebmm9tjHQLxIJrVVlstW/Lss89Oiy++eNpkk02yls7bbLNN5QGD//3f/51WWWWVOrZoEQIECBAgQIAAAQIECBAgQIAAAQIEBktAoHmwZG13rgSib+brr78+7b333pXtROvmadOmZeMjR45M5513Xjr00EMr8w0QIECAAAECBAgQIECAAAECBAgQINAaAQ8DbI27vdYhsMwyy6QzzjgjHXXUUemRRx5JTz31VFpggQWyls5rrLFGimCzRIAAAQIECBAgQIAAAQIECBAgQIBA6wUEmltfB3IwB4Fll102xd/WW289hyXNJkCAAAECBAgQIECAAAECBAgQIECgFQK6zmiFun0SIECAAAECBAgQIECAAAECBAgQIECgRAICzSWqTEUhQIAAAQIECBAgQIAAAQIECBAgQIBAKwQEmluhbp8ECBAgQIAAAQIECBAgQIAAAQIECBAokYBAc4kqU1EIECBAgAABAgQIECBAgAABAgQIECDQCgGB5lao2ycBAgQIECBAgAABAgQIECBAgAABAgRKJCDQXKLKVBQCBAgQIECAAAECBAgQIECAAAECBAi0QkCguRXq9kmAAAECBAgQIECAAAECBAgQIECAAIESCQg0l6gyFYUAAQIECBAgQIAAAQIECBAgQIAAAQKtEBBoboW6fRIgQIAAAQIECBAgQIAAAQIECBAgQKBEAgLNJapMRSFAgAABAgQIECBAgAABAgQIECBAgEArBASaW6FunwQIECBAgAABAgQIECBAgAABAgQIECiRgEBziSpTUQgQIECAAAECBAgQIECAAAECBAgQINAKAYHmVqjbJwECBAgQIECAAAECBAgQIECAAAECBEokINBcospUFAIECBAgQIAAAQIECBAgQIAAAQIECLRCQKC5Fer2SYAAAQIECBAgQIAAAQIECBAgQIAAgRIJCDSXqDIVhQABAgQIECBAgAABAgQIECBAgAABAq0QEGhuhbp9EiBAgAABAgQIECBAgAABAgQIECBAoEQCAs0lqkxFIUCAAAECBAgQIECAAAECBAgQIECAQCsEBJpboW6fBAgQIECAAAECBAgQIECAAAECBAgQKJGAQHOJKlNRCBAgQIAAAQIECBAgQIAAAQIECBAg0AoBgeZWqNsnAQIECBAgQIAAAQIECBAgQIAAAQIESiQg0FyiylQUAgQIECBAgAABAgQIECBAgAABAgQItEJAoLkV6vZJgAABAgQIECBAgAABAgQIECBAgACBEgkINJeoMhWFAAECBAgQIECAAAECBAgQIECAAAECrRAQaG6Fun0SIECAAAECBAgQIECAAAECBAgQIECgRAICzSWqTEUhQIAAAQIECBAgQIAAAQIECBAgQIBAKwQEmluhbp8ECBAgQIAAAQIECBAgQIAAAQIECBAokYBAc4kqU1EIECBAgAABAgQIECBAgAABAgQIECDQCgGB5lao2ycBAgQIECBAgAABAgQIECBAgAABAgRKJCDQXKLKVBQCBAgQIECAAAECBAgQIECAAAECBAi0QkCguRXq9kmAAAECBAgQIECAAAECBAgQIECAAIESCQg0l6gyFYUAAQIECBAgQIAAAQIECBAgQIAAAQKtEBBoboW6fQ5IYObMmQNaz0oECBAgQIAAAQIECBAgQIAAAQIECAyugEDz4Praeg2BM844I40YMSKNGzeuxhL/N3ny5Mnpa1/7Who1alRaaKGFstexY8emSy65pM/1zCRAgAABAgQIECBAgAABAgQIECBAoHkCw5q3K3si8H8Cb731VvrpT3+ajfTVSnnSpEnpYx/7WIrXPE2ZMiULMkeg+ZlnnklHHnlkPssrAQIECBAgQIAAAQIECBAgQIAAAQItEtCiuUXwnbjbWbNmpfvuuy994QtfSI888sgcCfbee+9KkPmQQw5JN910U7ryyivTdtttl6173HHHpfPPP3+O27EAAQIECBAgQIAAAQIECBAgQIAAAQKDK6BF8+D62vp7Ap/5zGfSb37zm7o97rzzzvSHP/whW/6ggw5KJ510UmXdj3zkI2mLLbbIgtUnnHBC2muvvdKQIUMq8w0QIECAAAECBAgQIECAAAECBAgQINBcAS2am+vdsXubMGFCv8p+zTXXVJY//PDDK8MxEH07H3bYYdm06FZj/Pjx3eYbIUCAAAECBAgQIECAAAECBAgQIECguQICzc317ti93XjjjenJJ5+s/C2xxBJ9Wtx8883Z/E022SQtueSSsy27+eabV6b95S9/qQwbIECAAAECBAgQIECAAAECBAgQIECg+QK6zmi+eUfu8f3vf3+3cr/vfe/rNl498u6776aHHnoom7ThhhtWz6oMjx49ujL8wgsvVIYNECBAgAABAgQIECBAgAABAgQIECDQfAEtmptvbo9zEHjjjTcqSyy++OKV4Z4DeavoKVOm9JxlnAABAgQIECBAgAABAgQIECBAgACBJgpo0dxEbLuqT+C1116rLLjoootWhnsOLLLIIimCzK+++mrPWZXxH/zgB+moo46qjNczsMwyy6QzzzyznkUtQ4AAAQIECBAolcCWW26ZlcexUKmqVWEIECBAgAABAjUElq4xfWCTBZoH5jbXaw0ZWqzG5DNnzkxXXnllv8od3V6sssoqva7zTlf3GPH3btfcnhbD558/mxcrznrnndnm5xt8+ZVXsuUW7go499xGvkwaMqSyrcq0OQy807VPiQABAgQIECDQiQJ9XcDvRA9lJkCAAAECBAgQqF9AoLl+q45ecvr06enzn/98vwzOOOOMmoHmvjZU3Yp56tSpvS4a/TjnXWbkXWj0tuC4ceNS/NWTTj311HTkEUekF7taSe8zdmw9qxRymajLl19+Oc3fFdBfbLHFClmGejKdl3PEiBGp+j1Vz7pFWubNN99Mr3RddFlggQVStPIva4oudSL4seCCC6aFF164rMVMr7/+eorvvZEjR6aFFlqotOWcNm1airtXyl7OKOPrXWUd2VWXUdaypnjPxns3PpvxGS1riu+g+C6K79r4zi1rit+U+G2J3874DS1rimOhOFaIY6E4Jiprevmll9L0GTNSPC9l+PDhZS1meqmrnDO6yhnd7s0333ylLeeLL76Y3nrrraycfT3zpugAcZ4X5YyHws8777xFL07N/Mezht5+++201FJLpWHDyhuamTx5coqGa2Uv5/PPP59mzZqVll566TTPPPPUrPeiz/jHP/6RonFe3Ak+tGANKPtj//e//z1F3GnZZZftar84pD+rFmrZONb76Km/amiey/tt1lAmG4svytVWW61fEAMNesWXVQSP4wDj6aef7nWf1QHo+MGSCBAgQIAAAQIECBAgQIAAAQIECBBonYBAc+vsC7XnuMrx0EMPNS3PG220Ufrtb3+bfv/73/e6z9tuu60yffPNN68MGyBAgAABAgQIECBAgAABAgQIECBAoPkCxeoouPk+9tgigd122y3b86RJk9KvfjV7M/6LL744mx8tnzfYYIMW5dJuCRAgQIAAAQIECBAgQIAAAQIECBAIAYFm74O2FNh+++0r+TrwwAPTfffdl41H307HH398+vWvf52Nx7wy9wtUQTBAgAABAgQIECBAgAABAgQIECBAoI0FdJ3RxpXTyVmLhyZF1xnbbrttiodGbbrpplm/zfGQjxiPFH1G1/ugv062VHYCBAgQIECAAAECBAgQIECAAAECgy2gRfNgC9t+nwJ9tUbeaqut0uWXX54i6BwpHg6YB5m33nrrdMstt5T6aeh9wplJgAABAgQIECBAgAABAgQIECBAoI0EtGhuo8ropKw89dRTdRX3k5/8ZBZgfvTRR9Ndd92Vhg8fntZee+3sr64NWIgAAQIECBAgQIAAAQIECBAgQIAAgUEXEGgedGI7mFuBIUOGpDXXXDP7m9ttWZ8AAQIECBAgQIAAAQIECBAgQIAAgcYL6Dqj8aa2SIAAAQIECBAgQIAAAQIECBAgQIAAgY4SEGjuqOpWWAIECBAgQIAAAQIECBAgQIAAAQIECDReYMi7XSk2u9VpV3Tb+u8P3bnbuJH+Cdz27JRuK3zrqtu7jV9/4Ce7jRtpE4Guj8N7H4k2yZBsECBAgECRBYZ0ZT470CpyIeSdAAECBNpHoKtbwa4TlvbJj5wQIECAQKEFtj3num757xkP7m+8WIvmbpxGCBAgQIAAAQIECBAgQIAAAQIECBAgQKC/AgLN/RWzPAECBAgQIECAAAECBAgQIECAAAECBAh0ExBo7sZhhAABAgQIECBAgAABAgQIECBAgAABAgT6KyDQ3F8xyxMgQIAAAQIECBAgQIAAAQIECBAgQIBANwGB5m4cRgj0XyAeHjhz5sz+r9iGa0RZXnvttTbMWWOzFOV86aWX0qxZsxq7YVtrmcDUqVM74r3bMuAW7Dg+n5MnT05TpnR/uG4LsjIou3z77bfT9OnTB2Xb7bbRF198sTS/k+1mOxj5KdNxzWD4FHGbnfAZfPPNN1N8r3ZKit+P+I2M4x+puAJxDhnHOeqxuHVYnfP4Hpo2bVr1pFIOx/fPW2+9Vcqy1VuoTvq9qdekejmB5moNwx0vMP6ee9KIESPS+uuvP0eLa6+9Nm299dZpgQUWSAsttFA2/O1vfzs9/fTTc1y33Ra49NJL07//+7+npZdeOvsLg5122in98Y9/bLeszlV+rr/++vSxj30sq7MVVlghjRw5Mm2yySbpwgsvLHzQ+eGHH07/9m//VvffCSecMFeW7bDyK6+8kr7xjW+kpZZaKi2zzDLZezeGP/OZz6T//d//bYcsznUeDjvssDnW6UMPPTTX+2nHDZx00klp9OjRadSoUe2YvQHlKU4kjznmmOz3YuGFF07vf//7s/LF9+0dd9wxoG2260o//elP06677pp9PldcccXsdzK+b08++eTSBoM+/elPZ8cQl19+ebtWS5/5KtNxTZ8FrZpZ9DqrKspsg53wGXz00UfToYcemjbccMO0+OKLp/heXW211dIhhxySnnrqqdlMyjIhLsTG70b8Ru67776lKFYEreJcpK9j2ZhflkYit9xyS3YsEOeQcZwTx7HxPv7hD3+Y3nnnnULX6ZFHHtlnPfas42effbbQ5Y3GS3G8Ht898T0U5yJRp3vttVch4wK1KuOFF15IBx10UBYniePXRRZZJCvziSeeWPjGPvUeCzz44IPZeWbUcfzeRMwo6v7OO++sxdZW0//5z39m78+I9fz9738f1LwN6Wq18G7sYavTrui2o98funO3cSP9E7jt2e4tsL511e3dNnD9gZ/sNm6kPQS++MUvpp+ce25abrnl0oQJE2pmKr5QI6jcW4p1f//736cIZLZ7io//l770pXTeeefVzOpZZ52V/vM//7Pm/KLMiODOKaecUjO72223XfrlL3+Zhg4dWnOZdp7xpz/9KTtgrTePO++8c7rooovqXbztlnv55ZfTlltuWfNzGhcRbr/99vQv//IvbZf3/mQoDlTn1KL3pptuSh/60If6s9m2X7bn+zlaiBQ1DenKeBxovfrqq+lTn/pU+utf/1qzKBFcjwBJkVP8rhx77LF9ft/GyXRc+IsLtWVJcaK8xhprZMW54IILsiB7kcpWluOa/pgXvc5qlbVTPoN/+9vf0lZbbdVn68HbbrstbbzxxrWoCjv9lO9/Px3z9a9n+d9+++2z49fCFua9jD/55JNp3XXXnWMx4s7LYcOGzXG5dl7gJz/5SXb+VSuPY8eOTaeffnqt2W0/Pd6TcS5cbxo/fnxac8016128rZabOHFi1mipr1bMN998c9pss83aKt/9zcw9XY3xdtxxx5rnJBtssEG65pprsgYU/d12q5ev91jg1ltvTREvqJWuu+667Ny01vx2mP6rX/2qEtd57LHHusWrtj3num5Z7BkP7m+8uNjf0t0ojBAYuED8SMSJ4bk//nEaMiTCArVTtPLNg8zRkuDrXQd6q6++ehY8+MpXvpImTZqUttlmmxSBkrhK3c7pqquuqgSZ4wciggPR8ixaiERgNlpnH3jggenDH/5wWmWVVdq5KH3mLeosDzJHgOO4445Liy66aLrhhhuy1sxRzv/5n/9J559/ftpnn3363Fa7zozW6Pvvv3+f2YuLJ/mB3wc+8IE+l233mQcccEAlyByfu89//vNZC/VoSfi1r30tO/E8+uijU1FbFob/G2+8UTmgixZbCy64YK/VEp/ZMqVoqf6FL3yhTEXKyhLv0zzIHC3QIug8fPjw7Lvnx12/PXGScvjhh6dtt9220N+3UZbq79so99prr539NsZ3b/w2xkllLBO/OUVP0TokLmodccQRhS1KmY5r6qmEMtRZX+XshM9gtPiME/48uPPf//3fafPNN09xETqObfML6XvssUd6/PHH53hs35dnu827++67K0Hmdsvb3OTnmWeeyVaPhgLRCKa3FI1B5plnnt5mFWbavffeWylfnEf+4Ac/SHEOFnfixYXm++67Lzs3i9awH/zgBwtTruqMRqA5Wvf2lc4555xs9hJLLJG1sOxr2Xaet99++1W+h+IYJ1rdx3s5AnrxFynutIygXhzzFTFF9y5x3Jo3fIljtyhndB0Rd0WfffbZ2fs2Ygc/+tGPClPE/hwLxLnJbrvtVilb3J03ZsyY7PclLtTHOfYnPvGJ7Bi3njvjKxtq0kDkP+5am1OsoJHZEWhupKZtFU7g1FNPTccff3zlB6LvEPP/FS+WjxQHQr/5zW8qAYEIYMZtJHvuuWcWoI2rWrvvvvv/rdSm/+MHIVIc6EQAMv8BXGuttbIrr3lwOZzOOOOMNi3FnLMVV1jzFMHk/OAnfgjixz9vhRbB5qIGmqMOo55qpbjVML8KG62Zx40bV2vRtp9+//33Zz+WkdEIzH3zm9+s5DnuSogDvGiJH/UZLWHj9qAiprgAlqfvfOc7hT+5yssyp9c4wYwLdmVK0cIwDvAixXv0u9/9bqV40colbiONC5SR7rrrrsrvSmWhAg3kJxnxPRu/kXFRL1KMx0H5pptumh2Qx4F5XAwqatAgWqjHnQRF7C6r59upTMc1PctWPV6mOqsuV8/hTvgMRvA4D3pcdtll6ZOf/P93isZ36UorrZQ1KojfkgjgleWCbLTmLcNdhj3fszGed3US36vx21DWlP/+x3lk3NmT3wEbAdcrrrii8vsfjWGKGmiOxiB9peg2JA80//rXv06LLbZYX4u37bzo+/4Pf/hDlr+4qBUX1iOts846KYLt0bXEuV13Ssd3VdyBEbGCIqa4ePfII49kWY96i8Y9eYou0eLutGg8EI324qJ7u3/fDuRYIOoxv7B5ySWXpP/4j//ICKJON9poo0q3q+GT/wbnRq18jffn5z73ucrvZTPzUsx7xJspZF+lFoi+afIvjXoKGn0wxW14kSKgnAdi83WjP8o4UIiUX8XM57Xba/zo5SfIEazLg8x5PqOvsPxAIQK1Re4vLP9xjNuy8iBzXs74MYyWBJHyk5Z8Xple4xa8+LGJrl1ieE4t99u57HH1PE/RL1bPFK0L4r0bfzNmzOg5uzDjETCPFAesRQ3GZQXox79ohRYnWn21aOrH5tpm0SeeeKLyWxO3HvZM0RIvT/n3cj5epNdoMZF3OxUX8fIgc16G+J2pbq1e5LJGC58i5z+vkzId1+RlqvValjqrVb6Y3imfwb/85S8VhmhZ1zPF8zjyVH3RNp9W1Nf/+q//yr53IriRNx4oall65jsPNBe1C4We5eltPL5v4wJspC9/+cuVIHO+bJx7Rev8OH6NiyVlTHHXQZxDR4oGMvk5WDahYP/i2C5PcZdazxR3qOUp6r6oKe6iiBQxjgio90zRb3OeopuQdk8DORbI75CN76c8yJyXM2ILefA9zmHa6dwzng3TqviGQHP+DvHakQJx60cEc/K/nbse5NNXym97jmXy1mc9l88P/OIqdTun6hPkVVddtdes5g/hii+oMCpqiuBqpOeeey7rJ7W6HFGuuE0tUl531fPLMBwPLjjqqKOyosQttXGFvcgpv9iz9957d+ueJr8YEv0yf7+r/8L4K2oriaif/KQruh2IFOWLJ8zHAVIZUwQo81u6zjzzzOxOi7KUM4I/8f0Sf73dUlf9fRwnmkVN8aCYPNU6eXzf+96XL1LoC5jxwJ/oUzT/y7slqhSuIANlOq6ZE3lZ6qyvcnbKZzDuEonv0+hWqvo7JbeJFs95iq7FypDiOSI///nPs6LEQ6x7K3eRy5lfpMzPSeLhgK0KkAyWY3QblafPfvaz+WC338IIQMfxa7vfFVvJfD8H4jMb9Rp3c0XDkCKneCBcnqLbyZ4pv5Mtplc3KOi5XLuP5w224o7n3hq+VH/H/vnPf2734mQPbMyP3eJ1TsdvcXEkf/B6bxcUosAf/ehHs3JHA8be3gutQvn4xz9eOU6NssazYJqVdJ3RLGn7aUuBaDUXf3mqHs6nVb9G/0p5ii/b3lL1lfj4spnTNnvbRjOmVff3Grfz9PYwsbglKE9xJXbllVfORwv1Gn0qxUF51EfcXhktBeJWn+iXMm6FyVMZA83Tp0+vtByIiyPxAL0ipyhPfmEgHhoTD8KLh1lGv69x4BrBrbhdLbpfqH6PF7HMeaA5WkxEi6389rwoS7RmitvToj+wMqToJy2/HThaS8TTn/PbKstQvvi+yVtDVJcnLh7EyXX0xZin3lrn5fPa/TXu8omubSLltwNX5zkukkSwJE9F/U3J8199USCCIkVMZTquqce/DHXWVzk75TMYLSLzVpHVHvE5vOOOO7JutWJ6HBMU/XsmyhEXI/PyRn+oKxf4uSlRnt5SHmj+7W9/m3V/lgd24jwqzlGi/9v8wntv6xdhWnWgOe74iS5Coo//mB6tRePBldH9QtEfHFerLqLLgWjxGSkCXkW+uzLKEA2y4r0Z3znReC1aj8Z5ZhzbxTFfdNcYKc5LinxOsvDCC2fliAcCxnFcz4dxRrnzFA1iipD6cywQAdo81XpgafXD59vpAllckKwua3Tz2qykRXOzpO2nFALRp0+earUKrb5VuJ1vk6k+8K6+4pqXLzr4j/7B8hQt8oqa4hbKCEZGioO5eKBBtCo8+OCDK0HLCDj31tKwqGXO8x19a+dXoqNP1KKn6s/glVdemd2+FLch5j/qEYSO/ozjZKTIrfCjnvIWWfGerQ4yx7yYtssuu1RaAMe0Iqc4gYy6i7sP8gfJFbk8c8p7fCbj+yZOPOLBnFH2OJmOvv2rDwjntJ12mx8nH3ELYfz17I4pLibEBaB470aK4Z4nK+1Wnk7IT/V3atGPazqhvuZUxk79DEa3S/GdGu/huAAbDQui26mY3lsLvDk5ttP8OB7PL0busMMO3bofaqd8zk1eIniVB5rjnCQPMsc2oy7jLtEIwkajkSKn/Fg1fu/jonJ0HZH/Jsa8eLbI1ltvXXnofJHL2jPv0b94tNaOFA0KitpfcXW54uGUP/vZz9JWW22VTY7j1zjnjPG8n94oZ5GfcxQFyxvXxWcx70aj2qG6RXA7xz6q89yf4Xjv5qnWnbLVx0/VDfXy9TrxVaC5E2tdmQcsUH1CNt988/W6negQP0+vv/56Pth2rxEEiIfCRfrd737XrZVZBJUjCFB9oFf0A/U33nijzzqIFhRl+3GMMn/ve9/Lyh1Psl599dX7NCjCzOof+zz4+q1vfStFn2DRSiJ/InAcsI8dO7bQ3UxElyd5igceRgv8uB0rTrTy7mDiJPqnP/1pvlghX+OhMHGbaKQ4YM9bThSyMHVmOh5SmZ9U56vEAXxcHIlbwsuW4lbKuG00HhQTKVoZRusfqfUCZTquab1m++ag7J/B6r6p81qIaUVpXZfnubfXeHhcdHETLV6LHrDqrXwxLR7YmKcoZ9zRFBdg4w6ZaDyQpwMPPDB7qFo+XrTXvNFO/N5H+bbYYovsmT5xDPvDH/6wchdsNAwpQl+3/fGP3/8od6Tqh3j3ZxvtuGycO1Z3WdQzj9FoJO66LHKqfthqnHNVf6/GMXx8LvNU9HhBXo7q1/xzG9NqnaNUP3i++ly1ejudNqzrjE6r8RKWN66i9efKUdzOO9Bbknq20OqNszq43IxuM6IVQDwNtj8pnmIct1fGweuNN96Y/fDHLXlf/OIXs36LqvsLzbdb6wpePn+wX+emnN/4xjfSySefnGUxrjJ/9atfzW7r/sc//pHdnhctY+MvOu/v7fb2wS5b9fbnppzV24nh6MsvP6iLMrdTGmg5I0BXnaK/5mjlkqfoHiS2HUHnOLC79957u83Pl2vWaxyMxW2R/UnRymWhhRbKbpON29HioRPVXZ7EAyzjVr1oCRv1GwfseWun/uynkcsOtJzRyjW/HTj6ER/od3Mjy9LXtgZSzm266nNkV31Wp2gdcuutt2Z9xkfXRT/5yU+yW6PjLos4aYkHPrUyDaSc+fu2Ot/xwN0IKP/iF7+oTI4uUuICWPVBeWVmkwcaVc4mZ7uhu2vH45qGFrDDN9bun8FGVU88fDS6KIqLzHfeeWd2y/qkSZPSv/7rv2YBu3b/banlEBfU4+FwkSJQF/2MlzFFS/xx48alaCARrV6rH4QXD32O1ul536gRkC1q11r5MXnUYXTXFw+Oz7uPiPdo/OXHtPHg7mjdXIYU51f53WrRR/Pyyy9fhmJlF0jieydSnPN//etfz+osWjpH45C4Wy++k6K/7fgsF7UVd3z+okuXqMM47xo9enTW4KW3ftTL+B01//zzV96vtRqDVDdoi3M4KSWBZu+Cwgscc8wxvd7GUatg0ffnQA84qzv9jy/X3h7EER3G56kZwdnoszbv2zTf75xe4yAtAs3LLrtsuuuuu7Lb7+OHIw6A8oOg+OGMJ6hG8DlSM8rSV74HWs44WI3+7CJFcO7Xv/515TbK6D4kpkXL1+g3LG5Zi1bc8YPaqjTQckZ9Vqe41TJvzRwt16OFSDulgZazuv/auIU0PyDPyxYH7LvuumulD7hoAdxzmXzZZrw+8MAD/f58xm2UcZASrQZqpfjsRlAyWr3EQWz8tbKOB1rOOGiNvEeKB1ZEC588VXd9kk+PC4XN7F8sz0v+OqBydj2te80effrHQWt+chLljmB73G4ZrZzjolerA80DKud779vcKvpizi8ixLR4fsFpp52WPvzhD+eLtPy1EeVseSHmMgPteFwzl0Wy+nsCRfgMNqqyllxyyRR/kaL1XQSe82P96JIoH27U/pqxnVmzZqXPfe5z2a4i/9E1X/5bGBPz3864OJlPj+/ZWndcNiPPA91H/LYff/zxNVeP38n4zYyW3b3dul9zxTabUd01Vpy/5kHmPJvR7VvUYXSvFQ0lypIuvfTSyvv1C1/4QlmK1a2LyShjdaOQNdZYo9uFgzjerb7oXjSEb3/721mAOe6QjRQX8vIUd1rEuXacQ+ffw/m8MrxWn1/lcZKe5apu9VzGYHvP8tYzLtBcj5Jl2logAonVndDPKbP5LedzWq63+dVfnnGbV8/gXqxT3f1CM1o0xy0q0R9mf1J1P0LROjK6jYgD1ngoUAQoI9AaX6rR4jlSlGNu3PqTt1rLDrSc0f1A/qMQt/b0dkvP/vvvnwWaY99xcNfKQPNAy9nTLVpm5wcB1cGensu1anyg5ax+snH1gxeqy5E/+TemPffcc9Wzmj4cffD29/NZ70li9fdPfO9UHwg1u6ADLefEiRMrWY1Aa62UP607LpLts88+tRYb9OkDKWe0GI2LWHEHRfxe9dZCKQIIEVCIuy8iYPD888+n6vf6oBesxw4GUs7q920EyvP+CeP3Ix7689nPfrbt+mSe23L2YCvkaDse1xQSss0yXZTP4EDYIgAb3SzFA7fGjBnT6wPior/muIMt7nq85pprunW/MJB9tmKdKGceTI47tPLfwZ55qZ4XF6qrH0rec9kij8cxXwSaW31cNzeG1S15q4/hqrcZLZ3jXCTqvlajpurl23047jLM7yqNiwVlen/GXcGRooVvdZA5r5O4cBAXSWK5/EHJ+byivcZFkb333jtrhBYPK4+7n+P9HJ/L+C7OA9BlfN5RdeA4GsFElzc9U3X8p5XnYz3z1cpxgeZW6tt3QwQuvvjihmynno1UB7biYKe3g4QIKESKA4VmpLj9eCA/XnEAGz98cQtI9JcZLSR7fjFG382RojuCVj+0aaDlzA8Cohy1Av/VrbVr3RIT6zcjDbScPfN22WWXZZOiTvsK4PVcr1njc1POuOgRQfT8BKxnnqM7hjxFYK+VKVohDeTzGe/buP03gpRHHHFEr0WIW6LzFBeMWpkGWs4Ipta6iBV9nOUXifJlWn072kDKOaSrYo7s6hYkHloZt032FmiOuqsuW89WTs2u24GUM89j/CbnQeY4wTrrrLPa9gGHc1POvLxFf23H45qim7Y6/0X6DA7EKm5Ljzt6IkVAPVra9Zby79QIdBUxRTnz376e+Y+e/P9e1aIwX663Oy17rtuO49EVRlyMjVag0Rq9t5Q3nmhlY5De8tWfadXHatHtY1zs7JnyY9io06LWZ3WZ7rnnniwoGdMiUFmmlF/0qD6P7Fm+PEgZFw2KmuJuu/iLc7c4p4zjhupjh+ouAqsb+xS1vD3znX+/xvS4sBd3fPdM+QMRI9YQFxiklIZCIECgfoEIEsRVy0jRLUHPH40IKMVV6Ejbb7999tqu/yKgGl0qRFci559//mzZjAfH3HHHHdn0eIJ3UVP1lfM8cN6zLNF9SJ7yJ+vm40V8jW4p8gB7dKvSWyvuIpYrz3PeaiD6Ya7uqiafX91neVHrM1q0RivQOIHuLVAdJyI//vGPsyLHezwO/oqY4mGG+QFsz9cof57yedEtShFTfkAerc3iZLpniu/juL07UhykVndn0HPZdh/P+xONFh9xwav6VuF2z3sn5q9MxzWdWH+9lbnsn8G4EJf3dRrfm701EIjbmPOHqeXdFPVm1c7TooFH/tvX8/WJJ55Ie+yxR5b9ON/I5/fWAKady5jnLY7D4zc/+u/teW4Vy8QD1fJATl73+bpFet1oo40q2Y2uFnqmOH7PG4oUuZzV5YquGfMUXd6VKeV1FMd21Y0/8jLGXcIRmIzUym788vwM9DUa0UW8IBrRVT+LKt9e3lVjxEjy4918Xhle4469/CJJ9JUfLbqrU/RBHg9qjxTfx/POO2/17I4dFmju2KpX8IEIxMFtfhUrAsrRh2r+ZNE46Isv4UgRKGj3QHMcwEZrrkjnnntudpCajXT9i9tC8tYi8aOx44475rMK9xq39eQXB+LBGnG7ZX5SEnUX/aHGg0ciRRcHZfiBrO6/roxXlvMWvtHaNboFqW7ZHA/fiH7vIsVDgIp6C1d1P7bRn92TTz6ZlSn+RbmjX/G8dc/RRx9dmWegPQV22mmnSsbiAl9edzExvofiYZ35hbBWP9ixktEBDMQFkvxhsttuu232DID4TNb6y1tuDWBXVmmQQJmOaxpEUujNdMpnMO+7OI7FDzjggBQBujzFd1AEYfM7Yop8DJuXqeyv0c1JpPy4Lq+7mBbHP/EwtTzl5yf5eJFe4zwjD1hFQ4J4GGCe4j0cz8XJj2nzc5N8flFf84YvccGnuuvGopanOt8f+chHKqPRsCdv4RwTo7/i6E4iPybKH2ZZWaFAA3Hnc55OOOGEynl0nE/Hszfy49d4GGKr78jL89no1+o7LeI7KD+Oj2P4mJd/Z/X3uVmNzmc7bU/XGe1UG/JSCIF4KnK09o0fzlNPPTX7i1sq8i+cKMT3v//9QjwZ+jvf+U52G3cc1ERALg+OX3vttZW6iM79i3xlLn7wotXApptumpUpTkgiEBl1lj88JS9sBNyLXNa8HNWtB/Kr7fm8MrzGQxwj2BwPwouDm1GjRmV9vsUV5fyALi725E+4LmKZo4zx+YyDtmiptO6662YXQuJW4Gg5kafo1sZJdK7Rvq/x/Ronl3H3SHzvxMlmXABbYIEFspORPOcx/dhjj81HC/caXUrl6aiu7kLmlKIP/aK2wJtT2Yo0v0zHNUVyH4y8dspnMC7IRRc98fsYd8bEX3SpEBevYlqeIuBctlaUednK9Bp3K0XDj2g5efXVV2d/EdyK+szvFI3yRmv9OOYrcorj1+g3PM69IigV3b/0PCeJZ8dE/+NFTxF8y++O7a1f26KXb5dddsnes9EKPcq5+uqrZ99DkydPrlwwiDLGsXpR78iL/EdAPRrvxDlXxD6uv/767K6SOB/JP59RxvAoa4oGQHF8HheI4jw7P47Pzzuj3NEYsfriQ1kt6i2XFs31SlmuIwTyLgb66hMrbp+Ip8ZW98GcB5kjuBX9jMVDj4qQokVzlCXvmzkCzHmQOQ564kCoDAcGEaSLFnV5WeLgrjrIHF0PxI9GUW+v7PleywPNUa6ytR7Iyxo/9nGbUnzmIsWBTv5jH+/raNUdBwFFTocddliKh9/ln884ea4OMscT2qM1TFlbD0T/lGVKP/jBD7r1JRrv12jxkqeDDjoo3XrrrYXtBiXKEX0x9ieVqY6ry1K0z2SZjmsG+v4rWp3VKmenfAbjOD2+L3fbbbcKRXyf5kHmODaIgEg0lihryr9z8tcilzPusvzpT3+a4rgnT3Gcngexoj4jAF2GVr5xp2V0FRKBuUg9z0niWCEaLJUhVZ9rFbnriL7q4swzz8yO7fLzkfgeijrNU1xYaObzpPL9NvI1fh/PO++8yp0F8bn8+c9/Xvl8xgWTGG/185wGWubq79C+jgWiLo888sjKbvLzzpgQrdfjvdDuKY91RT6ryz0Y+R7S1eQ9nieQtjrtim7b//2hO3cbN9I/gdue/f9fMLHmt666vdsGrj/wk93GjbSJQNfHIe9WoZ4cTZ06NXsC8v/+7/+mFVZYIeuKorcHO9SzrVYuE/0txQ9j3J4W/UlFC7NoAdxXwL2V+Z2bfT/22GMpujmJ25uWXHLJLBgZ3WWUoSXz3LgUdd1oxfzoo4+mhx9+OAvIRnA9LpL0daBQtLLG7ZRRvugTLAJC0WIiWsPGsNT+AvEwwOxA672sRt+hEQyJ+ozfm6jL+M7NLyi0f4nksMwCZTmuKXMdKVt3gegbNY7rJk6cmN0lEt+n8VfE4/HuJetjrCvw0/UD0scCxZ0Vz96IQNazzz6bHadHXcY5VnWApLil657zeGZDPIcjjgvi+DWO74r6zI3uJeu8sfjt/Nvf/padS0c/41GXcX4Z55plSvFdG8ewEfuI54mst956lS4qy1TOvsoS9RsXUSJ2Esfu0fd6GZ5Hsu05//esmLzsPePB/Y0XCzTnkg1+FWhuMGizNtfPQHOzsmU/BAgQIFBMgZ6B5mKWQq4JECBAoG0EShxobhtjGSFAgEAHCTQ60Fyu+1I76I2gqAQIECBAgAABAgQIECBAgAABAgQIEGgXAYHmdqkJ+SBAgAABAgQIECBAgAABAgQIECBAgEBBBQSaC1pxsk2AAAECBAgQIECAAAECBAgQIECAAIF2ERBobpeakA8CBAgQIECAAAECBAgQIECAAAECBAgUVECguaAVJ9sECBAgQIAAAQIECBAgQIAAAQIECBBoFwGB5napCfkgQIAAAQIECBAgQIAAAQIECBAgQIBAQQUEmgtacbJNgAABAgQIECBAgAABAgQIECBAgACBdhEQaG6XmpAPAgQIECBAgAABAgQIECBAgAABAgQIFFRAoLmgFSfbBAgQIECAAAECBAgQIECAAAECBAgQaBcBgeZ2qQn5IECAAAECBAgQIECAAAECBAgQIECAQEEFBJoLWnH/r107OAEQCGAg6IH916xYg48NjOBXwkQ4DIpNgAABAgQIECBAgAABAgQIECBAgACBioChudKEHAQIECBAgAABAgQIECBAgAABAgQIEBgVMDSPFic2AQIECBAgQIAAAQIECBAgQIAAAQIEKgKG5koTchAgQIAAAQIECBAgQIAAAQIECBAgQGBUwNA8WpzYBAgQIECAAAECBAgQIECAAAECBAgQqAgYmitNyEGAAAECBAgQIECAAAECBAgQIECAAIFRAUPzaHFiEyBAgAABAgQIECBAgAABAgQIECBAoCJgaK40IQcBAgQIECBAgAABAgQIECBAgAABAgRGBQzNo8WJTYAAAQIECBAgQIAAAQIECBAgQIAAgYqAobnShBwECBAgQIAAAQIECBAgQIAAAQIECBAYFTA0jxYnNgECBAgQIECAAAECBAgQIECAAAECBCoChuZKE3IQIECAAAECBAgQIECAAAECBAgQIEBgVMDQPFqc2AQIECBAgAABAgQIECBAgAABAgQIEKgIGJorTchBgAABAgQIECBAgAABAgQIECBAgACBUQFD82hxYhMgQIAAAQIECBAgQIAAAQIECBAgQKAiYGiuNCEHAQIECBAgQIAAAQIECBAgQIAAAQIERgUMzaPFiU2AAAECBAgQIECAAAECBAgQIECAAIGKgKG50oQcBAgQIECAAAECBAgQIECAAAECBAgQGBUwNI8WJzYBAgQIECBAgAABAgQIECBAgAABAgQqAobmShNyECBAgAABAgQIECBAgAABAgQIECBAYFTA0DxanNgECBAgQIAAAQIECBAgQIAAAQIECBCoCBiaK03IQYAAAQIECBAgQIAAAQIECBAgQIAAgVEBQ/NocWITIECAAAECBAgQIECAAAECBAgQIECgImBorjQhBwECBAgQIECAAAECBAgQIECAAAECBEYFDM2jxYlNgAABAgQIECBAgAABAgQIECBAgACBioChudKEHAQIECBAgAABAgQIECBAgAABAgQIEBgVMDSPFic2AQIECBAgQIAAAQIECBAgQIAAAQIEKgKG5koTchAgQIAAAQIECBAgQIAAAQIECBAgQGBUwNA8WpzYBAgQIECAAAECBAgQIECAAAECBAgQqAgYmitNyEGAAAECBAgQIECAAAECBAgQIECAAIFRAUPzaHFiEyBAgAABAgQIECBAgAABAgQIECBAoCJgaK40IQcBAgQIECBAgAABAgQIECBAgAABAgRGBQzNo8WJTYAAAQIECBAgQIAAAQIECBAgQIAAgYqAobnShBwECBAgQIAAAQIECBAgQIAAAQIECBAYFTA0jxYnNgECBAgQIECAAAECBAgQIECAAAECBCoChuZKE3IQIECAAAECBAgQIECAAAECBAgQIEBgVMDQPFqc2AQIECBAgAABAgQIECBAgAABAgQIEKgIGJorTchBgAABAgQIECBAgAABAgQIECBAgACBUQFD82hxYhMgQIAAAQIECBAgQIAAAQIECBAgQKAiYGiuNCEHAQIECBAgQIAAAQIECBAgQIAAAQIERgUMzaPFiU2AAAECBAgQIECAAAECBAgQIECAAIGKgKG50oQcBAgQIECAAAECBAgQIECAAAECBAgQGBUwNI8WJzYBAgQIECBAgAABAgQIECBAgAABAgQqAncliBwEEgLnXOe9XQQIECBA4C8Bp8pfkp5DgAABAp+A7xUvAgECBAhEBfzRHC1GLAIECBAgQIAAAQIECBAgQIAAAQIECKwIGJpXmpKTAAECBAgQIECAAAECBAgQIECAAAECUQFDc7QYsQgQIECAAAECBAgQIECAAAECBAgQILAiYGheaUpOAgQIECBAgAABAgQIECBAgAABAgQIRAUMzdFixCJAgAABAgQIECBAgAABAgQIECBAgMCKgKF5pSk5CRAgQIAAAQIECBAgQIAAAQIECBAgEBUwNEeLEYsAAQIECBAgQIAAAQIECBAgQIAAAQIrAobmlabkJECAAAECBAgQIECAAAECBAgQIECAQFTA0BwtRiwCBAgQIECAAAECBAgQIECAAAECBAisCBiaV5qSkwABAgQIECBAgAABAgQIECBAgAABAlEBQ3O0GLEIECBAgAABAgQIECBAgAABAgQIECCwImBoXmlKTgIECBAgQIAAAQIECBAgQIAAAQIECEQFDM3RYsQiQIAAAQIECBAgQIAAAQIECBAgQIDAioCheaUpOQkQIECAAAECBAgQIECAAAECBAgQIBAVMDRHixGLAAECBAgQIECAAAECBAgQIECAAAECKwKG5pWm5CRAgAABAgQIECBAgAABAgQIECBAgEBUwNAcLUYsAgQIECBAgAABAgQIECBAgAABAgQIrAgYmleakpMAAQIECBAgQIAAAQIECBAgQIAAAQJRAUNztBixCBAgQIAAAQIECBAgQIAAAQIECBAgsCJgaF5pSk4CBAgQIECAAAECBAgQIECAAAECBAhEBQzN0WLEIkCAAAECBAgQIECAAAECBAgQIECAwIqAoXmlKTkJECBAgAABAgQIECBAgAABAgQIECAQFTA0R4sRiwABAgQIECBAgAABAgQIECBAgAABAisCDzZtpl7jqtbaAAAAAElFTkSuQmCC" + } + }, + { + "id": "Ca1VIXvxvHZBV-5b", + "title": "Text 2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "9. On the dropdown menu, you’ll see an option to “Link tiles,” where the XY Plot tile will be listed. Select that option, then click “Link.” Now you’ll be able to make a graph of your EMG readings!
" + ] + } + } + ], { - "id": "Mo17A3If3LtSFuUG", + "id": "IuCVTwe7xZh8SAHD", + "title": "Text 3", "content": { "type": "Text", "format": "html", - "text": ["5. Open the Backyard Brains Spike Recorder App on your computer. Click on the gear icon at the top left corner of the screen. Click on the 'Connect' button just below 'Select Port' (you may need to make the app window larger to view this option).
"] + "text": [ + "10. Now that you're set up, squeeze your hand or use the hand gripper!
" + ] } }, - {"id": "gy5LjOQMM03K1ezq", "title": "Setting up the SpikeRecoder App", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/filter.png", "filename": "curriculum/neural-engineering/images/filter.png"}}, { - "id": "BfEcsBHvG1mVwV4H", + "id": "b5KdlqtEIn67qC6R", + "title": "Text 4", "content": { "type": "Text", "format": "html", "text": [ - "The signals that you see on the screen reflect your muscle electrical activity. Change the time scale of your signal to ~1 second by scrolling up/down. You can also use the “+” and “-” buttons you to change the vertical scale.
", - "Hold the hand grip and squeeze it (or just make a fist) - how does the display change?"
" + "What is Electromyography (EMG)?
EMG is the recording and evaluation of electrical signals in the muscles. When you think about moving a muscle, your brain sends action potentials down the neurons in the spinal cord all the way to motor neurons deep inside of your muscles which causes your muscles to contract. When the muscles “contract” electrical activity is generated by muscle fibers which make up the greater muscle. These electrical signals, called electromyograms (spikes!) represent the combined electrical activity of muscles that are being recorded. In this next experiment, you will use EMG electrode pads and place them over different muscle groups and observe what happens.
" ] } }, - {"id": "nHcjmx6S8pJ4HydI", "title": "Backyard Brains App", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/12.png", "filename": "curriculum/neural-engineering/images/12.png"}}, { - "id": "7NWg1JOva6MjHeUC", + "id": "qFYzeJ0PFdaCnKM1", + "title": "Text 6", "content": { "type": "Text", "format": "html", "text": [ - "Now it is time to explore your EMG muscle activity. With your group, select 3 of the following research questions and answer them in your workspace. Make sure to include screenshots from the Spike Recorder App as evidence and describe what is shown in each image. (Screenshots can be copied and pasted into image or drawing tiles in your workspace.)
", - "Please document your observations in your Workspace." + "
EMG Experiment
Now it is time to explore your EMG muscle activity. With your group, select 3 of the following research questions and answer them in your workspace. Make sure to include all your graphs as evidence and describe what is shown in each image.
" ] } }, - {"id": "FXdgLMJooVFMO_Lq", "content": {"type": "Text", "format": "html", "text": ["Reflection
", "Please record your current thinking and learning in your Learning Journal (see Reflection tab).
"]}} + { + "id": "pMSzFO0DcqAIw80w", + "title": "Text 5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "How does muscle activity vary between one’s dominant vs. non-dominant hand?
How does muscle activity vary between different muscles (e.g., forearm vs. forehead muscles)?
What happens when we activate our hand muscles for an extended period of time using a hand gripper?
Can you predict who’s going to win an arm-wrestling contest based on the contestants’ muscle activity?
" + ] + } + } ] } } \ No newline at end of file diff --git a/curriculum/brain/teacher-guide/investigation-1/problem-1/overview/content.json b/curriculum/brain/teacher-guide/investigation-1/problem-1/overview/content.json index 3499810ab..46881b60f 100644 --- a/curriculum/brain/teacher-guide/investigation-1/problem-1/overview/content.json +++ b/curriculum/brain/teacher-guide/investigation-1/problem-1/overview/content.json @@ -3,20 +3,13 @@ "content": { "tiles": [ { - "id": "bfsShgpMoj8B6Kc0", + "id": "Ywd0NBtgCnQKBTmO", + "title": "Text 1", "content": { "type": "Text", "format": "html", "text": [ - "In this lesson, students will be introduced to emerging robotics technology that helps people with neurological conditions or missing limbs.
", - "Learning Objectives
", - "The goal of this lesson is to introduce the anchoring phenomenon of the unit and elicit student questions about bionic arms.
", - "NGSS Alignment
", - "See NGSS HS-LS1-2
", - "Formative assessment
", - "Listening to group conversations; reflecting on students’ questions; Learning Journals (found in student-facing CLUE tab for lesson 1.1).
", - "Materials
", - "Whiteboards and markers or chart paper (for each group of students)
" + "IMPORTANT: PLEASE COMPLETE LESSON 0 WITH YOUR STUDENTS BEFORE BEGINNING THIS MODULE!
In this lesson, students will be introduced to emerging robotics technology that helps people with neurological conditions or missing limbs.
Learning Objectives
The goal of this lesson is to introduce the anchoring phenomenon of the unit and elicit student questions about bionic arms.
NGSS Alignment
Formative assessment
Listening to group conversations; reflecting on students’ questions; Learning Journals (found in student-facing CLUE tab for lesson 1.1).
Materials
Whiteboards and markers or chart paper (for each group of students) (optional) Sticky notes and a poster board (for the driving questions board)
" ] } } diff --git a/curriculum/brain/teacher-guide/investigation-1/problem-4/overview/content.json b/curriculum/brain/teacher-guide/investigation-1/problem-4/overview/content.json index c70fa84c6..c1b430874 100644 --- a/curriculum/brain/teacher-guide/investigation-1/problem-4/overview/content.json +++ b/curriculum/brain/teacher-guide/investigation-1/problem-4/overview/content.json @@ -8,21 +8,7 @@ "type": "Text", "format": "html", "text": [ - "Students will use Electromyography (EMG) to investigate their own muscle activity.
", - "Learning Objectives
", - "Students will use computation to acquire, digitize, and make sense of muscle electrical activity (EMG).
", - "NGSS Alignment
", - "Under development
", - "Formative Assessment
", - "EMG and Learning Journals
", - "Materials
", - "For each group of 3-4 students:
", - "Preparation
", - "Before class you will need to install the Backyard Brains Spike Recorder App on student computers [https://backyardbrains.com/products/spikerecorder]
", - "Click here if your school uses Chromebooks
", - "You will also need to upload this Arduino sketch on each Arduino board.
", - "To do so, please create a free account on Arduino Cloud and install the Arduino Agent
" + "Students will use Electromyography (EMG) to investigate their own muscle activity.
Learning Objectives
Students will use computation to acquire, digitize, and make sense of muscle electrical activity (EMG).
NGSS Alignment
Under development
Formative Assessment
EMG and Learning Journals
Materials
For each group of 3-4 students:
NEW Instructional Sequence
", - "2 minutes
", - "Inform students that today’s lesson will help them begin to learn how the activity of muscles is identified and measured. This will help them explain how bionic arms work and work with a simple robotic arm.
", - "Consider noting students’ questions recorded in their learning journals, specifically questions related to the interactions between the nervous and muscular systems.
", - "15 minutes
", - "Assign students to teams composed of 3-4 classmates. Ask teams to follow the instructions in the student-facing lesson torecord and display EMG signals from their muscles
", - "10 minutes
", - "Teacher-led discussion on muscle contraction and EMG
", - "30 minutes
", - "Ask students to select 3 of the research questions listed in the student-facing lesson and answer them in their workspace using screenshots from SpikeRecorder as evidence. To answer the last question (arm-wrestling), students will need to work with another team since two EMG setups are required.
", - "- How does muscle activity vary between one’s dominant vs. non-dominant hand?
", - "- How does muscle activity vary between different muscles (e.g., forearm vs. forehead muscles)?
", - "- How does muscle activity vary between agonist and antagonist muscles?
", - "- What happens when we activate our hand muscles for an extended period of time using a hand gripper?
", - "- Can you predict who’s going to win an arm-wrestling contest based on the contestants’ muscle activity?
", - "Encourage students to develop other questions and explore them.
", - "15 minutes
", - "Facilitate a class discussion on questions such as:
", - "- Why does gathering EMG signals matter to you, your family, or others in the community?
", - "- Why does this matter to scientists, physicians, physical therapists, athletic trainers, and/or biomedical engineers?
", - "- How may gathering EMG data inform the design of a device that can help people with neurological conditions or missing limbs?
", - "10 minutes
", - "Ask students to post a reflection in their learning journals. Encourage students to apply what they noticed in the EMG activities, insights that were sparked by the discussion, and any new knowledge or wonderings they may have.
", - "Inform students that in the next activity they will apply and expand their knowledge of EMG and begin to explore the use of a simple robotic arm. This will help them explain how bionic arms work.
", - "NEW Instructional Sequence
2 minutes
Inform students that today’s lesson will help them begin to learn how the activity of muscles is identified and measured. This will help them explain how bionic arms work and work with a simple robotic arm.
Consider noting students’ questions recorded in their learning journals, specifically questions related to the interactions between the nervous and muscular systems.
15 minutes
Assign students to teams composed of 3-4 classmates. Ask teams to follow the instructions in the student-facing lesson to record and display EMG signals from their muscles. After all groups have completed steps 1-4, walk through how to link and unlink Dataflow and XY Plot tiles to record the data they want (this can be confusing for some). Refer to the instructional video if needed. Use the demo data for the EMG sensor if needed
10 minutes
Teacher-led discussion on muscle contraction and EMG
30 minutes
Ask students to select 3 of the research questions listed in the student-facing lesson and answer them in their workspace using Dataflow and XY Plot tiles as evidence. To answer the last question (arm-wrestling), students will need to work with another team since two EMG setups are required.
- How does muscle activity vary between one’s dominant vs. non-dominant hand?
- How does muscle activity vary between different muscles (e.g., forearm vs. forehead muscles)?
- How does muscle activity vary between agonist and antagonist muscles?
- What happens when we activate our hand muscles for an extended period of time using a hand gripper?
- Can you predict who’s going to win an arm-wrestling contest based on the contestants’ muscle activity?
Encourage students to develop other questions and explore them.
15 minutes
Facilitate a class discussion on questions such as:
- Why does gathering EMG signals matter to you, your family, or others in the community?
- Why does this matter to scientists, physicians, physical therapists, athletic trainers, and/or biomedical engineers?
- How may gathering EMG data inform the design of a device that can help people with neurological conditions or missing limbs?
10 minutes
Ask students to post a reflection in their learning journals. Encourage students to apply what they noticed in the EMG activities, insights that were sparked by the discussion, and any new knowledge or wonderings they may have.
Inform students that in the next activity, they will apply and expand their knowledge of EMG and begin to explore the use of a simple robotic arm. This will help them explain how bionic arms work.
Lesson Resources
" ] } }, - {"id": "kBJBbezdh9bxu6Dx", "title": "Arm Muscle Diagram", "content": {"type": "Image", "url": "curriculum/neural-engineering/images/armMuscles.png", "filename": "curriculum/neural-engineering/images/armMuscles.png"}}, - {"id": "3s1CMxSi6t3ADC8Z", "content": {"type": "Text", "format": "html", "text": ["https://dmr.bsu.edu/digital/collection/AnatMod/id/211
"]}} + { + "id": "kBJBbezdh9bxu6Dx", + "title": "Arm Muscle Diagram", + "content": { + "type": "Image", + "url": "brain/images/armMuscles.png", + "filename": "brain/images/armMuscles.png" + } + }, + { + "id": "3s1CMxSi6t3ADC8Z", + "content": { + "type": "Text", + "format": "html", + "text": [ + "https://dmr.bsu.edu/digital/collection/AnatMod/id/211
" + ] + } + } ] }, "supports": [] diff --git a/curriculum/hlit/investigation-1/problem-1/initialChallenge/content.json b/curriculum/hlit/investigation-1/problem-1/initialChallenge/content.json index 1a36c5616..2fd9b8f80 100644 --- a/curriculum/hlit/investigation-1/problem-1/initialChallenge/content.json +++ b/curriculum/hlit/investigation-1/problem-1/initialChallenge/content.json @@ -1 +1,19 @@ -{"type": "initialChallenge", "content": {"tiles": []}, "supports": []} \ No newline at end of file +{ + "type": "initialChallenge", + "content": { + "tiles": [ + { + "id": "cPE6HA_4dr6n3Ll3", + "title": "Text 5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Problem 1.1
Negotiating Screen Time: Tossing Coins and Cups to Find Probability
" + ] + } + } + ] + }, + "supports": [] +} \ No newline at end of file diff --git a/curriculum/hlit/investigation-1/problem-1/introduction/content.json b/curriculum/hlit/investigation-1/problem-1/introduction/content.json index 885b88878..3b0b43c36 100644 --- a/curriculum/hlit/investigation-1/problem-1/introduction/content.json +++ b/curriculum/hlit/investigation-1/problem-1/introduction/content.json @@ -1 +1,50 @@ -{"type": "introduction", "content": {"tiles": []}, "supports": []} \ No newline at end of file +{ + "type": "introduction", + "content": { + "tiles": [ + { + "id": "7x-DY6px9Xks1RAG", + "title": "Text 1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Investigation 1
A First Look at Chance
" + ] + } + }, + { + "id": "6e92HBa67zf8fxKK", + "title": "Text 2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Decisions, decisions, decisions—we make decisions every day. We choose what to wear, with whom to have lunch, what to do after school, and maybe what time to go to bed. To make some decisions, we consider the chance, or likelihood, that something will happen. We may listen to the weather forecast to decide whether you will wear a raincoat to school. In some cases, we may even let chance decide for us, such as when we roll a number cube to see who goes first in a game. A number cube shows the numbers 1, 2, 3, 4, 5, and 6 on its faces.
" + ] + } + }, + { + "id": "AuhGDpyvWk_SVza6", + "title": "Two number cubes", + "content": { + "type": "Image", + "url": "curriculum/how-likely-is-it/images/Inv_1_Intro.png", + "filename": "curriculum/how-likely-is-it/images/Inv_1_Intro.png" + } + }, + { + "id": "ZzxayrfajS8TCQq7", + "title": "Text 4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Think about these questions. They are examples of probability situations to help us consider the likelihood that a particular event will occur.
What are the chances of getting a 2 when we roll a number cube? Are we more likely to roll a 2 or a 6? How can we decide?
The weather forecaster says the chance of rain tomorrow is 40%. What does this mean? Should we wear a raincoat?
When we toss a coin, what are the chances of getting tails?
Suppose we toss a coin and get seven tails in a row. Are we more likely to get heads or tails on the next toss?
Tossing a coin one time is called an event.
The tossing a coin event has two possible results: either a head turns up or a tail turns up. The results are called outcomes.
" + ] + } + } + ] + }, + "supports": [] +} \ No newline at end of file diff --git a/curriculum/images/kids.jpeg b/curriculum/images/kids.jpeg new file mode 100644 index 000000000..5f8444b13 Binary files /dev/null and b/curriculum/images/kids.jpeg differ diff --git a/curriculum/m2s/images/dinosaur-fiesta.jpeg b/curriculum/m2s/images/dinosaur-fiesta.jpeg new file mode 100644 index 000000000..329fb7081 Binary files /dev/null and b/curriculum/m2s/images/dinosaur-fiesta.jpeg differ diff --git a/curriculum/m2s/images/screenshot-2023-07-12-at-2.13.04-pm.png b/curriculum/m2s/images/screenshot-2023-07-12-at-2.13.04-pm.png new file mode 100644 index 000000000..67afdf937 Binary files /dev/null and b/curriculum/m2s/images/screenshot-2023-07-12-at-2.13.04-pm.png differ diff --git a/curriculum/m2s/investigation-1/problem-1/help/content.json b/curriculum/m2s/investigation-1/problem-1/help/content.json index d7f0d5e8a..44c82b5bf 100644 --- a/curriculum/m2s/investigation-1/problem-1/help/content.json +++ b/curriculum/m2s/investigation-1/problem-1/help/content.json @@ -3,36 +3,23 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "Welcome to your work space! In here, you will find information and questions. You will work both individually and in groups, so be sure to listen to your teacher about what to do when.
", - "", - "
Some tips for this workspace:
", - "To the right, you can see 7 buttons. These will add tiles to your workspace:
", - "You can rearrange your spaces by clicking on the top right-hand corner of the tile (where you will see 6 dots). This will allow you drag and move the tiles.
", - "You can click on the bottom right corner of any tile and then drag it up or down to make it smaller or bigger.
", - "You can share your work with your group-mates by using the Share slider on the top right corner, or publish your work to the whole class by clicking the button with the up-arrow next to the File menu.
", - "You can also look at the work of your group-mates by clicking the Group View icon on the top bar (it looks like a window).
", - "", - "Are you ready? Let's go!
" + "Welcome to your work space! In here, you will find information and questions. You will work both individually and in groups, so be sure to listen to your teacher about what to do when.
Some tips for this workspace:
To the right, you can see 7 buttons. These will add tiles to your workspace:
You can rearrange your spaces by clicking on the top right-hand corner of the tile (where you will see 6 dots). This will allow you drag and move the tiles.
You can click on the bottom right corner of any tile and then drag it up or down to make it smaller or bigger.
You can share your work with your group-mates by using the Share slider on the top right corner, or publish your work to the whole class by clicking the button with the up-arrow next to the File menu.
You can also look at the work of your group-mates by clicking the Group View icon on the top bar (it looks like a window).
Are you ready? Let's go!
" ] } }, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Welcome to teacher solutions
", - "Some tips for this workspace:
", - "If your students are having trouble, consider putting some tips in a document of your own and publishing it with the uparrow button near the File menu. This will appear in Class Work and students can see the examples you post. They can publish too and the class can share ideas.
", - "All content from the left hand panels can be dragged into working documents on the right. Some curriculum pieces are intended to be dragged in as starting places for student work.
", - "", - "Are you ready? Let's go!
" + "Welcome to teacher solutions
Some tips for this workspace:
If your students are having trouble, consider putting some tips in a document of your own and publishing it with the uparrow button near the File menu. This will appear in Class Work and students can see the examples you post. They can publish too and the class can share ideas.
All content from the left hand panels can be dragged into working documents on the right. Some curriculum pieces are intended to be dragged in as starting places for student work.
Are you ready? Let's go!
" ] } } diff --git a/curriculum/m2s/investigation-1/problem-1/taska/content.json b/curriculum/m2s/investigation-1/problem-1/taska/content.json index 27a5a342f..ecc18e163 100644 --- a/curriculum/m2s/investigation-1/problem-1/taska/content.json +++ b/curriculum/m2s/investigation-1/problem-1/taska/content.json @@ -3,6 +3,7 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", @@ -12,40 +13,87 @@ } }, { + "id": "document_Text_2", "content": { "type": "Text", "format": "html", "text": [ - "Answer the questions below using the tiles in your workspace. Be sure to label each answer with the question number you are answering! You can also create additional tiles.
", - "", - "1. Describe your first task in your own words.
", - "", - "
2. What do you need to know about the school in order to complete your first task?
", - "a. List as many factors (key quantities and variables) as you can:
", - "b. Next to each factor, write where you can find out the information or what you would need to do to figure it out.
Examples:
- I need to know how many pets the students have. --> I will conduct a survey to collect this information.
", - "- I wonder how many books are at the library. --> Ask the librarian if they have this on record.
", - "c. Turn your factors into “variable chips” by clicking on the [v=] button in your text tile.
", - "", - "3. What assumptions can you make about the context or factors to help you complete this task?
", - "Hint: Use the [v=] and go to "Reference existing variable" to select the chips you created in Q2. If you come up with a new variable now, you can also turn it into a chip here.
", - "Example: By saying 'typical day', the school board likely means to consider only days that school is in session.
", - "Example: We probably only care about the [pets] owned by the students on the soccer team.
", - "", - "4. Share your variables/factors and assumptions with your group. Together, sort them to indicate how important you think they are to completing the task.
", - "Note: Your teacher may ask you to sort them in class, or ask you to arrange the orange boxes in your workspace.
", - "", - "
5. Select 2 of the factors and explain how/why they are important for helping you to complete the task.
", - "Hint: You can use the [v=] button to get a list and then select from 'Reference existing variable' to get you started!
", - "Example: We need to know the number of [pets] so that we buy enough [pet food].
", - "", - "6. Describe in words how some of these factors are related.
", - "Example: The more [pets] we have, the more [pet food] we need.
", - "", - "7. Use mathematical language or symbols to describe the relationship between those variables.
", - "Note: If you want to sketch the relationship, click on the pencil icon to create a drawing tile!
" + "Answer the questions below using the tiles in your workspace. Be sure to label each answer with the question number you are answering! You can also create additional tiles.
1. Describe your first task in your own words.
2. What do you need to know about the school in order to complete your first task?
a. List as many factors (key quantities and variables) as you can:
b. Next to each factor, write where you can find out the information or what you would need to do to figure it out. Examples:
- I need to know how many pets the students have. --> I will conduct a survey to collect this information.
- I wonder how many books are at the library. --> Ask the librarian if they have this on record.
c. Turn your factors into “variable chips” by clicking on the [v=] button in your text tile.
3. What assumptions can you make about the context or factors to help you complete this task?
Hint: Use the [v=] and go to "Reference existing variable" to select the chips you created in Q2. If you come up with a new variable now, you can also turn it into a chip here.
Example: By saying 'typical day', the school board likely means to consider only days that school is in session.
Example: We probably only care about the [pets] owned by the students on the soccer team.
4. Share your variables/factors and assumptions with your group. Together, sort them to indicate how important you think they are to completing the task.
Note: Your teacher may ask you to sort them in class, or ask you to arrange the orange boxes in your workspace.
5. Select 2 of the factors and explain how/why they are important for helping you to complete the task.
Hint: You can use the [v=] button to get a list and then select from 'Reference existing variable' to get you started!
Example: We need to know the number of [pets] so that we buy enough [pet food].
6. Describe in words how some of these factors are related.
Example: The more [pets] we have, the more [pet food] we need.
7. Use mathematical language or symbols to describe the relationship between those variables.
Note: If you want to sketch the relationship, click on the pencil icon to create a drawing tile!
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"]}}, { - "id": "60HTS9AMp3MffHdZ", + "title": "Text 7", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Alana, Gilberto, and Leanne were students in Ms. Chang’s class. They each did the walking experiment to find their walking rate.
" + ] + } + }, + { "title": "Table 1", "content": { "type": "Table", - "name": "Walking Rates for Ms. Chang's Class", - "columns": [{"name": "Name", "width": 80, "values": ["Alana", "Gilberto", "Leanne"]}, {"name": "Walking rate", "width": 214.08203125, "values": ["1 meter per second", "2 meters per second", "2.5 meters per second"]}] + "name": "Walking Rates for Ms. Chang's Class" + } + }, + { + "title": "Text 8", + "content": { + "type": "Text", + "format": "html", + "text": [ + "They had some questions about how their walking data is represented in a table, graph, or equation.
" + ] + } + }, + { + "title": "Text 9", + "content": { + "type": "Text", + "format": "html", + "text": [ + "They had some questions about how their walking data is represented in a table, graph, or equation.
"]}}, - {"id": "nkn0pzhsFP2Bz9ut", "title": "Text 9", "content": {"type": "Text", "format": "html", "text": ["Alana: d = t or d = 1t; Gilberto: d = 2t; Leanne: d = 2.5t.
" + ] + } + }, + { + "title": "Text 20", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Alana: d = t or d = 1t; Gilberto: d = 2t; Leanne: d = 2.5t.
"]}}, - {"id": "cdOLKAm2pwpkP5h1", "title": "Text 20", "content": {"type": "Text", "format": "html", "text": ["In the equation the walking rate is represented as the number that you multiply by the time to get distance. (Note that students will learn later that the multiplier is called the coefficient.)
", - "In the table, the walking rate is represented as the difference between values for distance in consecutive rows (1 second apart). So, as the x-values increase by 1, the y values will increase by the walking rate. (Note that students will learn later that this is called the rate of change.)
", - "In the graph, the walking rate is represented as the steepness of the graph – the greater the walking rate, the steeper the line on the graph. (Note that students will learn later that this is called the slope.)
" + "In the equation the walking rate is represented as the number that you multiply by the time to get distance. (Note that students will learn later that the multiplier is called the coefficient.)
In the table, the walking rate is represented as the difference between values for distance in consecutive rows (1 second apart). So, as the x-values increase by 1, the y values will increase by the walking rate. (Note that students will learn later that this is called the rate of change.)
In the graph, the walking rate is represented as the steepness of the graph – the greater the walking rate, the steeper the line on the graph. (Note that students will learn later that this is called the slope.)
" + ] + } + }, + { + "title": "Solutions for 3 Walking Rate Tables", + "content": { + "type": "Image", + "url": "curriculum/moving-straight-ahead/images/MSA_1-2_TimeDistance3groups.png" + } + }, + { + "title": "Text 24", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Answers will vary. Sample answers:
", - "The table is the most helpful because I can figure out the pattern, but I can also see many values that would answer questions.
", - "The graph is the most important because I can see the pattern for the walking rates. I can also see how the pattern of change for one line is related to the pattern of change for another. I can also find or approximate answers to questions.
", - "The equation is the most useful because I can use any amount of time to find the distance, not just small values for time like on a graph or table.
" + "Answers will vary. Sample answers:
The table is the most helpful because I can figure out the pattern, but I can also see many values that would answer questions.
The graph is the most important because I can see the pattern for the walking rates. I can also see how the pattern of change for one line is related to the pattern of change for another. I can also find or approximate answers to questions.
The equation is the most useful because I can use any amount of time to find the distance, not just small values for time like on a graph or table.
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", "For each of Yvonne's questions what answer would you give her?
"]}}, - {"id": "q1qfuwtzXFioGC99", "title": "Text 29", "content": {"type": "Text", "format": "html", "text": ["Question1
", "How can I tell from the table that the relationships between time and distance are proportional?
"]}}, - {"id": "dJp7G8r-vAsBPvfI", "display": "teacher", "title": "Text 33", "content": {"type": "Text", "format": "html", "text": ["The relationships are proportional. On the table, you can take any two coordinate pairs and write a proportion. For example on the table for Gilberto:
"]}}, + { + "id": "UQy4nhb_uZw9lPHh", + "title": "Text 28", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Situation A. Yvonne’s Claims
For each of Yvonne's questions what answer would you give her?
" + ] + } + }, + { + "id": "q1qfuwtzXFioGC99", + "title": "Text 29", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Question1
How can I tell from the table that the relationships between time and distance are proportional?
" + ] + } + }, + { + "id": "dJp7G8r-vAsBPvfI", + "title": "Text 33", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The relationships are proportional. On the table, you can take any two coordinate pairs and write a proportion. For example on the table for Gilberto:
" + ] + } + }, { "id": "HXZK3Np_pnEbn1Z1", - "display": "teacher", "title": "Table 3", - "content": {"type": "Table", "name": "Gilberto", "columns": [{"name": "Time (sec)", "width": 102.46875, "values": ["0", "1", "2", "3", "4", "5", "6"]}, {"name": "Distance (m)", "width": 145.9375, "values": ["0", "2", "4", "6", "8", "10", "12"]}]} + "content": { + "type": "Table", + "columnWidths": { + "POM4SyQLKAxBYyZq": 102.46875, + "ehjAR3E8RQxh1ITe": 145.9375 + }, + "name": "Gilberto" + } }, { "id": "XAB2gP9PmoC5WKV6", - "display": "teacher", "title": "Text 34", "content": { "type": "Text", "format": "html", "text": [ - "2 sec/ 3 sec = 4m/ 6m OR 2 sec/ 4m - 3 sec/ 6m
", - "Also, you can see this because any distance divided by time gives a constant ratio. Since the relationship is proportional, it is also linear because distance divided by time gives a constant rate of change.
", - "(Note: Not all linear relationships are proportional.)
" + "2 sec/ 3 sec = 4m/ 6m OR 2 sec/ 4m - 3 sec/ 6m
Also, you can see this because any distance divided by time gives a constant ratio. Since the relationship is proportional, it is also linear because distance divided by time gives a constant rate of change.
(Note: Not all linear relationships are proportional.)
" + ] + } + }, + { + "id": "Ljbb68m7mAUHVAN-", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Question 2
How can I use a table or graph to answer the question:
For each student, if time t increases by 1 second, by how much does the distance change?
" ] } }, - {"id": "Ljbb68m7mAUHVAN-", "content": {"type": "Text", "format": "html", "text": ["Question 2
", "How can I use a table or graph to answer the question:
", "For each student, if time t increases by 1 second, by how much does the distance change?
"]}}, { "id": "7KE3ajmLfA34lMbE", - "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "GRAPH
", - "If time increases by 1 second, she can find the change in distance on a graph by looking at the steepness of the line. Or, how much the y-variable changes (goes up or down) for every change of 1 in the x-variable.
", - "TABLE
", - "If time increases by 1 second, she can find the change in distance on a table by looking at the distance in two consecutive rows (one second apart) and calculating the difference.
" + "GRAPH
If time increases by 1 second, she can find the change in distance on a graph by looking at the steepness of the line. Or, how much the y-variable changes (goes up or down) for every change of 1 in the x-variable.
TABLE
If time increases by 1 second, she can find the change in distance on a table by looking at the distance in two consecutive rows (one second apart) and calculating the difference.
" + ] + } + }, + { + "id": "GiQUMHu-Wjc_-_uM", + "title": "Text 42", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Situation B. Valentina and Omar have the Same Walking Rate
Valentina and Omar have the same walking rate. Each made a graph to represent their data.
" ] } }, - {"id": "GiQUMHu-Wjc_-_uM", "title": "Text 42", "content": {"type": "Text", "format": "html", "text": ["Situation B. Valentina and Omar have the Same Walking Rate
", "Valentina and Omar have the same walking rate. Each made a graph to represent their data.
"]}}, { "id": "PwCZy2-WmFczZRpc", "title": "Omar's Walking Rate", "content": { "type": "Geometry", - "board": {"properties": {"axisMin": [-10, -16.25], "axisRange": [60, 100], "axisNames": ["t", "d"]}}, + "board": { + "properties": { + "axisMin": [ + -10, + -16.25 + ], + "axisRange": [ + 60, + 100 + ], + "axisNames": [ + "t", + "d" + ] + } + }, "objects": [ - {"type": "point", "parents": [0, 0], "properties": {"id": "EbBxFXPVI-BCC4Ng", "name": ""}}, - {"type": "point", "parents": [5, 10], "properties": {"id": "MKvaMqFTrLbYt_KC", "name": ""}}, - {"type": "point", "parents": [10, 20], "properties": {"id": "sn04YJgRO4UcroFY", "name": ""}}, - {"type": "point", "parents": [15, 30], "properties": {"id": "H5DpKBvCF80G_S3_", "name": ""}}, - {"type": "point", "parents": [20, 40], "properties": {"id": "nAN4zKeHiUddoQns", "name": ""}}, - {"type": "point", "parents": [25, 50], "properties": {"id": "qXFlXP0KGuWXPh5H", "name": ""}}, - {"type": "point", "parents": [30, 60], "properties": {"id": "ZDWIizg-DonRUgfZ", "name": ""}}, - {"type": "point", "parents": [35, 70], "properties": {"id": "wN70rNqnUo-r3VbZ", "name": ""}}, - {"type": "point", "parents": [40, 80], "properties": {"id": "UQ-3ui2QZfer9tXz", "name": ""}} + { + "type": "point", + "parents": [ + 0, + 0 + ], + "properties": { + "id": "EbBxFXPVI-BCC4Ng", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 5, + 10 + ], + "properties": { + "id": "MKvaMqFTrLbYt_KC", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 10, + 20 + ], + "properties": { + "id": "sn04YJgRO4UcroFY", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 15, + 30 + ], + "properties": { + "id": "H5DpKBvCF80G_S3_", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 20, + 40 + ], + "properties": { + "id": "nAN4zKeHiUddoQns", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 25, + 50 + ], + "properties": { + "id": "qXFlXP0KGuWXPh5H", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 30, + 60 + ], + "properties": { + "id": "ZDWIizg-DonRUgfZ", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 35, + 70 + ], + "properties": { + "id": "wN70rNqnUo-r3VbZ", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 40, + 80 + ], + "properties": { + "id": "UQ-3ui2QZfer9tXz", + "name": "" + } + } ] } }, @@ -65,70 +218,437 @@ "title": "Valentina’s Walking Rate", "content": { "type": "Geometry", - "board": {"properties": {"axisMin": [-1.917, -1.688], "axisRange": [11, 11], "axisNames": ["t", "d"]}}, + "board": { + "properties": { + "axisMin": [ + -1.917, + -1.688 + ], + "axisRange": [ + 11, + 11 + ], + "axisNames": [ + "t", + "d" + ] + } + }, "objects": [ - {"type": "point", "parents": [1, 2], "properties": {"id": "C9V3nsBtjMpGwLvn", "name": ""}}, - {"type": "point", "parents": [2, 4], "properties": {"id": "Qkcizf88T8BKzaKs", "name": ""}}, - {"type": "point", "parents": [3, 6], "properties": {"id": "Gz_yhdB4Ql3t6MtA", "name": ""}}, - {"type": "point", "parents": [4, 8], "properties": {"id": "9J7yBns4pKgaE28B", "name": ""}} + { + "type": "point", + "parents": [ + 1, + 2 + ], + "properties": { + "id": "C9V3nsBtjMpGwLvn", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 2, + 4 + ], + "properties": { + "id": "Qkcizf88T8BKzaKs", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 3, + 6 + ], + "properties": { + "id": "Gz_yhdB4Ql3t6MtA", + "name": "" + } + }, + { + "type": "point", + "parents": [ + 4, + 8 + ], + "properties": { + "id": "9J7yBns4pKgaE28B", + "name": "" + } + } + ] + } + }, + { + "id": "fEMYoiZYnepkTGOT", + "title": "Text 43", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Yes. They used different scales, so the graphs look different.
", - "", - "Valentina and Omar’s graphs are similar in that, when the points are connected, the graphs have the same rate of change and y-intercept. Omar graphed his walking rate for 40 seconds, whereas Valentina graphed his walking rate for 4 seconds. Omar uses intervals of 5 seconds and 10 meters, whereas Valentina uses intervals of 1 second and 1 meter. The different scales makes it appear that Valentina has a faster walking rate. However, their walking rates are the same. Because Omar’s vertical scale has twice the value as the horizontal scale, it appears to “pull down” the points as you have less vertical “movement” for every point. Valentina’s scales both have a value of one for every grid line. So, you will have the “same” movement on the horizontal and vertical axes for each coordinate pair.
" + "Yes. They used different scales, so the graphs look different.
Valentina and Omar’s graphs are similar in that, when the points are connected, the graphs have the same rate of change and y-intercept. Omar graphed his walking rate for 40 seconds, whereas Valentina graphed his walking rate for 4 seconds. Omar uses intervals of 5 seconds and 10 meters, whereas Valentina uses intervals of 1 second and 1 meter. The different scales makes it appear that Valentina has a faster walking rate. However, their walking rates are the same. Because Omar’s vertical scale has twice the value as the horizontal scale, it appears to “pull down” the points as you have less vertical “movement” for every point. Valentina’s scales both have a value of one for every grid line. So, you will have the “same” movement on the horizontal and vertical axes for each coordinate pair.
" + ] + } + }, + { + "id": "6NCjD3F0sBpDbY3X", + "title": "Text 47", + "content": { + "type": "Text", + "format": "html", + "text": [ + "5t
"]}}, - {"id": "vg3G-ujpicYZeMpQ", "content": {"type": "Text", "format": "html", "text": ["2t
"]}}, - {"id": "Kd0ivdglPfKURWcm", "content": {"type": "Text", "format": "html", "text": ["0.5t
"]}} + { + "id": "5Z_J43S2bFXEb5WR", + "title": "Text 48", + "content": { + "type": "Text", + "format": "html", + "text": [ + "5t
" + ] + } + }, + { + "id": "vg3G-ujpicYZeMpQ", + "content": { + "type": "Text", + "format": "html", + "text": [ + "2t
" + ] + } + }, + { + "id": "Kd0ivdglPfKURWcm", + "content": { + "type": "Text", + "format": "html", + "text": [ + "0.5t
" + ] + } + } ], { "id": "27yHk2EjW1IBL0iF", - "display": "teacher", "title": "Text 51", - "content": {"type": "Text", "format": "html", "text": ["The expression 2t could represent both of their distances. On both graphs, the distance traveled is always twice the time in seconds, so they are traveling 2 meters every second.
"]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "The expression 2t could represent both of their distances. On both graphs, the distance traveled is always twice the time in seconds, so they are traveling 2 meters every second.
" + ] + } }, { "id": "s3HBHlnSDS1x7IaM", "title": "Text 52", - "content": {"type": "Text", "format": "html", "text": ["Situation C. More Walking Rates
", "Five other friends made the following representations of their Walkathon data. Could any of these relationships be linear relationships? Explain.
"]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "Situation C. More Walking Rates
Five other friends made the following representations of their Walkathon data. Could any of these relationships be linear relationships? Explain.
" + ] + } }, [ - {"id": "e7PUjYkCd0aQbK8Q", "title": "Table 4", "content": {"type": "Table", "name": "George's Walkathon", "columns": [{"name": "Time (sec)", "width": 93.0078125, "values": [0, 1, 2, 3, 4, 5]}, {"name": "Dist (m)", "width": 80.8046875, "values": [0, 2, 9, 11, 20, 25]}]}}, - {"id": "PBPual7wzV94aNVA", "content": {"type": "Table", "name": "Elizabeth's Walkathon", "columns": [{"name": "Time (sec)", "width": 90.66015625, "values": [0, 2, 4, 6, 8, 10]}, {"name": "Dist (m)", "width": 80, "values": [0, 3, 6, 9, 12, 15]}]}} + { + "id": "e7PUjYkCd0aQbK8Q", + "title": "Table 4", + "content": { + "type": "Table", + "columnWidths": { + "Axb83HryiTJTfitU": 93.0078125, + "kW8XsGGjvxvZjhmy": 80.8046875 + }, + "name": "George's Walkathon" + } + }, + { + "id": "PBPual7wzV94aNVA", + "content": { + "type": "Table", + "columnWidths": { + "acFiot747Ds9P6W_": 90.66015625, + "BGVpqeN7zm-UAprj": 80 + }, + "name": "Elizabeth's Walkathon" + } + } ], [ - {"id": "ZJQwx5qTjiZbZzhH", "title": "Evo's Walk- a Thon", "content": {"type": "Image", "url": "curriculum/moving-straight-ahead/images/MSA_1_2_Evos_Graph.jpg"}}, - {"id": "q9LbDkd_vsZBRTfu", "title": "Text 54", "content": {"type": "Text", "format": "html", "text": ["Billie's Walk-a Thon
", "D = 2.25t
", "", "D represents distance
", "t represents time
", ""]}}, - {"id": "23Iv3lcNaAXHoUFd", "title": "Text 56", "content": {"type": "Text", "format": "html", "text": ["Bob’s Walkathon
", "= 100/r
", "t represents time
", "r represents walking rate
"]}} + { + "id": "ZJQwx5qTjiZbZzhH", + "title": "Evo's Walk- a Thon", + "content": { + "type": "Image", + "url": "msa/images/MSA_1_2_Evos_Graph.jpg" + } + }, + { + "id": "q9LbDkd_vsZBRTfu", + "title": "Text 54", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Billie's Walk-a Thon
D = 2.25t
D represents distance
t represents time
" + ] + } + }, + { + "id": "23Iv3lcNaAXHoUFd", + "title": "Text 56", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Bob’s Walkathon
= 100/r
t represents time
r represents walking rate
" + ] + } + } ], { "id": "dlxv49xticu_qjeJ", - "display": "teacher", "title": "Text 58", "content": { "type": "Text", "format": "html", "text": [ - "Elizabeth and Billie’s relationships are linear and proportional.
", - "Elizabeth walks at a constant rate of 3 meters every 2 seconds, which you can see in the table. Billie walks at a constant rate of 2.25 m/s, since the equation is in the form of d = rt, similar to the equations for Alana, Gilberto, and Leanne. Both of these relationships are also proportional, since at 0 seconds they have walked 0 meters.
", - "George’s, Evo’s, and Bob’s relationships are not linear. The table for George does not show a constant rate of change. Evo’s graph does not make a straight line, so it does not show a constant rate of change. In the equation for Bob, the rate is a variable, so the walking rate is not constant. (Some students may make graphs and claim the relationships are either linear or not based on whether the data lie on a straight line.)
" + "Elizabeth and Billie’s relationships are linear and proportional.
Elizabeth walks at a constant rate of 3 meters every 2 seconds, which you can see in the table. Billie walks at a constant rate of 2.25 m/s, since the equation is in the form of d = rt, similar to the equations for Alana, Gilberto, and Leanne. Both of these relationships are also proportional, since at 0 seconds they have walked 0 meters.
George’s, Evo’s, and Bob’s relationships are not linear. The table for George does not show a constant rate of change. Evo’s graph does not make a straight line, so it does not show a constant rate of change. In the equation for Bob, the rate is a variable, so the walking rate is not constant. (Some students may make graphs and claim the relationships are either linear or not based on whether the data lie on a straight line.)
" ] } } + ], + "sharedModels": [ + { + "sharedModel": { + "type": "SharedDataSet", + "id": "McSIb3yTQjRIV24j", + "providerId": "HXZK3Np_pnEbn1Z1", + "dataSet": { + "id": "-y2gLU-pkdv3HUVV", + "name": "Gilberto", + "attributes": [ + { + "id": "POM4SyQLKAxBYyZq", + "clientKey": "", + "name": "Time (sec)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + "0", + "1", + "2", + "3", + "4", + "5", + "6" + ] + }, + { + "id": "ehjAR3E8RQxh1ITe", + "clientKey": "", + "name": "Distance (m)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + "0", + "2", + "4", + "6", + "8", + "10", + "12" + ] + } + ], + "cases": [ + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7K" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7M" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7N" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7P" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7Q" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7R" + }, + { + "__id__": "01GWQ6NBJYM9DNT072DTS8QX7S" + } + ] + } + }, + "tiles": [ + "HXZK3Np_pnEbn1Z1" + ] + }, + { + "sharedModel": { + "type": "SharedDataSet", + "id": "T2OXjP3bM4dYO-cj", + "providerId": "e7PUjYkCd0aQbK8Q", + "dataSet": { + "id": "000sehwyGpEP19lz", + "name": "George's Walkathon", + "attributes": [ + { + "id": "Axb83HryiTJTfitU", + "clientKey": "", + "name": "Time (sec)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + 0, + 1, + 2, + 3, + 4, + 5 + ] + }, + { + "id": "kW8XsGGjvxvZjhmy", + "clientKey": "", + "name": "Dist (m)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + 0, + 2, + 9, + 11, + 20, + 25 + ] + } + ], + "cases": [ + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ3" + }, + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ4" + }, + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ5" + }, + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ6" + }, + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ7" + }, + { + "__id__": "01GWQ6NBK5WWG35CCQFEQC5BJ8" + } + ] + } + }, + "tiles": [ + "e7PUjYkCd0aQbK8Q" + ] + }, + { + "sharedModel": { + "type": "SharedDataSet", + "id": "pgSQECQSmDSaclUa", + "providerId": "PBPual7wzV94aNVA", + "dataSet": { + "id": "GAgm15_U4U2Rp04u", + "name": "Elizabeth's Walkathon", + "attributes": [ + { + "id": "acFiot747Ds9P6W_", + "clientKey": "", + "name": "Time (sec)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + 0, + 2, + 4, + 6, + 8, + 10 + ] + }, + { + "id": "BGVpqeN7zm-UAprj", + "clientKey": "", + "name": "Dist (m)", + "hidden": false, + "units": "", + "formula": {}, + "values": [ + 0, + 3, + 6, + 9, + 12, + 15 + ] + } + ], + "cases": [ + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GT8" + }, + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GT9" + }, + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GTA" + }, + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GTB" + }, + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GTC" + }, + { + "__id__": "01GWQ6NBK6ZJ08Z3YBD2QR7GTD" + } + ] + } + }, + "tiles": [ + "PBPual7wzV94aNVA" + ] + } ] } } \ No newline at end of file diff --git a/curriculum/msa/investigation-1/problem-3/introduction/content.json b/curriculum/msa/investigation-1/problem-3/introduction/content.json index d828e5e41..d1f2e3cde 100644 --- a/curriculum/msa/investigation-1/problem-3/introduction/content.json +++ b/curriculum/msa/investigation-1/problem-3/introduction/content.json @@ -8,7 +8,9 @@ "content": { "type": "Text", "format": "html", - "text": ["In Problems 1.1 and 1.2, the distance walked depended on the time. This tells us that distance is the dependent variable and time is the independent variable. In this Problem, we will look at relationships between two other variables in a walkathon.
"] + "text": [ + "In Problems 1.1 and 1.2, the distance walked depended on the time. This tells us that distance is the dependent variable and time is the independent variable. In this Problem, we will look at relationships between two other variables in a walkathon.
" + ] } }, { diff --git a/curriculum/sad/investigation-1/problem-1/initialChallenge/content.json b/curriculum/sad/investigation-1/problem-1/initialChallenge/content.json index 1a36c5616..c67a40ddf 100644 --- a/curriculum/sad/investigation-1/problem-1/initialChallenge/content.json +++ b/curriculum/sad/investigation-1/problem-1/initialChallenge/content.json @@ -1 +1,7 @@ -{"type": "initialChallenge", "content": {"tiles": []}, "supports": []} \ No newline at end of file +{ + "type": "initialChallenge", + "content": { + "tiles": [] + }, + "supports": [] +} \ No newline at end of file diff --git a/curriculum/sad/investigation-1/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sad/investigation-1/problem-1/nowWhatDoYouKnow/content.json index 82b421db3..73c589397 100644 --- a/curriculum/sad/investigation-1/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sad/investigation-1/problem-1/nowWhatDoYouKnow/content.json @@ -1 +1,6 @@ -{"type": "nowWhatDoYouKnow", "content": {"tiles": [], "supports": []}} \ No newline at end of file +{ + "type": "nowWhatDoYouKnow", + "content": { + "tiles": [] + } +} \ No newline at end of file diff --git a/curriculum/sad/investigation-1/problem-1/whatIf/content.json b/curriculum/sad/investigation-1/problem-1/whatIf/content.json index 6d0b4c3ed..cf19f5658 100644 --- a/curriculum/sad/investigation-1/problem-1/whatIf/content.json +++ b/curriculum/sad/investigation-1/problem-1/whatIf/content.json @@ -1 +1,6 @@ -{"type": "whatIf", "content": {"tiles": [], "supports": []}} \ No newline at end of file +{ + "type": "whatIf", + "content": { + "tiles": [] + } +} \ No newline at end of file diff --git a/curriculum/sad/investigation-1/problem-2/initialChallenge/content.json b/curriculum/sad/investigation-1/problem-2/initialChallenge/content.json index 1a36c5616..c67a40ddf 100644 --- a/curriculum/sad/investigation-1/problem-2/initialChallenge/content.json +++ b/curriculum/sad/investigation-1/problem-2/initialChallenge/content.json @@ -1 +1,7 @@ -{"type": "initialChallenge", "content": {"tiles": []}, "supports": []} \ No newline at end of file +{ + "type": "initialChallenge", + "content": { + "tiles": [] + }, + "supports": [] +} \ No newline at end of file diff --git a/curriculum/sas/investigation-0/problem-1/initialChallenge/content.json b/curriculum/sas/investigation-0/problem-1/initialChallenge/content.json index 16ba3f638..28d0611d5 100644 --- a/curriculum/sas/investigation-0/problem-1/initialChallenge/content.json +++ b/curriculum/sas/investigation-0/problem-1/initialChallenge/content.json @@ -4,105 +4,108 @@ "tiles": [ [ { - "id": "IubDD3qrjJw8Uhb9", + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "Using CLUE’s Tools
", - "", - "It’s time to try out each of CLUE’s tools. You’ll decide which tools to use to solve a problem. Knowing how the tools work will help you present your mathematical answers in a way that makes sense to you, whether that’s in words or a graph or table. To use a tool, just click it. You can then move it to a particular section or above or below another tile. Or to position it precisely, drag it from the toolbar into your workspace, moving to where you want it (the drop zone is indicated by a blue vertical bar), then let go.
" + "Using CLUE’s Tools
It's time to try out each of CLUE’s tools. You’ll decide which tools to use to solve a problem. Knowing how the tools work will help you present your mathematical answers in a way that makes sense to you, whether that’s in words or a graph or table. To use a tool, just click it. You can then move it to a particular section or above or below another tile. Or to position it precisely, drag it from the toolbar into your workspace, moving to where you want it (the drop zone is indicated by a blue vertical bar), then let go.
" ] } }, - {"id": "_acGcUoGuBg5sXvL", "title": "Tool Tiles on the CLUE Toolbar", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/AllToolsToolBar-labeled.png"}} + { + "id": "document_Image_1", + "title": "Tool Tiles on the CLUE Toolbar", + "content": { + "type": "Image", + "url": "sas/images/AllToolsToolBar-labeled.png" + } + } ], [ { - "id": "jVu0lyX6VmWRgOhY", - "layout": {"height": 120}, + "id": "document_Text_2", "content": { "type": "Text", "format": "html", - "text": ["Text
", "When you click into a text tile in your workspace, a tray with icons for editing options appears below it. Hover your mouse over the items in the tray for more information (and a keyboard shortcut) about each.
", ""] + "text": [ + "Text
When you click into a text tile in your workspace, a tray with icons for editing options appears below it. Hover your mouse over the items in the tray for more information (and a keyboard shortcut) about each.
" + ] } }, - {"id": "kKGmMgSxgJId6zJW", "title": "Text controls", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/TextTray.png"}} + { + "id": "document_Image_2", + "title": "Text controls", + "content": { + "type": "Image", + "url": "sas/images/TextTray.png" + } + } ], [ { - "id": "I8j7wDtsSN4g6NYH", + "id": "document_Text_3", "content": { "type": "Text", "format": "html", "text": [ - "The text tool is like many other editors, but some options may work slightly differently.
", - "The text tool is like many other editors, but some options may work slightly differently.
Drag this tile into the Initial Challenge section in your workspace, and format the text below as described.
", - "", - "Bold
", - "Italic
", - "Underline
", - "Subscript
", - "Superscript
", - "", - "This is a
", - "Numbered
", - "List
", - "", - "This is a
", - "Bulleted
", - "List
" + "Drag this tile into the Initial Challenge section in your workspace, and format the text below as described.
Bold
Italic
Underline
Subscript
Superscript
This is a
Numbered
List
This is a
Bulleted
List
" ] } } ], { - "id": "T7Nf4eiuSzITUz7L", + "id": "document_Text_5", "content": { "type": "Text", "format": "html", "text": [ - "A few more things about text tiles:
", - "When text is selected, you can use the usual keyboard shortcuts:
", - "A few more things about text tiles:
When text is selected, you can use the usual keyboard shortcuts:
Table
", - "", - "Use a table to relate two or more quantities. Tables can hold numbers or text. You can edit the table title or column labels by double-clicking. You can move from cell to cell with the tab key. Below are some example tables. Drag each one into the Initial Challenge section and make the suggested edits.
" + "Table
Use a table to relate two or more quantities. Tables can hold numbers or text. You can edit the table title or column labels by double-clicking. You can move from cell to cell with the tab key. Below are some example tables. Drag each one into the Initial Challenge section and make the suggested edits.
" ] } }, [ { - "id": "a_B3E01X00sg3_kO", + "id": "document_Text_7", "content": { "type": "Text", "format": "html", - "text": ["Explore the table functions. See if you can add another column and label it Height (ft.), then fill the column with heights. You can make up the numbers (or research them, if you want). Also, add another dinosaur or two and fill out the columns with numbers.
"] + "text": [ + "Explore the table functions. See if you can add another column and label it Height (ft.), then fill the column with heights. You can make up the numbers (or research them, if you want). Also, add another dinosaur or two and fill out the columns with numbers.
" + ] } }, - {"id": "-ZoJoDESMoYPKL7H", "content": {"type": "Table", "name": "Dinosaur Characteristics", "columns": [{"name": "Dinosaur", "values": ["Velociraptor", "Coelophysis", "Triceratops", "Allosaurus"]}, {"name": "Length (ft.)", "values": ["6.5", "10", "26", "32"]}]}} + { + "id": "document_Table_1", + "content": { + "type": "Table", + "columnWidths": {}, + "name": "Table 1" + } + } ], { - "id": "FMm-bEHPbtoLSJd2", + "id": "document_Text_8", "content": { "type": "Text", "format": "html", @@ -111,112 +114,203 @@ ] } }, - {"id": "JU_PfL7clLhi5YKm", "content": {"type": "Table", "name": "Connections Between Points", "columns": [{"name": "Points", "values": ["1", "2", "3", "4", "5"]}, {"name": "Connections", "values": ["0", "1", "3", "6", "10"]}]}}, - {"id": "1O2b0WS9ShaqbaHv", "content": {"type": "Text", "format": "html", "text": ["Tables have other features that we’ll explore later in this activity.
"]}}, + { + "id": "document_Table_2", + "content": { + "type": "Table", + "columnWidths": {}, + "name": "Table 2" + } + }, + { + "id": "document_Text_9", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Tables have other features that we’ll explore later in this activity.
" + ] + } + }, [ { - "id": "bsVBeX_vC7orGn2k", + "id": "document_Text_10", "content": { "type": "Text", "format": "html", - "text": ["Graph
", "The Graph tool allows you to work with both geometrical figures and number relationships on a graph. Many features are available from the graph tray that appears when a graph tile is selected.
"] + "text": [ + "Graph
The Graph tool allows you to work with both geometrical figures and number relationships on a graph. Many features are available from the graph tray that appears when a graph tile is selected.
" + ] } }, - {"id": "8l7oyYGXkc9uVEps", "title": "Graph controls", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/GraphTrayLabled.png"}} + { + "id": "document_Image_3", + "title": "Graph controls", + "content": { + "type": "Image", + "url": "sas/images/GraphTrayLabled.png" + } + } ], { - "id": "ig4n6NXWNFIqgugW", + "id": "document_Text_11", "content": { "type": "Text", "format": "html", "text": [ - "Try out the geometrical features by dragging the Graph tile below into the Initial Challenge workspace. Drag this text tile in, too, and close out this panel (with the “X”) so you have more room to work. When you are done, click on My Resources and come back to the Initial Challenge.
", - "", - "Try out the geometrical features by dragging the Graph tile below into the Initial Challenge workspace. Drag this text tile in, too, and close out this panel (with the “X”) so you have more room to work. When you are done, click on My Resources and come back to the Initial Challenge.
You can try out the remaining features and some tricks with the Graph tool later in this activity.
", ""]}} + { + "id": "document_Text_12", + "content": { + "type": "Text", + "format": "html", + "text": [ + "You can try out the remaining features and some tricks with the Graph tool later in this activity.
" + ] + } + } ], { - "id": "V8HfULbj8W5hEh1x", + "id": "document_Text_13", "content": { "type": "Text", "format": "html", "text": [ - "Image
", - "", - "Use the image tool to add a picture or snapshot to your work. For example, you might want to do some of your work with a pencil and paper. You can take a picture of it with the computer’s camera or a cell phone camera and upload it to your workspace. Then, all your work is together and your teacher can easily see it.
" + "Image
Use the image tool to add a picture or snapshot to your work. For example, you might want to do some of your work with a pencil and paper. You can take a picture of it with the computer’s camera or a cell phone camera and upload it to your workspace. Then, all your work is together and your teacher can easily see it.
" ] } }, - {"id": "ldQbqn6TNXqeGSnU", "title": "Snapshot of physical work loaded in CLUE", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/ImageTool-StudentWork_450w.png"}}, { - "id": "MADDxE2jZiDIptpg", + "id": "document_Image_4", + "title": "Snapshot of physical work loaded in CLUE", + "content": { + "type": "Image", + "url": "sas/images/ImageTool-StudentWork_450w.png" + } + }, + { + "id": "document_Text_14", "content": { "type": "Text", "format": "html", "text": [ - "You can upload an image three ways: (1) Drag an image (JPG, PNG) from your computer directly into your workspace, (2) Drag and drop an image into a new image tool, or (3) Use the Upload Image option below the image tool to upload the file.
", - "", - "Of course, you can always drag an image from a problem into your workspace.
" + "You can upload an image three ways: (1) Drag an image (JPG, PNG) from your computer directly into your workspace, (2) Drag and drop an image into a new image tool, or (3) Use the Upload Image option below the image tool to upload the file.
Of course, you can always drag an image from a problem into your workspace.
" ] } }, - {"id": "SbbKDh_4RIFGF5Ig", "content": {"type": "Text", "format": "html", "text": ["Draw
", "This simple draw tool can help you explain your answers when nothing else will. Drag a new Draw tool into the Initial Challenge workspace, and try it out.
"]}}, - {"id": "gOJ6rVNNfONMKs3K", "title": "Drawing controls", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/DrawTrayLabeled_450w.png"}}, { - "id": "UmuJ2eGSIGvOpkwy", + "id": "document_Text_15", "content": { "type": "Text", "format": "html", "text": [ - "There are several features in the Draw tray.
", - "Note: In some activities, the Draw tool has an extra feature called Stamp with small icons you can use to solve the questions for that problem.
" + "Draw
This simple draw tool can help you explain your answers when nothing else will. Drag a new Draw tool into the Initial Challenge workspace, and try it out.
" ] } }, { - "id": "9WCoe166uaNJlt_1", + "id": "document_Image_5", + "title": "Drawing controls", + "content": { + "type": "Image", + "url": "sas/images/DrawTrayLabeled_450w.png" + } + }, + { + "id": "document_Text_16", "content": { "type": "Text", "format": "html", "text": [ - "Using the Table and Graph Tool Together
", - "", - "The Table and Graph tools can be linked together. Try this:
", - "There are several features in the Draw tray.
Note: In some activities, the Draw tool has an extra feature called Stamp with small icons you can use to solve the questions for that problem.
" ] } }, { - "id": "xW3a8ImrCr37XGef", + "id": "document_Text_17", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Using the Table and Graph Tool Together
The Table and Graph tools can be linked together. Try this:
Once you can see a dog, what can you do with it? Try selecting the whole figure and then different elements of it--points and lines. Then test the different tools in the graph tray. For instance,
", - "", - "See if you can unlink the graph. What happens?
" + "Once you can see a dog, what can you do with it? Try selecting the whole figure and then different elements of it--points and lines. Then test the different tools in the graph tray. For instance,
See if you can unlink the graph. What happens?
" ] } }, { - "id": "Zl70Im62cFEh239k", + "id": "document_Text_20", "content": { "type": "Text", "format": "html", "text": [ - "Uploading an Image to a Graph
", - "", - "The Graph tool can measure the lengths of line segments using the Segment Label feature. It also can be used to make measurements on images that can be uploaded to the graph. Start a new graph in the Initial Challenge section and find an image on your computer that you’d like to share. You can make points and shapes on top of the image. Is there anything in the image that you can measure? Add a label with a measurement.
" + "Uploading an Image to a Graph
The Graph tool can measure the lengths of line segments using the Segment Label feature. It also can be used to make measurements on images that can be uploaded to the graph. Start a new graph in the Initial Challenge section and find an image on your computer that you’d like to share. You can make points and shapes on top of the image. Is there anything in the image that you can measure? Add a label with a measurement.
" ] } } + ], + "sharedModels": [ + { + "sharedModel": { + "type": "SharedDataSet", + "id": "-doSGSv9zrRGl1_k", + "providerId": "document_Table_1", + "dataSet": { + "id": "5IZamq8mFu-sUyu6", + "name": "Table 1", + "attributes": [], + "cases": [] + } + }, + "tiles": [ + "document_Table_1" + ] + }, + { + "sharedModel": { + "type": "SharedDataSet", + "id": "cr7RMM0fGGn0uLrR", + "providerId": "document_Table_2", + "dataSet": { + "id": "LJ94WaA-kB607ru1", + "name": "Table 2", + "attributes": [], + "cases": [] + } + }, + "tiles": [ + "document_Table_2" + ] + }, + { + "sharedModel": { + "type": "SharedDataSet", + "id": "t-PXmqWHl5eS3uhe", + "providerId": "document_Table_3", + "dataSet": { + "id": "QYaTIGyQGB20lMiF", + "name": "Table 3", + "attributes": [], + "cases": [] + } + }, + "tiles": [ + "document_Table_3" + ] + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-0/problem-1/introduction/content.json b/curriculum/sas/investigation-0/problem-1/introduction/content.json index 2b20f139d..49aed9485 100644 --- a/curriculum/sas/investigation-0/problem-1/introduction/content.json +++ b/curriculum/sas/investigation-0/problem-1/introduction/content.json @@ -4,34 +4,40 @@ "tiles": [ { "id": "y5zjsg_GUnvZhNqs", - "content": {"type": "Text", "format": "html", "text": ["Welcome to CLUE!
", "CLUE is short for Collaborative Learning User Environment.
", "It has been designed to help you do math together with your classmates.
"]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "Welcome to CLUE!
CLUE is short for Collaborative Learning User Environment.
It has been designed to help you do math together with your classmates.
" + ] + } + }, + { + "id": "0JPeZra2cygU7GLQ", + "title": "Collaborative Classroom", + "content": { + "type": "Image", + "url": "sas/images/inscriptions3_450w.png" + } }, - {"id": "0JPeZra2cygU7GLQ", "title": "Collaborative Classroom", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/inscriptions3_450w.png"}}, { "id": "D7AsUAaGeFf_Ie6y", "content": { "type": "Text", "format": "html", "text": [ - "", - "", - "In CLUE, everyone works in a group with up to four people. When you start an activity, CLUE drops you into a group randomly. You can change groups by clicking on the group number in the upper right corner. Then, you can either join an existing group that has fewer than four students, or start a new group. Your teacher may ask you to join a specific group. When you change groups, your work moves with you.
", - "Groups are important in CLUE. You can learn from classmates in your group and they can learn from you. Many features of CLUE are designed to help you share information and learn from others in your group and in your class.
", - "" + "In CLUE, everyone works in a group with up to four people. When you start an activity, CLUE drops you into a group randomly. You can change groups by clicking on the group number in the upper right corner. Then, you can either join an existing group that has fewer than four students, or start a new group. Your teacher may ask you to join a specific group. When you change groups, your work moves with you.
Groups are important in CLUE. You can learn from classmates in your group and they can learn from you. Many features of CLUE are designed to help you share information and learn from others in your group and in your class.
" ] } }, { + "id": "document_Text_1", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "This activity is designed to acquaint your students with the features of the CLUE platform. In the first two sections — Introduction and Initial Challenge — students get a chance to try out the features of their individual workspaces and the tools that are available for solving problems. The latter two sections — What If…? and Now What Do you Know? — present the collaboration tools, so students learn how to share their work with their group members and with the class.
", - "", - "To get the most out of this activity or any activity, seat students in groups of four, if possible, and have these students work in the same group. As students work, encourage them to share their questions and their findings and help each other. At the end, you may want to use student-published work to pull together the major discoveries that students have made about the CLUE platform.
", - "", - "Finally, CLUE has been developed for use with the Chrome browser, and we recommend using it. With other browsers, certain functions may work differently than described here.
" + "This activity is designed to acquaint your students with the features of the CLUE platform. In the first two sections — Introduction and Initial Challenge — students get a chance to try out the features of their individual workspaces and the tools that are available for solving problems. The latter two sections — What If…? and Now What Do you Know? — present the collaboration tools, so students learn how to share their work with their group members and with the class.
To get the most out of this activity or any activity, seat students in groups of four, if possible, and have these students work in the same group. As students work, encourage them to share their questions and their findings and help each other. At the end, you may want to use student-published work to pull together the major discoveries that students have made about the CLUE platform.
Finally, CLUE has been developed for use with the Chrome browser, and we recommend using it. With other browsers, certain functions may work differently than described here.
" ] } }, @@ -41,10 +47,7 @@ "type": "Text", "format": "html", "text": [ - "Each problem has three or four parts. The tabs above display each part. Try clicking on the tabs listed below, then click back to the Introduction.
", - "(Note: Not all lessons have an Introduction.)
" + "Each problem has three or four parts. The tabs above display each part. Try clicking on the tabs listed below, then click back to the Introduction.
(Note: Not all lessons have an Introduction.)
" ] } }, @@ -54,11 +57,7 @@ "type": "Text", "format": "html", "text": [ - "Problems are made of little chunks called tiles that contain the following:
", - "Try hovering your mouse over the text or other features. You’ll see a gray box around each “tile.”
" + "Problems are made of little chunks called tiles that contain the following:
Try hovering your mouse over the text or other features. You’ll see a gray box around each “tile.”
" ] } }, @@ -68,9 +67,7 @@ "type": "Text", "format": "html", "text": [ - "On the right is your workspace. To edit your workspace, you must first add a tile. You get a tile in your workspace by either
", - "All tiles have a waffle (gray box with six dots) in the upper right corner if you hover over it. To drag the tile, click the waffle and hold it down as you drag it to your workspace. As you drag the tile into the workspace, a blue line shows where the tile will go when you let go.
" + "On the right is your workspace. To edit your workspace, you must first add a tile. You get a tile in your workspace by either
All tiles have a waffle (gray box with six dots) in the upper right corner if you hover over it. To drag the tile, click the waffle and hold it down as you drag it to your workspace. As you drag the tile into the workspace, a blue line shows where the tile will go when you let go.
" ] } }, @@ -79,7 +76,9 @@ "content": { "type": "Text", "format": "html", - "text": ["Your workspace has dividers for each section of the problem. Put your answers in the same section as that of the question. For instance, drag the tile below into the Introduction section and try writing your own haiku below it.
"] + "text": [ + "Your workspace has dividers for each section of the problem. Put your answers in the same section as that of the question. For instance, drag the tile below into the Introduction section and try writing your own haiku below it.
" + ] } }, { @@ -88,13 +87,7 @@ "type": "Text", "format": "html", "text": [ - "Here is an example haiku:
", - "", - "Answers, thoughtfully
", - "Arranged, enlighten ideas,
", - "Adding clarity.
", - "", - "(The usual haiku has three lines, a total of 17 syllables with lines of 5, 7, and 5 syllables.)
" + "Here is an example haiku:
Answers, thoughtfully
Arranged, enlighten ideas,
Adding clarity.
(The usual haiku has three lines, a total of 17 syllables with lines of 5, 7, and 5 syllables.)
" ] } }, @@ -118,13 +111,22 @@ ] } }, - {"id": "85R9h791ebdw1NbA", "title": "Open and close Workspace and esources views", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/WholeScreen-400w.png"}}, + { + "id": "85R9h791ebdw1NbA", + "title": "Open and close Workspace and esources views", + "content": { + "type": "Image", + "url": "sas/images/WholeScreen-400w.png" + } + }, { "id": "fQmDj6IwaKzYdwhP", "content": { "type": "Text", "format": "html", - "text": ["When your working session is over, just close the browser window. Your workspace is saved automatically. (There is no Save button.) If you are on a shared computer, be sure to log out of the STEM Resource Finder. Now, click the Initial Challenge tab to continue.
"] + "text": [ + "When your working session is over, just close the browser window. Your workspace is saved automatically. (There is no Save button.) If you are on a shared computer, be sure to log out of the STEM Resource Finder. Now, click the Initial Challenge tab to continue.
" + ] } } ] diff --git a/curriculum/sas/investigation-0/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-0/problem-1/nowWhatDoYouKnow/content.json index 5e42a9e8a..b10354635 100644 --- a/curriculum/sas/investigation-0/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-0/problem-1/nowWhatDoYouKnow/content.json @@ -3,14 +3,13 @@ "content": { "tiles": [ { + "id": "document_Text_1", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "This section shows students how they can use their past work or published class work to synthesize their learning. Students can access published work, either from other students or from you, and incorporate them into their documents.
", - "", - "Editing and updating the Learning Log is a particularly powerful way for students to reflect on their learning. Learning Log files are visible in each problem of the Unit. Encourage students to take notes on the Unit content and incorporate it into their Learning Logs.
" + "This section shows students how they can use their past work or published class work to synthesize their learning. Students can access published work, either from other students or from you, and incorporate them into their documents.
Editing and updating the Learning Log is a particularly powerful way for students to reflect on their learning. Learning Log files are visible in each problem of the Unit. Encourage students to take notes on the Unit content and incorporate it into their Learning Logs.
" ] } }, @@ -20,9 +19,7 @@ "type": "Text", "format": "html", "text": [ - "Accessing Class and Personal Documents
", - "So far, you have been only using the Problem tab on the left side of the screen. Now try using the three remaining tabs to access saved personal documents or class documents while editing another document on the right side of the screen. Explore the tabs to find a document and click the icon of the document. It will appear on the left. If you have a document on the right, you can drag tiles into it just as you would from the Problems tab. The files are sorted by the tabs:
", - "Accessing Class and Personal Documents
So far, you have been only using the Problem tab on the left side of the screen. Now try using the three remaining tabs to access saved personal documents or class documents while editing another document on the right side of the screen. Explore the tabs to find a document and click the icon of the document. It will appear on the left. If you have a document on the right, you can drag tiles into it just as you would from the Problems tab. The files are sorted by the tabs:
Under My Work and Class Work, you also have access to sub-tabs:
", - "Under My Work and Class Work, you also have access to sub-tabs:
Sharing Work in Your Group
", - "CLUE is designed so that you can learn with others in your group and in your class. Discussing and sharing your work is an important part of the learning process.
", - "", - "Sharing your work with your group is controlled with the button and slider switch in the upper right corner of your workspace. The button on the left toggles your workspace view from your individual view to a group view. In the group view, your work is always in the upper left corner. You can see the initials of your group members in each window pane.
" + "Sharing Work in Your Group
CLUE is designed so that you can learn with others in your group and in your class. Discussing and sharing your work is an important part of the learning process.
Sharing your work with your group is controlled with the button and slider switch in the upper right corner of your workspace. The button on the left toggles your workspace view from your individual view to a group view. In the group view, your work is always in the upper left corner. You can see the initials of your group members in each window pane.
" ] } }, { + "id": "document_Text_1", "display": "teacher", "content": { "type": "Text", @@ -28,20 +26,22 @@ [ { "id": "xNSvm1tfNTblOYgf", - "layout": {"height": 250}, "content": { "type": "Text", "format": "html", "text": [ - "The Share slider makes your work visible to your group members.
", - "", - "Your group members cannot change your work and you can’t change theirs. However, you can drag tiles from your group members’ workspaces and they can drag tiles from your workspace.
", - "Switch to group view and turn on sharing. Ask your group members to do the same. You can zoom into each window by placing your cursor at the center of the four windows, and dragging the window panes to see more detail.
", - "" + "The Share slider makes your work visible to your group members.
Your group members cannot change your work and you can’t change theirs. However, you can drag tiles from your group members’ workspaces and they can drag tiles from your workspace.
Switch to group view and turn on sharing. Ask your group members to do the same. You can zoom into each window by placing your cursor at the center of the four windows, and dragging the window panes to see more detail.
" ] } }, - {"id": "9xpInLKuRpI_mMhg", "title": "Group Sharing controls", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/GroupSharingControls.png"}} + { + "id": "9xpInLKuRpI_mMhg", + "title": "Group Sharing controls", + "content": { + "type": "Image", + "url": "sas/images/GroupSharingControls.png" + } + } ], { "id": "P1hcXvW95DxVMbMF", @@ -49,11 +49,7 @@ "type": "Text", "format": "html", "text": [ - "Look at your group members’ work in the Introduction. Did they write a haiku? In the Initial Challenge did they do something fun with the dog graph?
", - "", - "If you like something from your group members’ work, copy it by dragging your neighbor’s tile and placing it in your What if...? Section, for example. Then you can edit it and expand on it. Your neighbor may want to copy it back after your changes.
", - "", - "Why is this useful when doing math? Imagine that you’re working on a problem and your neighbor finds a different way to solve it. You can trade your solutions. Or, maybe you are stuck on how to start a problem. Perhaps your neighbors can help you get going.
" + "Look at your group members’ work in the Introduction. Did they write a haiku? In the Initial Challenge did they do something fun with the dog graph?
If you like something from your group members’ work, copy it by dragging your neighbor’s tile and placing it in your What if...? Section, for example. Then you can edit it and expand on it. Your neighbor may want to copy it back after your changes.
Why is this useful when doing math? Imagine that you’re working on a problem and your neighbor finds a different way to solve it. You can trade your solutions. Or, maybe you are stuck on how to start a problem. Perhaps your neighbors can help you get going.
" ] } }, @@ -64,14 +60,18 @@ "type": "Text", "format": "html", "text": [ - "Publishing
", - "", - "To share your work with others in your class, publish it by clicking the button at the top left of your workspace. Others can find the published documents by clicking the Class Work tab. You may update your work by publishing it again. Only the most recent version is visible to your class.
", - "" + "Publishing
To share your work with others in your class, publish it by clicking the button at the top left of your workspace. Others can find the published documents by clicking the Class Work tab. You may update your work by publishing it again. Only the most recent version is visible to your class.
" ] } }, - {"id": "07QJRxughLLyUbJf", "title": "Publishing in CLUE", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/PublishFileIcons-Labled.png"}} + { + "id": "07QJRxughLLyUbJf", + "title": "Publishing in CLUE", + "content": { + "type": "Image", + "url": "sas/images/PublishFileIcons-Labled.png" + } + } ], { "id": "k3Nnn7IHqtKk_dmT", @@ -79,13 +79,10 @@ "type": "Text", "format": "html", "text": [ - "Create or Edit Files
", - "To create new files for your personal use or to edit existing files, use the File dropdown menu. You might create files to try something out or take notes. Below are the things you can do. Try them out.
", - "Create or Edit Files
To create new files for your personal use or to edit existing files, use the File dropdown menu. You might create files to try something out or take notes. Below are the things you can do. Try them out.
One of Daphne’s photos looks like the picture below. Daphne has a copy of the P.I. Monthly magazine shown in the picture. The P.I. Monthly magazine is 10 inches high. She thinks the photo might be helpful in determining the height of the mystery teacher.
" + ] + } + }, + { + "id": "20AUG20220932", + "title": "Daphne’s photo of the mystery teacher by a magazine rack", + "content": { + "type": "Image", + "url": "sas/images/SS_1_1_06_magazine_rack_500w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] } }, - {"id": "20AUG20220932", "title": "Daphne’s photo of the mystery teacher by a magazine rack", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_1_06_magazine_rack_500w.png"}}, - {"content": {"type": "Text", "format": "markdown", "text": ["* Is Daphne's claim correct? Is it possible to use the magazine and the picture to estimate the teacher's height? Explain."]}}, { + "id": "document_Text_3", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Daphne’s claim is correct. In her picture, we can measure both the height of the P.I. magazine and the height of the teacher and then compare two values. Knowing the P.I. magazine is 10 inches high in real life, you can estimate the teacher’s real height.
", - "Possible student strategies:
", - "Daphne’s claim is correct. In her picture, we can measure both the height of the P.I. magazine and the height of the teacher and then compare two values. Knowing the P.I. magazine is 10 inches high in real life, you can estimate the teacher’s real height.
Possible student strategies:
Answers will vary. Possible answers:
", - "Students will think about the proportional relationship of heights between the picture and the reality.
" + "Answers will vary. Possible answers:
Students will think about the proportional relationship of heights between the picture and the reality.
" ] } } diff --git a/curriculum/sas/investigation-1/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-1/problem-1/nowWhatDoYouKnow/content.json index ce8201ca9..49f0dffce 100644 --- a/curriculum/sas/investigation-1/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-1/problem-1/nowWhatDoYouKnow/content.json @@ -2,20 +2,35 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["The Mystery Club advisor says that the picture is similar to the actual scene. What do you suppose the advisor means by similar? How is the photo similar to the actual scene that is photographed?"]}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The Mystery Club advisor says that the picture is similar to the actual scene. What do you suppose the advisor means by similar? How is the photo similar to the actual scene that is photographed?
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "By similar, the advisor might mean that the figures in the picture look the same as the original shapes in the actual scene, except in size. The photo represents the actual scene in real life in a smaller version.
", - "As the introduction to the Unit, students might have general rather than mathematically specific answers. Students should begin to informally recognize that proportional relationships between quantities can be used to estimate the relationships between the lengths.
" + "By similar, the advisor might mean that the figures in the picture look the same as the original shapes in the actual scene, except in size. The photo represents the actual scene in real life in a smaller version.
As the introduction to the Unit, students might have general rather than mathematically specific answers. Students should begin to informally recognize that proportional relationships between quantities can be used to estimate the relationships between the lengths.
" ] } }, - {"id": "20AUG20220933", "title": "Did You Know?: Measurement in police work", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_1_NW_07_did_you_know_350w.png"}} - ], - "supports": [] + { + "id": "20AUG20220933", + "title": "Did You Know?: Measurement in police work", + "content": { + "type": "Image", + "url": "sas/images/SS_1_1_NW_07_did_you_know_350w.png" + } + } + ] } } \ No newline at end of file diff --git a/curriculum/sas/investigation-1/problem-2/initialChallenge/content.json b/curriculum/sas/investigation-1/problem-2/initialChallenge/content.json index ea20afe94..6dfbcc0ba 100644 --- a/curriculum/sas/investigation-1/problem-2/initialChallenge/content.json +++ b/curriculum/sas/investigation-1/problem-2/initialChallenge/content.json @@ -3,71 +3,114 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Michelle, Daphne, and Mukesh are officers of the Mystery Club. Mukesh designs a flier to attract new members.", - "Daphne is making a large poster to publicize the next meeting. She wants to redraw the club’s logo, “Super Sleuth,” in a larger size. Michelle shows her a clever way to enlarge the figure by using rubber bands." + "" ] } }, - {"id": "20AUG20220935", "title": "Mystery club flier", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_2_In_08_flyer_350w.png"}}, - {"content": {"type": "Text", "format": "markdown", "text": ["## Equipment", "* Rubber bands – identical size, bands about 3 inches long work well", "* Learning Aid – with a shape to enlarge and anchor point", "* Blank paper", "* Tape"]}}, { + "id": "20AUG20220935", + "title": "Mystery club flier", + "content": { + "type": "Image", + "url": "sas/images/SS_1_2_In_08_flyer_350w.png" + } + }, + { + "id": "document_Text_2", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Instructions for Stretching a Figure", - "* Make a “two-band stretcher” by tying the ends of the rubber bands together.", - "* Tape the Learning Aid to your desk. Next to it, tape a blank sheet of paper. ", - "If you are right-handed, put the blank paper on the right.", - " If you are left-handed, put the blank paper on the left. " + "" ] } }, - {"id": "20AUG20220935123", "title": "Left-handed and right-handed setup for using a rubber band stretcher", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_2_rubberbands.jpg"}}, { + "id": "document_Text_3", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Instructions for Stretching a Figure", - "* With your finger, hold down one end of the rubber-band stretcher on point P. Point P is called the anchor point.", - "* Put a pencil in the other hand of the stretcher. Stretch the rubber bands with the pencil until the knot is on the outline of the shape.", - "* Keep the rubber bands taut (stretched). Move your pencil to guide the knot around the picture. Your pencil will draw a copy of the shape. The new picture is called the image of the original. It is also a scale drawing of the original." + "" + ] + } + }, + { + "id": "20AUG20220935123", + "title": "Left-handed and right-handed setup for using a rubber band stretcher", + "content": { + "type": "Image", + "url": "sas/images/SS_1_2_rubberbands.jpg" + } + }, + { + "id": "document_Text_4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" ] } }, - {"content": {"type": "Text", "format": "markdown", "text": ["* Use the rubber-band method to enlarge the figure on the Mystery Club flier. Draw the figure as carefully as you can, so you can compare the size and shape of the image to the size and shape of the original figure."]}}, { - "display": "teacher", "id": "V_gWTG15Nz1BmRtV", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Note: Students will experience different levels of success using the rubber band to enlarge the shape. Have fun with it. The messy shapes motivate the need for more precise stretching and shrinking strategies that students will experience in the next few problems.
Technique Notes: It is important to keep the rubber band as close to the paper as possible. And, watch the knot, not your pencil.
" + ] + } + }, + { + "id": "document_Text_6", "content": { "type": "Text", "format": "html", "text": [ - "Note: Students will experience different levels of success using the rubber band to enlarge the shape. Have fun with it. The messy shapes motivate the need for more precise stretching and shrinking strategies that students will experience in the next few problems.
", - "Technique Notes: It is important to keep the rubber band as close to the paper as possible. And, watch the knot, not your pencil.
" + "" ] } }, - {"content": {"type": "Text", "format": "markdown", "text": ["* How are the original figure and its image alike? Different? What is your evidence?"]}}, { + "id": "document_Text_7", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Students may compare the general shapes of two figures, the lengths of line segments in the hats and bodies, the areas or the perimeters of the hats and bodies, the angles in the hats and bodies, or the distance of corresponding points on each figure from the anchor point P. Because the tool does provide exact replicas, the answers will be estimates at this time.
", - "Note that the answers above are true in the ideal case. In practice, the 2 to 1 ratio of the lengths (and the 4 to 1 ratio of the areas) will not always be observed. This is because of the imperfection of the bands and some differences in the application of the method. More precise methods will be explored in next Problems.
", - "The rubber band stretcher results are more accurate if the end of the rubber band on point P is fixed by holding a pin instead of holding by hand directly; if the image end of the band is held as close to the page as possible using the pencil; if the pencil chosen is as thin as possible since its thickness might cause the band in the image end to be shorter than it is supposed to be; if the bands are not stretched too much.
" + "Students may compare the general shapes of two figures, the lengths of line segments in the hats and bodies, the areas or the perimeters of the hats and bodies, the angles in the hats and bodies, or the distance of corresponding points on each figure from the anchor point P. Because the tool does provide exact replicas, the answers will be estimates at this time.
Note that the answers above are true in the ideal case. In practice, the 2 to 1 ratio of the lengths (and the 4 to 1 ratio of the areas) will not always be observed. This is because of the imperfection of the bands and some differences in the application of the method. More precise methods will be explored in next Problems.
The rubber band stretcher results are more accurate if the end of the rubber band on point P is fixed by holding a pin instead of holding by hand directly; if the image end of the band is held as close to the page as possible using the pencil; if the pencil chosen is as thin as possible since its thickness might cause the band in the image end to be shorter than it is supposed to be; if the bands are not stretched too much.
" ] } } ] }, - "supports": [{"text": "How do the lengths of line segments compare between the two figures?"}, {"text": "How do the areas of the two figures compare?"}, {"text": "How do the angles of the two figures compare?"}] + "supports": [ + { + "text": "How do the lengths of line segments compare between the two figures?" + }, + { + "text": "How do the areas of the two figures compare?" + }, + { + "text": "How do the angles of the two figures compare?" + } + ] } \ No newline at end of file diff --git a/curriculum/sas/investigation-1/problem-2/whatIf/content.json b/curriculum/sas/investigation-1/problem-2/whatIf/content.json index c51189b7f..9047fd56d 100644 --- a/curriculum/sas/investigation-1/problem-2/whatIf/content.json +++ b/curriculum/sas/investigation-1/problem-2/whatIf/content.json @@ -3,34 +3,59 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "### Situation A. Making Comparisons", - "Ms. Marvel’s class made several comparison statements about the original figure and the image.", - "Merve’s Comparison: The lengths of the sides of the image are twice the lengths of the original.", - "Ashley’s Comparison: The distance from a point on the original figure to anchor point P is equal to the distance from the image of the point to P. ", - "Eli’s Comparison: The measure of an angle in the original figure has the same measure as the image of the angle.", - "Soro’s Comparison: The area of the hat of the original figure is about ¼ the area of the hat of image.", - "* Which of these statements are true? Explain your reasoning.", - "* Which of these statements represent ratios? Write these as ratio statements.", - "* Use your rubber band stretcher to enlarge another figure, such as a circle or square. Which of the comparisons are true for the original figure and its image?" + "" ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "markdown", "text": ["* Any of these are ratios, see examples below:", "* The same comparisons would be true for the original figure and its image."]}}, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", - "text": ["Merve’s Comparison is true. We can place copies of the original lengths on the image to see this relationship. The ratio of original to image would be x to 2x. For every measurement in the original, the image is twice the size.
"] + "text": [ + "" + ] } }, - {"display": "teacher", "id": "20AUG20220936", "title": "Sample diagram for Merve’s comparison", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_If_Situation_A_1.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Any of the comparisons could be re-written as ratios. Examples include:
", "Merve’s Comparison: The comparison of the lengths on the image to the original is 2 to 1
"]}}, { + "id": "document_Text_3", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Merve’s Comparison is true. We can place copies of the original lengths on the image to see this relationship. The ratio of original to image would be x to 2x. For every measurement in the original, the image is twice the size.
" + ] + } + }, + { + "id": "20AUG20220936", + "title": "Sample diagram for Merve’s comparison", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/1-2_What_If_Situation_A_1.png" + } + }, + { + "id": "document_Text_4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Any of the comparisons could be re-written as ratios. Examples include:
Merve’s Comparison: The comparison of the lengths on the image to the original is 2 to 1
" + ] + } + }, + { + "id": "document_Text_5", "display": "teacher", "content": { "type": "Text", @@ -40,8 +65,17 @@ ] } }, - {"display": "teacher", "id": "20AUG20220937", "title": "Sample diagram for Ashley’s comparison", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_If_Situation_A_2.png"}}, { + "id": "20AUG20220937", + "title": "Sample diagram for Ashley’s comparison", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/1-2_What_If_Situation_A_2.png" + } + }, + { + "id": "document_Text_6", "display": "teacher", "content": { "type": "Text", @@ -51,62 +85,169 @@ ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Eli's Comparison is true. We can place copies of the original angles on the image to see this relationship. The angle ratios from the original to the image will always be 1 to 1.
"]}}, - {"display": "teacher", "id": "20AUG20220938", "title": "Sample diagram for Eli’s comparison", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_If_Situation_A_3.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Eli's Comparison: The measure of the angles have a 1 to 1 relationship. For every 90˚ on the original, there will be 90˚ on the corresponding angle of the image.
", "Comparison 4 is true.
"]}}, - {"display": "teacher", "id": "20AUG20220940", "title": "Sample diagram for Soro’s comparison", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_If_Situation_A_4.png"}}, { + "id": "document_Text_7", "display": "teacher", - "content": {"type": "Text", "format": "html", "text": ["About 4 of the original hats fit inside the image hat. So, the original hat is about 1/4 the area of the image.", "Soro's Comparison: The area of the hat of the original figure to the area of the hat of image is 1 to 4. "]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "Eli's Comparison is true. We can place copies of the original angles on the image to see this relationship. The angle ratios from the original to the image will always be 1 to 1.
" + ] + } }, { + "id": "20AUG20220938", + "title": "Sample diagram for Eli’s comparison", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/1-2_What_If_Situation_A_3.png" + } + }, + { + "id": "document_Text_8", + "display": "teacher", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "### Situation B. Changing the Anchor Point and Number of Bands", - "Several students had questions about the anchor point and the number of rubber bands. What is your response to each question?", - "DaShawn’s Question: What if we change the position of the anchor point? How does this affect the image?", - "Sunyoung’s Question: What if we use three rubber bands? We would still trace the figure using the knot closest to the anchor point. How will this affect the image? ", - "Amy’s Question: The rubber bands seem to be acting like multipliers. Since there is a multiplying effect, we can use ratios. How can I use ratio language to describe what happens to corresponding side lengths?" + "Eli's Comparison: The measure of the angles have a 1 to 1 relationship. For every 90˚ on the original, there will be 90˚ on the corresponding angle of the image.
Comparison 4 is true.
" ] } }, { + "id": "20AUG20220940", + "title": "Sample diagram for Soro’s comparison", "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/1-2_What_If_Situation_A_4.png" + } + }, + { + "id": "document_Text_9", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "About 4 of the original hats fit inside the image hat. So, the original hat is about 1/4 the area of the image.Soro's Comparison: The area of the hat of the original figure to the area of the hat of image is 1 to 4.
" + ] + } + }, + { + "id": "document_Text_10", "content": { "type": "Text", "format": "html", "text": [ - "If the location of P is changed, the location of the image will also change. However, the location of P does not affect the size or shape of the image.
", - "For example, the darker blue triangle below is the original. Moving the location of P moves the image (lighter blue triangle). It does not change the shape or size. The length of the distances away from P remain proportional. If we look at corresponding right angles, on the image the right angle is always twice the distance from P while the right angle on the original is always one distance away from P.
" + "" ] } }, - {"display": "teacher", "id": "20AUG202209399", "title": "Results of moving the anchor point for a rubber band stretcher", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_if_Situation_B.png"}}, { + "id": "document_Text_11", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Note that there are two possible interpretations of Sunyoung’s question. Most students will use the knot closer to the anchor point to trace the original figure. Some students may use the knot closer to the pencil.
", - "Answers for the knots closer to the anchor point:
", - "If the location of P is changed, the location of the image will also change. However, the location of P does not affect the size or shape of the image.
For example, the darker blue triangle below is the original. Moving the location of P moves the image (lighter blue triangle). It does not change the shape or size. The length of the distances away from P remain proportional. If we look at corresponding right angles, on the image the right angle is always twice the distance from P while the right angle on the original is always one distance away from P.
" ] } }, - {"display": "teacher", "id": "20AUG202209349", "title": "Side lengths for similar figures from a three rubber band stretcher (knot closer to anchor point)", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-2_What_If_Situation_B_Sunyoungs_Question_1.png"}}, { + "id": "20AUG202209399", + "title": "Results of moving the anchor point for a rubber band stretcher", "display": "teacher", - "content": {"type": "Text", "format": "html", "text": ["Note that there are two possible interpretations of Sunyoung’s question. Most students will use the knot closer to the anchor point to trace the original figure. Some students may use the knot closer to the pencil.
Answers for the knots closer to the anchor point:
In Amy's Question, if the distances of each figure from the anchor point P have a 2 to 1 ratio, like the 2 rubber band stretcher, then the side length of the image figure is 2 times the side length of the original figure.
", - "Using three rubber bands the ratio of the side length in figure 1 to the side length of corresponding side length in the image is 1 to 3 or 1 : 3.
" + "In Amy's Question, if the distances of each figure from the anchor point P have a 2 to 1 ratio, like the 2 rubber band stretcher, then the side length of the image figure is 2 times the side length of the original figure.
Using three rubber bands the ratio of the side length in figure 1 to the side length of corresponding side length in the image is 1 to 3 or 1 : 3.
" ] } } diff --git a/curriculum/sas/investigation-1/problem-3/initialChallenge/content.json b/curriculum/sas/investigation-1/problem-3/initialChallenge/content.json index ce1935abf..989593a76 100644 --- a/curriculum/sas/investigation-1/problem-3/initialChallenge/content.json +++ b/curriculum/sas/investigation-1/problem-3/initialChallenge/content.json @@ -3,46 +3,92 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", - "text": ["Daphne thinks the rubber-band method is clever, but she believes the school copier can make more accurate copies in a greater variety of sizes. She makes a copy of “Super Sleuth” with two different percent size factors. The results are shown below."] + "text": [ + "Daphne thinks the rubber-band method is clever, but she believes the school copier can make more accurate copies in a greater variety of sizes. She makes a copy of “Super Sleuth” with two different percent size factors. The results are shown below.
" + ] + } + }, + { + "id": "21AUG20220852340AM", + "title": "Copies of Super Sleuth with different percent size factors.", + "content": { + "type": "Image", + "url": "sas/images/copiesOfSuperSleuth1_3.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_3", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "For Copy 2, if we compare corresponding sides such as the base of the triangle, 1 and ½ lengths of the original make the corresponding length of the copy. This means that the multiplier is 1.5 or 150% of the original.
" + ] } }, - {"id": "21AUG20220852340AM", "title": "Copies of Super Sleuth with different percent size factors.", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/copiesOfSuperSleuth1_3.png"}}, - {"content": {"type": "Text", "format": "markdown", "text": ["* What percent size multiplier did Daphne use to create Copy 1 and Copy 2? Explain your reasoning."]}}, { + "id": "21AUsfafG20220850AM", + "title": "Comparing side lengths for Super Sleuth and Copy 2", "display": "teacher", - "content": {"type": "Text", "format": "html", "text": ["For Copy 2, if we compare corresponding sides such as the base of the triangle, 1 and ½ lengths of the original make the corresponding length of the copy. This means that the multiplier is 1.5 or 150% of the original.
"]} + "content": { + "type": "Image", + "url": "sas/images/comparingSideLengths1_3.png" + } }, - {"display": "teacher", "id": "21AUsfafG20220850AM", "title": "Comparing side lengths for Super Sleuth and Copy 2", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/comparingSideLengths1_3.png"}}, { + "id": "document_Text_4", "display": "teacher", - "content": {"type": "Text", "format": "html", "text": ["For Copy 1, if we compare corresponding sides such as the base of the triangle, ¾ of the length of the original makes the corresponding length of the copy. This means that the multiplier is 0.75 or 75% of the original.
"]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "For Copy 1, if we compare corresponding sides such as the base of the triangle, ¾ of the length of the original makes the corresponding length of the copy. This means that the multiplier is 0.75 or 75% of the original.
" + ] + } }, - {"display": "teacher", "id": "21AUasG2022adsf0850AM", "title": "Comparing side lengths for Super Sleuth and Copy 1", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/1-3_Initial_Challenge_2.png"}}, - {"content": {"type": "Text", "format": "markdown", "text": ["* How are the copies like the original? How are they different?"]}}, { + "id": "21AUasG2022adsf0850AM", + "title": "Comparing side lengths for Super Sleuth and Copy 1", "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/1-3_Initial_Challenge_2.png" + } + }, + { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { "id": "_7HJi5zFt89fPzIp", "title": "Text 1", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Possible answers
", - "Stays the same/alike:
", - "Size changes:
", - "Corresponding side lengths change:
", - "Perimeter changes in the same way the corresponding side lengths change. This can be explained by the Distributive Property: For example, in Copy 2 the sides of the hat change b6 150%, so the perimeter will also change by 150%: 1.5l+1.5l+1.5w+1.5w=1.5(l+l+w+w)
", - "Area changes:
", - "Note: At this time in the Unit, students will make general statements about the area. Such as, “The area grows (or shrinks) but not in the same way as the lengths.” The area change relationship in scale figures will be developed in Investigations 2 and 3.
", - "Ratios change:
", - "Possible answers
Stays the same/alike:
Size changes:
Corresponding side lengths change:
Perimeter changes in the same way the corresponding side lengths change. This can be explained by the Distributive Property: For example, in Copy 2 the sides of the hat change b6 150%, so the perimeter will also change by 150%: 1.5l+1.5l+1.5w+1.5w=1.5(l+l+w+w)
Area changes:
Note: At this time in the Unit, students will make general statements about the area. Such as, “The area grows (or shrinks) but not in the same way as the lengths.” The area change relationship in scale figures will be developed in Investigations 2 and 3.
Ratios change:
In the last Problem, we worked with images, or scale drawings, that were similar to the original. Those scale drawings were larger than the original figure. In this Problem, you will work with scale drawings that are smaller than the original. You will also learn more about what it means for figures to be similar.
" ] } }, { + "id": "document_Text_2", "content": { "type": "Text", "format": "html", "text": [ - "When we study similar figures, we often compare their sides and angles. Recall that to compare the parts correctly, mathematicians use the terms corresponding sides and corresponding angles. In every pair of similar figures, each side of one figure has a corresponding side in the other figure. Also, each angle has a corresponding angle.", - "The example below shows the corresponding sides and corresponding angles of two triangles.
" + "When we study similar figures, we often compare their sides and angles. Recall that to compare the parts correctly, mathematicians use the terms
corresponding sides
and
corresponding angles
. In every pair of similar figures, each side of one figure has a corresponding side in the other figure. Also, each angle has a corresponding angle.
The example below shows the corresponding sides and corresponding angles of two triangles.
" ] } }, - {"id": "21AUG20220843AM", "title": "Corresponding sides and corresponding angles for similar triangles ABC and DEF", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_3_corresponding.jpg"}}, + { + "id": "21AUG20220843AM", + "title": "Corresponding sides and corresponding angles for similar triangles ABC and DEF", + "content": { + "type": "Image", + "url": "sas/images/SS_1_3_corresponding.jpg" + } + }, { "id": "21AUG20220528PM", "title": "Corresponding Angles", "content": { "type": "Geometry", - "board": {"properties": {"axisMin": [-2, -2], "axisRange": [20, 16]}}, + "board": { + "properties": { + "axisMin": [ + -2, + -2 + ], + "axisRange": [ + 20, + 16 + ] + } + }, "objects": [ - {"type": "point", "parents": [1, 1], "properties": {"id": "fD4BT7J3op3pVQtK", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [1, 6], "properties": {"id": "gIZaiLYMyd1FrE5x", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [4, 1], "properties": {"id": "Kn7fkbmzBqjMA32K", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["fD4BT7J3op3pVQtK", "gIZaiLYMyd1FrE5x", "Kn7fkbmzBqjMA32K"], "properties": {"id": "BTA-bCQzBm-RaG9S"}}, - {"type": "point", "parents": [6, 1], "properties": {"id": "d-I-pw7ySlzt7ETY", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [6, 9.4], "properties": {"id": "LaCUJeVNrw7NtNJ2", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [11, 1], "properties": {"id": "3jxIfnZmEvGoiXdO", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["d-I-pw7ySlzt7ETY", "LaCUJeVNrw7NtNJ2", "3jxIfnZmEvGoiXdO"], "properties": {"id": "7nB5OzVIjO7ZnjcC"}}, - {"type": "vertexAngle", "parents": ["d-I-pw7ySlzt7ETY", "LaCUJeVNrw7NtNJ2", "3jxIfnZmEvGoiXdO"], "properties": {"id": "qC8fQ3hGBhegjZ0m", "radius": 1}}, - {"type": "vertexAngle", "parents": ["fD4BT7J3op3pVQtK", "gIZaiLYMyd1FrE5x", "Kn7fkbmzBqjMA32K"], "properties": {"id": "Z8sxCfZoi_i7aA7U", "radius": 1}} + { + "type": "point", + "parents": [ + 1, + 1 + ], + "properties": { + "id": "fD4BT7J3op3pVQtK", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "point", + "parents": [ + 1, + 6 + ], + "properties": { + "id": "gIZaiLYMyd1FrE5x", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "point", + "parents": [ + 4, + 1 + ], + "properties": { + "id": "Kn7fkbmzBqjMA32K", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "polygon", + "parents": [ + "fD4BT7J3op3pVQtK", + "gIZaiLYMyd1FrE5x", + "Kn7fkbmzBqjMA32K" + ], + "properties": { + "id": "BTA-bCQzBm-RaG9S" + } + }, + { + "type": "point", + "parents": [ + 6, + 1 + ], + "properties": { + "id": "d-I-pw7ySlzt7ETY", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "point", + "parents": [ + 6, + 9.4 + ], + "properties": { + "id": "LaCUJeVNrw7NtNJ2", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "point", + "parents": [ + 11, + 1 + ], + "properties": { + "id": "3jxIfnZmEvGoiXdO", + "snapToGrid": true, + "snapSizeX": 0.1, + "snapSizeY": 0.1 + } + }, + { + "type": "polygon", + "parents": [ + "d-I-pw7ySlzt7ETY", + "LaCUJeVNrw7NtNJ2", + "3jxIfnZmEvGoiXdO" + ], + "properties": { + "id": "7nB5OzVIjO7ZnjcC" + } + }, + { + "type": "vertexAngle", + "parents": [ + "d-I-pw7ySlzt7ETY", + "LaCUJeVNrw7NtNJ2", + "3jxIfnZmEvGoiXdO" + ], + "properties": { + "id": "qC8fQ3hGBhegjZ0m", + "radius": 1 + } + }, + { + "type": "vertexAngle", + "parents": [ + "fD4BT7J3op3pVQtK", + "gIZaiLYMyd1FrE5x", + "Kn7fkbmzBqjMA32K" + ], + "properties": { + "id": "Z8sxCfZoi_i7aA7U", + "radius": 1 + } + } ] } }, { + "id": "document_Text_3", "content": { "type": "Text", "format": "html", "text": [ - "There are different ways to identify angles. We can identify an angle with three letters. The letter identifying the vertex of an angle is always the middle letter in its name. We use the word ‘angle’ or the angle symbol ‘∠’. Also, we can also name an angle by its vertex when it is clear which angle we are referring to." + "There are different ways to identify angles. We can identify an angle with three letters. The letter identifying the vertex of an angle is always the middle letter in its name. We use the word ‘angle’ or the angle symbol ‘∠’. Also, we can also name an angle by its vertex when it is clear which angle we are referring to.
" ] } }, - {"id": "21AUG20220847AM", "title": "Names of angles in triangle ABCF", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_3_identify_angles.jpg"}}, - {"content": {"type": "Text", "format": "html", "text": ["What names would you give the angles in the large triangle? ", "Name the corresponding angles in the following two similar triangles?"]}}, - {"id": "21AUG20220849AM", "title": "Similar triangles with an unknown side length", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_1_3_identify_angles.png"}} + { + "id": "21AUG20220847AM", + "title": "Names of angles in triangle ABCF", + "content": { + "type": "Image", + "url": "sas/images/SS_1_3_identify_angles.jpg" + } + }, + { + "id": "document_Text_4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "What names would you give the angles in the large triangle?
Name the corresponding angles in the following two similar triangles?
" + ] + } + }, + { + "id": "21AUG20220849AM", + "title": "Similar triangles with an unknown side length", + "content": { + "type": "Image", + "url": "sas/images/SS_1_3_identify_angles.png" + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-2/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-2/problem-1/nowWhatDoYouKnow/content.json index 8e3d3cf51..43df1b406 100644 --- a/curriculum/sas/investigation-2/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-2/problem-1/nowWhatDoYouKnow/content.json @@ -2,22 +2,35 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["How can you determine if an original figure and its image are similar by looking at the coordinate rule that produced the image? What features (attributes) stay the same for Mug and similar figures? What features change?"]}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "How can you determine if an original figure and its image are similar by looking at the coordinate rule that produced the image? What features (attributes) stay the same for Mug and similar figures? What features change?
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Students should discuss enlarging geometric figures using coordinate grids and rules that produce both similar and non-similar figures. ", - "If the coordinates for the original figure is (x, y), then the coordinates for the similar image is (kx, ky), which means that each x-coordinate and y- coordinate for the similar image is multiplied by the same number k to the original coordinates. ", - "Also, students should expand understanding which attributes change and which stay the same: ", - "* corresponding angles of two similar figures are the same measure while angles of non-similar figures may not be.", - "* corresponding side lengths from the original shape to the similar figure increase by the multiplier used to create a new rule. " + "" ] } }, - {"id": "21AUG20220851AM", "title": "Did You Know?: Images in computer graphics", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_2_1_In_13_did_you_know_350w.png"}} + { + "id": "21AUG20220851AM", + "title": "Did You Know?: Images in computer graphics", + "content": { + "type": "Image", + "url": "sas/images/SS_2_1_In_13_did_you_know_350w.png" + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-2/problem-2/initialChallenge/content.json b/curriculum/sas/investigation-2/problem-2/initialChallenge/content.json index 259392aaa..aebbe03d6 100644 --- a/curriculum/sas/investigation-2/problem-2/initialChallenge/content.json +++ b/curriculum/sas/investigation-2/problem-2/initialChallenge/content.json @@ -3,205 +3,1056 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "Zack experiments with multiplying Mug’s coordinates by different whole numbers to make other characters. Marta asks her uncle how multiplying the coordinates by a decimal or adding numbers to or subtracting numbers from each coordinate will affect Mug’s shape. He gives her a sketch for a new shape (a hat for Mug) and some rules to investigate." + "Zack experiments with multiplying Mug’s coordinates by different whole numbers to make other characters. Marta asks her uncle how multiplying the coordinates by a decimal or adding numbers to or subtracting numbers from each coordinate will affect Mug’s shape. He gives her a sketch for a new shape (a hat for Mug) and some rules to investigate.
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At this time, many students may not have connected the stretching and shrinking to a multiplicative relationship. They may predict that adding will make a shape enlarge and subtracting will make a shape shrink. If so, students may predict that Hat 1 and Hat 5 will look the same." + "" ] } }, - {"content": {"type": "Text", "format": "markdown", "text": ["* Test each rule. How does your result compare with your prediction? "]}}, { + "id": "document_Text_5", "display": "teacher", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Answers will vary. Predictions may or may not have matched what happened to the shapes.", - "* Hat 1 will move 2 units to the right and 3 units up without changing its size or shape. (congruent and similar)", - "* Hat 2 will move 1 unit left and 4 units up, also without changing its size or shape. (congruent and similar)", - "* Hat 3 will be located 2 units to the right, and it will be 3 times as high (stretched vertically and not similar)", - "* Hat 4 will shrink vertically and horizontally by the same factor: 0.5. It keeps the same shape. Each length will be half of the original corresponding length. (similar)", - "* Hat 5 will be stretched vertically by the factor of 2, and horizontally by the factor of 3. (not similar)", - "* Hats 1, 2, and 4 are similar to Mug’s Hat. Hat 1 and Hat 2 are the same size and shape as Mug’s hat, but they move to different place on the coordinate graph. Hat 4 has the same shape, but different size from the Mug’s hat." + "" ] } }, { + "id": "document_Table_1", "display": "teacher", "content": { "type": "Table", - "name": "Table of Coordinate Pairs", - "columns": [ - {"name": " ", "values": ["Point", "A", "B", "C", "D", "E", "F", "G"]}, - {"name": "Mug's Hat", "values": ["(x , y)", "(1, 1)", "(9, 1)", "(6, 2)", "(6, 3)", "(4, 3)", "(4, 2)", "(1, 1)"]}, - {"name": "Hat 1", "values": ["(x + 2, y + 3)", "(3, 4)", "(11, 4)", "(8, 5)", " (8, 6)", "(6, 6)", "(6, 5)", "(3, 4)"]}, - {"name": "Hat 2", "values": ["(x - 1, y + 4)", "(0, 5)", "(8, 5)", "(5, 6)", "(5, 7)", "(3, 7)", "(3, 6)", "(0, 5)"]}, - {"name": "Hat 3", "values": ["(x + 2, 3y)", "(3, 3)", "(11, 3)", "(8, 6)", "(8, 9)", "(6, 9)", "(6, 6)", "(3, 3)"]}, - {"name": "Hat 4", "values": ["(0.5x, 0.5y)", "(0,5, 0.5)", "(4.5, 0.5)", "(3, 1)", "(3, 1.5)", "(2, 1.5)", "(2, 1)", "(0.5, 0.5)"]}, - {"name": "Hat 5", "values": ["(2x, 3y)", "(2, 3)", "(18, 3)", "(12, 6)", "(12, 9)", "(8, 9)", "(8, 6)", "(2, 3)"]} - 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{"text": "To predict what will happen to the hat with rules, recall the relationship between the rules to draw Zug, Lug, Bug, and Glug and its similarity in Problem 2.1."}, - {"text": "In Problem 2.1, how is a rule with adding or subtracting a number to the x or y coordinate different from a rule with multiplying a number?"} + { + "text": "To predict what will happen to the hat with rules, recall the relationship between the rules to draw Zug, Lug, Bug, and Glug and its similarity in Problem 2.1." + }, + { + "text": "In Problem 2.1, how is a rule with adding or subtracting a number to the x or y coordinate different from a rule with multiplying a number?" + } ] } \ No newline at end of file diff --git a/curriculum/sas/investigation-2/problem-2/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-2/problem-2/nowWhatDoYouKnow/content.json index 8f47b4883..97917e717 100644 --- a/curriculum/sas/investigation-2/problem-2/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-2/problem-2/nowWhatDoYouKnow/content.json @@ -3,27 +3,35 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", - "text": ["If you know the coordinate rules to create an image, how can you tell if the two figures are similar? How can you use the rule to predict the side lengths of the image? How is the effect of a coordinate rule like the effect of a rubber band stretcher or a copy machine setting?"] + "text": [ + "If you know the coordinate rules to create an image, how can you tell if the two figures are similar? How can you use the rule to predict the side lengths of the image? How is the effect of a coordinate rule like the effect of a rubber band stretcher or a copy machine setting?
" + ] } }, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "For the coordinates (x, y) of the original figure, if you make the coordinate rules by multiplying each coordinate by the same number, k, then the new image with the coordinates (kx, ky) is similar to the original figure. For example, if you multiply (x, y) by 2, then you will have new coordinates (2x, 2y). It makes the side lengths of the new image 2 times longer than the side lengths of the original figure. This rule has the same effect as both a rubber band with two-band stretcher and a copy machine setting with 200%.
", - "You can use the rule to predict what will happen to the lengths of corresponding sides. When looking at the coordinate rules, the multiplier from one coordinate to the next will tell how much the side lengths change from one figure to another. For example, if we think of Zug as the original and Bug as the image, each coordinate in the rule multiplies by 1.5. So, the lengths of Zug will grow 1.5 times to make the lengths of Bug. Zug’s nose is 2 units tall and Bug’s nose is 2 • 1.5 = 3 units tall. Zug’s forehead is 8 units long and Bug’s forehead is 8 • 1.5 = 12 units long
", - "Zug (2x, 2y)", - "For the coordinates (x, y) of the original figure, if you make the coordinate rules by multiplying each coordinate by the same number, k, then the new image with the coordinates (kx, ky) is similar to the original figure. For example, if you multiply (x, y) by 2, then you will have new coordinates (2x, 2y). It makes the side lengths of the new image 2 times longer than the side lengths of the original figure. This rule has the same effect as both a rubber band with two-band stretcher and a copy machine setting with 200%.
You can use the rule to predict what will happen to the lengths of corresponding sides. When looking at the coordinate rules, the multiplier from one coordinate to the next will tell how much the side lengths change from one figure to another. For example, if we think of Zug as the original and Bug as the image, each coordinate in the rule multiplies by 1.5. So, the lengths of Zug will grow 1.5 times to make the lengths of Bug. Zug’s nose is 2 units tall and Bug’s nose is 2 • 1.5 = 3 units tall. Zug’s forehead is 8 units long and Bug’s forehead is 8 • 1.5 = 12 units long
Zug (2x, 2y)
Bug (3x, 3y)
" ] } }, - {"display": "teacher", "id": "-6wzAUG20220915AM", "title": "Comparing nose lengths for Zug and Bug", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_2_2_NWDYK_Mug.jpg"}} + { + "id": "-6wzAUG20220915AM", + "title": "Comparing nose lengths for Zug and Bug", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/SS_2_2_NWDYK_Mug.jpg" + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-2/problem-2/whatIf/content.json b/curriculum/sas/investigation-2/problem-2/whatIf/content.json index 4185136f0..bdbf69271 100644 --- a/curriculum/sas/investigation-2/problem-2/whatIf/content.json +++ b/curriculum/sas/investigation-2/problem-2/whatIf/content.json @@ -3,38 +3,101 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "### Situation A. Writing New Hat Rules", - "Several members of the computer club wrote different design criteria that would produce hats similar to the original Mug hat. ", - "What rule would you write for each design?", - "**Syrah’s Design:** The side lengths are one third as long as Mug’s hat?" + "" ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "markdown", "text": ["(1/3 x, 1/3 y)"]}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Joe’s Design:** The side lengths are 1.5 times as long as Mug’s hat?"]}}, - {"display": "teacher", "content": {"type": "Text", "format": "markdown", "text": ["(1.5 x, 1.5 y)"]}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Viola’s Design:**The hat is the same size as Mug’s hat but has moved right 1 unit and up 5 units?"]}}, - {"display": "teacher", "content": {"type": "Text", "format": "markdown", "text": ["(x + 1, y - 5)"]}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Kathy's Design:** The image is in another quadrant of the graph?"]}}, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Answers will vary.
", - "To move the image to the second quadrant, you should move it left more than 9 units and up more than 0: possible answers are (x-9, y), (x-10, y+1), (x-12, y+3).
", - "To move the image to the third quadrant, you should move it left more than 9 units and down more than 3 units: possible answers are (x-9, y-3), (x-9, y-4), (x-11, y-4).
", - "To move the image to the fourth quadrant, you should move it down more than 3 units and right more than 0 units: possible answers are (x, y-3), (x, y-5), (x+2, y-5).
" + "" + ] + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["Situation B. Raymond's Claim about Negative Numbers and Rules", "Raymond's Claim", "If you multiply each coordinate by a negative number the image is similar but smaller. Is he correct? Explain."]}}, { + "id": "document_Text_4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_6", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_7", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_8", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Answers will vary.
To move the image to the second quadrant, you should move it left more than 9 units and up more than 0: possible answers are (x-9, y), (x-10, y+1), (x-12, y+3).
To move the image to the third quadrant, you should move it left more than 9 units and down more than 3 units: possible answers are (x-9, y-3), (x-9, y-4), (x-11, y-4).
To move the image to the fourth quadrant, you should move it down more than 3 units and right more than 0 units: possible answers are (x, y-3), (x, y-5), (x+2, y-5).
" + ] + } + }, + { + "id": "document_Text_9", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Situation B. Raymond's Claim about Negative Numbers and Rules
Raymond's ClaimIf you multiply each coordinate by a negative number the image is similar but smaller. Is he correct? Explain.
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{"content": {"type": "Text", "format": "markdown", "text": ["* Identify pairs of similar shapes. Provide evidence that your shapes are similar. What is the scale factor? "]}}, { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_3", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Rectangles
", - "Rectangles (mouths) J, L, and N are similar to each other. Students should point out that since these are all rectangles, the angles are all right angles and hence congruent, or the same size. For rectangles, it is then only necessary to check side lengths.
", - "L to J is 2; L to N is 3; J to N is 3/2
", - "J to L is 1/2 (reciprocal of 2); N to L is 1/3 (reciprocal of 3); N to J is 2/3 (reciprocal of 3/2 ).
", - "Triangles
", - "Triangles (noses) O, R, and S are similar to each other.
", - "O to R is 2; O to S is 3; and R to S is 3/2 .
", - "R to O is 1/2 (reciprocal of 2); S to O is 1/3 (reciprocal of 3); S to R is 2/3 (reciprocal of 3/2 ).
" + "Rectangles
Rectangles (mouths) J, L, and N are similar to each other. Students should point out that since these are all rectangles, the angles are all right angles and hence congruent, or the same size. For rectangles, it is then only necessary to check side lengths.
L to J is 2; L to N is 3; J to N is 3/2
J to L is 1/2 (reciprocal of 2); N to L is 1/3 (reciprocal of 3); N to J is 2/3 (reciprocal of 3/2 ).
Triangles
Triangles (noses) O, R, and S are similar to each other.
O to R is 2; O to S is 3; and R to S is 3/2 .
R to O is 1/2 (reciprocal of 2); S to O is 1/3 (reciprocal of 3); S to R is 2/3 (reciprocal of 3/2 ).
" + ] + } + }, + { + "id": "document_Text_4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "• In what ways could scale factor be useful when determining similar figures?
" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["• In what ways could scale factor be useful when determining similar figures?"]}}, { + "id": "document_Text_5", "display": "teacher", "content": { "type": "Text", @@ -95,5 +597,9 @@ } ] }, - "supports": [{"text": "When you identify pairs of rectangles or triangles, what measurements do you compare? Angles, Side lengths, Perimeters, Areas, etc."}] + "supports": [ + { + "text": "When you identify pairs of rectangles or triangles, what measurements do you compare? Angles, Side lengths, Perimeters, Areas, etc." + } + ] } \ No newline at end of file diff --git a/curriculum/sas/investigation-2/problem-3/introduction/content.json b/curriculum/sas/investigation-2/problem-3/introduction/content.json index c8b67fe17..c9ed9ee3d 100644 --- a/curriculum/sas/investigation-2/problem-3/introduction/content.json +++ b/curriculum/sas/investigation-2/problem-3/introduction/content.json @@ -2,24 +2,51 @@ "type": "introduction", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["In the computer game the characters were members of the Wump family. We found a way to decide which characters were imposters using the coordinate rule."]}}, - {"id": "AUG20221120AM", "title": "Character animations for the Wumps and imposters", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_2_3_In_17_three_characters_500w.png"}}, - {"content": {"type": "Text", "format": "html", "text": ["How can you decide whether two shapes are similar?"]}}, { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "We have experimented with rubber-band stretchers, copiers, and coordinate plots. Your experiments suggest that for two figures to be similar, there must be the following correspondence between the figures:In the computer game the characters were members of the Wump family. We found a way to decide which characters were imposters using the coordinate rule.
" ] } }, { + "id": "AUG20221120AM", + "title": "Character animations for the Wumps and imposters", + "content": { + "type": "Image", + "url": "sas/images/SS_2_3_In_17_three_characters_500w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "How can you decide whether two shapes are similar?
" + ] + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "We have experimented with rubber-band stretchers, copiers, and coordinate plots. Your experiments suggest that for two figures to be similar, there must be the following correspondence between the figures:
The
scale factor
is the number that the side lengths of one figure are multiplied by to give the corresponding side lengths of a similar figure.
How can you decide if two shapes are similar? How can you determine the scale factor between two similar shapes?
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "SOLUTION
", - "To determine is two shapes are similar:
", - "Scale factor can be determined by measuring and comparing corresponding lengths between two figures. This done using proportional reasoning. For every unit of length in the original there are x times as many units in the corresponding side length.
", - "We have seen scale factor as the number of rubber bands used, the percent increase on a copy machine, or the coefficient relationship of the x and y coordinates.
" + "SOLUTION
To determine is two shapes are similar:
Scale factor can be determined by measuring and comparing corresponding lengths between two figures. This done using proportional reasoning. For every unit of length in the original there are x times as many units in the corresponding side length.
We have seen scale factor as the number of rubber bands used, the percent increase on a copy machine, or the coefficient relationship of the x and y coordinates.
" ] } }, - {"id": "AUG20221123AM", "title": "The Chicago Model City", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_2_3_chicago.png"}} + { + "id": "AUG20221123AM", + "title": "The Chicago Model City", + "content": { + "type": "Image", + "url": "sas/images/SS_2_3_chicago.png" + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-3/problem-1/initialChallenge/content.json b/curriculum/sas/investigation-3/problem-1/initialChallenge/content.json index 8cc9f5319..b6012af1f 100644 --- a/curriculum/sas/investigation-3/problem-1/initialChallenge/content.json +++ b/curriculum/sas/investigation-3/problem-1/initialChallenge/content.json @@ -9,8 +9,7 @@ "type": "Text", "format": "html", "text": [ - "The Art Club at P.I. Middle school is also exploring similar figures to create rep-tiles. They need to know which rectangles and triangles are rep-tiles.
", - "To answer this question, sketch or use your Shape Set to make several larger and similar copies of each of the following shapes:
" + "The Art Club at P.I. Middle school is also exploring similar figures to create rep-tiles. They need to know which rectangles and triangles are rep-tiles.
To answer this question, sketch or use your Shape Set to make several larger and similar copies of each of the following shapes:
" ] } }, @@ -20,81 +19,384 @@ "content": { "type": "Text", "format": "html", - "text": ["Quadrilaterals Triangles
", "A non-square rectangle A right triangle
", "A non-rectangular parallelogram An isosceles triangle
"] + "text": [ + "Quadrilaterals Triangles
A non-square rectangle A right triangle
A non-rectangular parallelogram An isosceles triangle
" + ] + } + }, + { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] } }, - {"content": {"type": "Text", "format": "markdown", "text": ["* Which shapes are a rep-tile? Make a sketch to show how the copies fit together."]}}, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Student answers will vary.", - "Quadrilaterals", - "All rectangles and parallelograms have copies that can fit together to make a larger shape that is similar to the original. Also, there are some trapezoids that have copies that can fit together to make a larger, similar shape. Not every trapezoid is a rep-tile. Possible sketches are below. ", - "Triangles", - "All triangles have copies that can fit together to make a larger, similar triangle. Possible sketches shown below." + "Student answers will vary.
Quadrilaterals
All rectangles and parallelograms have copies that can fit together to make a larger shape that is similar to the original. Also, there are some trapezoids that have copies that can fit together to make a larger, similar shape. Not every trapezoid is a rep-tile. Possible sketches are below.
Triangles
All triangles have copies that can fit together to make a larger, similar triangle. Possible sketches shown below.
" ] } }, { + "id": "document_Text_3", "content": { "type": "Text", "format": "html", "text": [ - "For the shapes that rep-tile, what is theFor the shapes that rep-tile, what is the
See the chart above for answers.
", - "The side lengths and perimeter of the larger figure are the scale factor times the side lengths of the smaller figure. Note: The perimeter change can be explained by the Distributive Property. The scale factor multiplies by every length.
", - "So, if we have a rectangle with length of L, width of W, and scale factor of s, then the perimeter change is s(L) + s(L) + s(W) + s(W) = s(L + L + S + S).
", - "The angle measures don’t change since corresponding angles for similar figures are congruent. The corresponding angles would all have equal measures.
", - "The corresponding angles would all have equal measures.
", - "The area of the larger figure is the square of the scale factor, or scale factor time scale factor, times the area of the smaller figure. For example, if you have a scale factor of 5, each length would be 5 times larger. To make the reptile, you would need 25 copies of the original. The area grows by the square of the scale factor, or 52, so you need 25 copies. If we consider a rectangle with a scale factor of 5, then the area of the image would be 5L.
", - "Original rectangle: L・W
", - "Image with scale factor of 5: 5(L)・5(W) =
", - "Using associative property: 5・5・L・W =
", - "See the impact of scale factor on area: 5²・L・W
" + "See the chart above for answers.
The side lengths and perimeter of the larger figure are the scale factor times the side lengths of the smaller figure. Note: The perimeter change can be explained by the Distributive Property. The scale factor multiplies by every length.
So, if we have a rectangle with length of L, width of W, and scale factor of s, then the perimeter change is s(L) + s(L) + s(W) + s(W) = s(L + L + S + S).
The angle measures don’t change since corresponding angles for similar figures are congruent. The corresponding angles would all have equal measures.
The corresponding angles would all have equal measures.
The area of the larger figure is the square of the scale factor, or scale factor time scale factor, times the area of the smaller figure. For example, if you have a scale factor of 5, each length would be 5 times larger. To make the reptile, you would need 25 copies of the original. The area grows by the square of the scale factor, or 52, so you need 25 copies. If we consider a rectangle with a scale factor of 5, then the area of the image would be 5L.
Original rectangle: L・W
Image with scale factor of 5: 5(L)・5(W) =
Using associative property: 5・5・L・W =
See the impact of scale factor on area: 5²・L・W
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"In Shapes and Designs, we learned that some polygons fit together to cover, or tile, a flat surface. For example, the surface of a honeycomb has a pattern of regular hexagons. Many bathroom and kitchen floors are covered with a pattern of square tiles. These patterns of polygons that fit together are called tessellations." + "In
Shapes and Designs
, we learned that some polygons fit together to cover, or tile, a flat surface. For example, the surface of a honeycomb has a pattern of regular hexagons. Many bathroom and kitchen floors are covered with a pattern of square tiles. These patterns of polygons that fit together are called
tessellations.
" ] } }, - {"id": "21AUG20221123AM", "title": "Examples of tesselations", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_In_20_rep_tiles_350w.png"}}, { + "id": "21AUG20221123AM", + "title": "Examples of tesselations", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_In_20_rep_tiles_350w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Look closely at the pattern of squares. We can see that the large square consists of nine small squares. The large square is similar to each of the nine small squares. The large square has sides formed by the sides of three small squares, so the scale factor from the small square to the large square is 3.
" + ] + } + }, + { + "id": "21AUG20221124AM", + "title": "Similar squares with a scale factor of 3 or 1/3", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_Intro_scale3.jpg" + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "We can also put four small squares together to make a four-tile square. This four-tile square is similar to both the large nine-tile square and the small single-tile square.
" + ] + } + }, + { + "id": "21AUG20221125AM", + "title": "Similar squares with a scale factor of 2 or 1/2", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_Intro_scale2.jpg" + } + }, + { + "id": "document_Text_4", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The scale factor from the single-tile square to the four-tile square is 2. The scale factor from the four-tile square to the single-tile square is 1/2.
" + ] + } + }, + { + "id": "document_Text_5", "content": { "type": "Text", "format": "html", "text": [ - "Look closely at the pattern of squares. We can see that the large square consists of nine small squares. The large square is similar to each of the nine small squares. The large square has sides formed by the sides of three small squares, so the scale factor from the small square to the large square is 3." + "No matter how closely we look at the hexagon pattern, however, you cannot find a large hexagon made up of similar smaller hexagons.
" ] } }, - {"id": "21AUG20221124AM", "title": "Similar squares with a scale factor of 3 or 1/3", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_Intro_scale3.jpg"}}, - {"content": {"type": "Text", "format": "html", "text": ["We can also put four small squares together to make a four-tile square. This four-tile square is similar to both the large nine-tile square and the small single-tile square."]}}, - {"id": "21AUG20221125AM", "title": "Similar squares with a scale factor of 2 or 1/2", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_Intro_scale2.jpg"}}, - {"content": {"type": "Text", "format": "html", "text": ["The scale factor from the single-tile square to the four-tile square is 2. The scale factor from the four-tile square to the single-tile square is 1/2."]}}, - {"content": {"type": "Text", "format": "html", "text": ["No matter how closely we look at the hexagon pattern, however, you cannot find a large hexagon made up of similar smaller hexagons."]}}, - {"id": "6wzAUG20221255AM", "title": "Tiling with hexagons", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_Intro_hexagons.jpg"}}, { + "id": "6wzAUG20221255AM", + "title": "Tiling with hexagons", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_Intro_hexagons.jpg" + } + }, + { + "id": "document_Text_6", "content": { "type": "Text", "format": "html", "text": [ - "A shape is a rep-tile if you can put together copies that are the same size and shape (congruent) copies of the shape to make a larger, similar shape. The copies may be rotated in order to fit together. A square is a rep-tile. \n\nIn this problem we will investigate which rectangles and triangles are rep-tiles." + "A shape is a
rep-tile
if you can put together copies that are the same size and shape (congruent) copies of the shape to make a larger, similar shape. The copies may be rotated in order to fit together. A square is a rep-tile. In this problem we will investigate which rectangles and triangles are rep-tiles.
" ] } } diff --git a/curriculum/sas/investigation-3/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-3/problem-1/nowWhatDoYouKnow/content.json index a67c74058..a2ae5bdcb 100644 --- a/curriculum/sas/investigation-3/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-3/problem-1/nowWhatDoYouKnow/content.json @@ -2,26 +2,35 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["How do rep-tiles show the relationship between the scale factor and the perimeter of a similar shape? What about the scale factor and the area? "]}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "How do rep-tiles show the relationship between the scale factor and the perimeter of a similar shape? What about the scale factor and the area?
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "When rep-tiling, we can use multiple tiles of a shape to make a larger or smaller similar shape. Rep-tiles keep the corresponding angles the same measure. This lets us focus on the relationships in the other measures, like lengths and area.
", - "If you make a rep-tile using four same copies, then the area of a rep-tile is four times the area of the original copy. And the scale factor is 2, because the side length of a rep-tile will be twice the side length of the original copy.
", - "If the scale factor is k, then the side lengths of the image will be times the side lengths of the original copy. Each dimension of the shape is stretched or shrunk by the scale factor. Since we find area by multiplying both dimensions, we also multiply the scale factor times the scale factor on the image. The area of the rep-tile will be times larger. If
", - "Aoriginal = L • W , then
", - "A scale factor k = K • L • K• W =
", - "K • K • L • W =
", - "K2 • L • W
", - "Note that students will need to use their knowledge of the Commutative Property from the previous unit.
" + "When rep-tiling, we can use multiple tiles of a shape to make a larger or smaller similar shape. Rep-tiles keep the corresponding angles the same measure. This lets us focus on the relationships in the other measures, like lengths and area.
If you make a rep-tile using four same copies, then the area of a rep-tile is four times the area of the original copy. And the scale factor is 2, because the side length of a rep-tile will be twice the side length of the original copy.
If the scale factor is k, then the side lengths of the image will be times the side lengths of the original copy. Each dimension of the shape is stretched or shrunk by the scale factor. Since we find area by multiplying both dimensions, we also multiply the scale factor times the scale factor on the image. The area of the rep-tile will be times larger. If
Aoriginal = L • W , then
A scale factor k = K • L • K• W =
K • K • L • W =
K2 • L • W
Note that students will need to use their knowledge of the Commutative Property from the previous unit.
" ] } }, - {"id": "6wzAUG202201121pM", "title": "Did You Know?: Tiling and crystals", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_NW_22_did_you_know_350w.png"}} - ], - "supports": [] + { + "id": "6wzAUG202201121pM", + "title": "Did You Know?: Tiling and crystals", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_NW_22_did_you_know_350w.png" + } + } + ] } } \ No newline at end of file diff --git a/curriculum/sas/investigation-3/problem-1/whatIf/content.json b/curriculum/sas/investigation-3/problem-1/whatIf/content.json index 7e508fb46..7b56be532 100644 --- a/curriculum/sas/investigation-3/problem-1/whatIf/content.json +++ b/curriculum/sas/investigation-3/problem-1/whatIf/content.json @@ -2,9 +2,29 @@ "type": "whatIf", "content": { "tiles": [ - {"id": "eDp86zl9LDrWO-B4", "title": "Text 3", "content": {"type": "Text", "format": "html", "text": ["Examine each claim. Is it correct? Explain why.
"]}}, - {"content": {"type": "Text", "format": "html", "text": ["Patricia’s Claim If it takes nine copies of a certain rectangle or triangle to make a similar figure, the scale factor is 9. "]}}, { + "id": "eDp86zl9LDrWO-B4", + "title": "Text 3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Examine each claim. Is it correct? Explain why.
" + ] + } + }, + { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Patricia’s Claim
If it takes nine copies of a certain rectangle or triangle to make a similar figure, the scale factor is 9.
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", @@ -14,23 +34,39 @@ ] } }, - {"content": {"type": "Text", "format": "html", "text": ["Pete’s Claim If you are given a certain rectangle or triangle and a scale factor of 5, then it will take 5 copies of the original to make a scale copy."]}}, { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Pete’s Claim
If you are given a certain rectangle or triangle and a scale factor of 5, then it will take 5 copies of the original to make a scale copy.
" + ] + } + }, + { + "id": "document_Text_4", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Not correct. If we consider a rectangle, both the length and the width will increase by a factor of 5. You will need 25 copies of the original. The area grows by the scale factor times the scale factor, or square of the scale factor, so you need 25 copies.
", - "Aoriginal= L • W
", - "Ascale factor 5 = 5 • L • 5 • W
", - "= 5 • 5 •L • W or
", - "= 52 • L • W
" + "Not correct. If we consider a rectangle, both the length and the width will increase by a factor of 5. You will need 25 copies of the original. The area grows by the scale factor times the scale factor, or square of the scale factor, so you need 25 copies.
Aoriginal= L • W
Ascale factor 5 = 5 • L • 5 • W
= 5 • 5 •L • W or
= 52 • L • W
" + ] + } + }, + { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Tomiko’s Claim
All triangles are rep-tiles.
" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["Tomiko’s Claim All triangles are rep-tiles."]}}, { + "id": "document_Text_6", "display": "teacher", "content": { "type": "Text", @@ -41,44 +77,171 @@ } }, { + "id": "document_Text_7", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Kazuko’s Claim
If you want to show two triangles with the same angle measures are similar, you can use a unit rep-tile. I used an equilateral triangle whose side lengths are one unit. To show that the following two triangles are similar.
" + ] + } + }, + { + "id": "6wzAUG20220118pM", + "title": "Kazuko’s Claim: Measuring corresponding angles using a unit rep-tile", + "content": { + "type": "Image", + "url": "sas/images/SS_3_1_similar.jpg" + } + }, + { + "id": "document_Text_8", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "It is true. We can use a unit rep-tile to show that corresponding angles are the same measure. Note that this strategy may be more difficult to use if scale factors are not whole numbers.
" + ] + } + }, + { + "id": "6wzAUG20220119pM", + "title": "Unit rep-tile", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_C_1.png" + } + }, + { + "id": "6wzAUG202201120pM", + "title": "Measuring corresponding angles using a unit rep-tile", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_C_2.png" + } + }, + { + "id": "document_Text_9", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Dola started with a sketch of a quadrilateral. She divided it into four smaller quadrilaterals that have the same size and shape (congruent). She claims they are similar.
The smaller shapes have corresponding angles with the same measure. The corresponding lengths have all changed in the same way. We can see that two of the smaller lengths will equal the length of the corresponding side of the original.
" + ] + } + }, + { + "id": "document_Text_11", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "2. The lengths, which includes the perimeters, are ½ the size of the original and areas are ¼ of the original.
" + ] + } + }, + { + "id": "document_Text_12", + "display": "teacher", "content": { "type": "Text", "format": "html", - "text": ["Kazuko’s Claim If you want to show two triangles with the same angle measures are similar, you can use a unit rep-tile. I used an equilateral triangle whose side lengths are one unit. To show that the following two triangles are similar."] + "text": [ + "3. Yes. Many find it more difficult to sub-divide triangles. You can begin by sub-dividing the side lengths. Then draw in the smaller triangles making sure you keep the corresponding sides parallel.
" + ] + } + }, + { + "id": "6wzAUG20221258324pM", + "title": "Dividing a triangle into rep-tiles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_B_3.png" } }, - {"id": "6wzAUG20220118pM", "title": "Kazuko’s Claim: Measuring corresponding angles using a unit rep-tile", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_1_similar.jpg"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["It is true. We can use a unit rep-tile to show that corresponding angles are the same measure. Note that this strategy may be more difficult to use if scale factors are not whole numbers.
"]}}, - {"display": "teacher", "id": "6wzAUG20220119pM", "title": "Unit rep-tile", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_C_1.png"}}, - {"display": "teacher", "id": "6wzAUG202201120pM", "title": "Measuring corresponding angles using a unit rep-tile", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_C_2.png"}}, { + "id": "6wzAUG20221259pM", + "title": "Subdividing sides of a triangle to create 4 rep-tiles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_B_4.png" + } + }, + { + "id": "document_Text_13", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Then draw in the smaller triangles making sure you keep the corresponding sides parallel.
" ] } }, - {"display": "teacher", "id": "6wzAUG2022125asd6AM", "title": "Dividing a rectangle into rep-tiles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_B_1.png"}}, - {"display": "teacher", "id": "6wzAUG20221257pM", "title": "Dividing a parallelogram into rep-tiles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_B_2.png"}}, { + "id": "6wzAUG20220117pM", + "title": "Subdividing sides of a triangle to create 9 rep-tiles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_B_6.png" + } + }, + { + "id": "document_Text_14", "display": "teacher", "content": { "type": "Text", "format": "html", - "text": ["The smaller shapes have corresponding angles with the same measure. The corresponding lengths have all changed in the same way. We can see that two of the smaller lengths will equal the length of the corresponding side of the original.
"] + "text": [ + "Example with a scale factor of 1/3.
" + ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["2. The lengths, which includes the perimeters, are ½ the size of the original and areas are ¼ of the original.
"]}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["3. Yes. Many find it more difficult to sub-divide triangles. You can begin by sub-dividing the side lengths. Then draw in the smaller triangles making sure you keep the corresponding sides parallel.
"]}}, - {"display": "teacher", "id": "6wzAUG20221258324pM", "title": "Dividing a triangle into rep-tiles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_B_3.png"}}, - {"display": "teacher", "id": "6wzAUG20221259pM", "title": "Subdividing sides of a triangle to create 4 rep-tiles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_B_4.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Then draw in the smaller triangles making sure you keep the corresponding sides parallel.
"]}}, - {"display": "teacher", "id": "6wzAUG20220117pM", "title": "Subdividing sides of a triangle with parallel lines", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/parallelSubdivide3_1.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Example with a scale factor of 1/3.
"]}}, - {"display": "teacher", "id": "6wzAUG20220117pM", "title": "Subdividing sides of a triangle to create 9 rep-tiles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-1_What_If_Situation_B_6.png"}} + { + "id": "6wzAUG20220117pM", + "title": "Subdividing sides of a triangle to create 9 rep-tiles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-1_What_If_Situation_B_6.png" + } + } ] } } \ No newline at end of file diff --git a/curriculum/sas/investigation-3/problem-2/initialChallenge/content.json b/curriculum/sas/investigation-3/problem-2/initialChallenge/content.json index b98374822..94f5784c2 100644 --- a/curriculum/sas/investigation-3/problem-2/initialChallenge/content.json +++ b/curriculum/sas/investigation-3/problem-2/initialChallenge/content.json @@ -2,138 +2,580 @@ "type": "initialChallenge", "content": { "tiles": [ - {"id": "-6zAUG20220128pm", "title": "Rectangle A and Triangle B", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_2_In_23_A_B_350w.png"}}, { + "id": "-6zAUG20220128pm", + "title": "Rectangle A and Triangle B", + "content": { + "type": "Image", + "url": "sas/images/SS_3_2_In_23_A_B_350w.png" + } + }, + { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The Art Club created several design challenges using Rectangle A and Triangle B.
Criteria for Rectangles
Rectangle P The scale factor from Rectangle A to Rectangle P is 2.5.
Criteria for Rectangles
", "Rectangle P The scale factor from Rectangle A to Rectangle P is 2.5.
These two rectangles are similar. Is it possible to find the length of side AD? Explain your reasoning.
" + ] + } + }, + { + "id": "-6wzAUG20220136pM", + "title": "Similar rectangles with an unknown side length", + "content": { + "type": "Image", + "url": "sas/images/SS_3_2_WI_24_Q1_500w.png" + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "The scale factor from one figure to the other is 7.5 ÷ 6, or 1.25. Side DF is 3.75 cm since 3 × 1.25 is 3.75. Side FE is 6.25 cm (5 × 1.25 = 6.25). Because the triangles are similar, the corresponding angle measures are the same. So, the measure of angle F is 94°. Angle B and corresponding angle E are each 30° since 180 – (94 + 56) = 30. Note: Students will need to use the fact that the sum of the interior angles of a triangle is 180°." + "" ] } }, - {"id": "-6wzAUG202201df38pM", "title": "Similar triangles with unknown side lengths and angles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_2_WI_25_Q2_500w.png"}}, - {"display": "teacher", "id": "-6wzAUG20220138pM", "title": "Sample diagram using scale factor to find unknown side lengths and angles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/3-2_What_If_Situation_B_2.jpg"}} + { + "id": "-6wzAUG20220137pM", + "title": "Sample diagram using scale factor to find an unknown side length", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-2_What_If_Situation_A_1.png" + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "These two triangles are similar. Find all the missing side lengths and angles. Explain your reasoning.
" + ] + } + }, + { + "id": "document_Text_4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "-6wzAUG202201df38pM", + "title": "Similar triangles with unknown side lengths and angles", + "content": { + "type": "Image", + "url": "sas/images/SS_3_2_WI_25_Q2_500w.png" + } + }, + { + "id": "-6wzAUG20220138pM", + "title": "Sample diagram using scale factor to find unknown side lengths and angles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/3-2_What_If_Situation_B_2.jpg" + } + } ] }, - "supports": [{"text": "Can using corresponding sides help?"}, {"text": "Can using corresponding angles help?"}, {"text": "What is the scale factor from one shape to the other?"}] + "supports": [ + { + "text": "Can using corresponding sides help?" + }, + { + "text": "Can using corresponding angles help?" + }, + { + "text": "What is the scale factor from one shape to the other?" + } + ] } \ No newline at end of file diff --git a/curriculum/sas/investigation-3/problem-3/initialChallenge/content.json b/curriculum/sas/investigation-3/problem-3/initialChallenge/content.json index b4aa6ee11..00d955e11 100644 --- a/curriculum/sas/investigation-3/problem-3/initialChallenge/content.json +++ b/curriculum/sas/investigation-3/problem-3/initialChallenge/content.json @@ -3,21 +3,48 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "Durrell, Angie, and Tonya are designing a boardwalk that crosses a river for a science project. They make several measurements and use stakes to mark the distances to create triangles. They also make a sketch like the diagram below.", - "The students use similar triangles to find distances that are difficult to measure. The diagram shows a specific type of similar triangles, nested triangles, which are triangles that share a common angle.
" + "Durrell, Angie, and Tonya are designing a boardwalk that crosses a river for a science project. They make several measurements and use stakes to mark the distances to create triangles. They also make a sketch like the diagram below.
The students use similar triangles to find distances that are difficult to measure. The diagram shows a specific type of similar triangles, nested triangles, which are triangles that share a common angle.
" + ] + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "• What is the distance across the river from Stake 1 to Tree 1? Explain your reasoning.
" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["• What is the distance across the river from Stake 1 to Tree 1? Explain your reasoning."]}}, [ - {"id": "-6wzAUG202201df45pM", "title": "Diagram of the river with similar triangles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_3_3_In_26_river_triangle_350w.png"}}, - {"id": "Gxtx7JsemG3EXVsl", "title": "Text 1", "content": {"type": "Text", "format": "html", "text": ["The triangles in the diagram are similar.
", "The angles that look like right angles are right angles.
", "The angle at Stake 3 is shared by both triangles.
"]}} + { + "id": "-6wzAUG202201df45pM", + "title": "Diagram of the river with similar triangles", + "content": { + "type": "Image", + "url": "sas/images/SS_3_3_In_26_river_triangle_350w.png" + } + }, + { + "id": "Gxtx7JsemG3EXVsl", + "title": "Text 1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The triangles in the diagram are similar.
The angles that look like right angles are right angles.
The angle at Stake 3 is shared by both triangles.
" + ] + } + } ], { + "id": "document_Text_3", "display": "teacher", "content": { "type": "Text", @@ -29,5 +56,15 @@ } ] }, - "supports": [{"text": "What shapes do you see in the diagram? Are they similar? Why?"}, {"text": "What measurements in the diagram might be useful?"}, {"text": "How can corresponding sides and angles in two similar triangles help find the missing measurements?"}] + "supports": [ + { + "text": "What shapes do you see in the diagram? Are they similar? Why?" + }, + { + "text": "What measurements in the diagram might be useful?" + }, + { + "text": "How can corresponding sides and angles in two similar triangles help find the missing measurements?" + } + ] } \ No newline at end of file diff --git a/curriculum/sas/investigation-3/problem-3/whatIf/content.json b/curriculum/sas/investigation-3/problem-3/whatIf/content.json index 6c4cbcd31..4e7d9ba55 100644 --- a/curriculum/sas/investigation-3/problem-3/whatIf/content.json +++ b/curriculum/sas/investigation-3/problem-3/whatIf/content.json @@ -2,21 +2,47 @@ "type": "whatIf", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["I used unit rep-tiles to show that the smaller right triangle is similar to the larger right triangle. Is he correct? Explain.
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Durrell’s Claim is not correct.
", - "Students may refer back to Problem 3.1 Kazuko’s Claim. The scale factor is not a whole number. So, we cannot consider the smaller triangle as a unit rep-tile. The distance from Stake 1 to Stake 2 in smaller triangle is 80ft. The corresponding distance in larger triangle is 140ft (from Tree 1 to Tree 2). If you put two small triangles, it will be 160 ft long, which is longer than 140 ft. You cannot fit whole amounts of the small triangles in the large triangle. Therefore, you cannot use rep-tiles to show the similarity.
" + "Durrell’s Claim is not correct.
Students may refer back to Problem 3.1 Kazuko’s Claim. The scale factor is not a whole number. So, we cannot consider the smaller triangle as a unit rep-tile. The distance from Stake 1 to Stake 2 in smaller triangle is 80ft. The corresponding distance in larger triangle is 140ft (from Tree 1 to Tree 2). If you put two small triangles, it will be 160 ft long, which is longer than 140 ft. You cannot fit whole amounts of the small triangles in the large triangle. Therefore, you cannot use rep-tiles to show the similarity.
" + ] + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Angie’s StrategyI put the stakes in different places and made a sketch. It does not change my answer.Is she correct? Explain.
" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["Consider this set of Rectangles
" + ] + } + }, + { + "id": "21AUG20200148pm", + "title": "Rectangles A, B, C, and D", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_IC_32_rectangles_350w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "• For the set of rectangles, which are similar? Why?
" + ] + } + }, + { + "id": "document_Text_3", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Rectangles: A, B, and C are similar.
", - "Possible explanation:
", - "Because the shapes are rectangles, all the angles will be 90˚. So, corresponding angles will have the same measures.
", - "To determine similarity of these rectangles, students may use scale factors or ratios.
", - "Ratio of adjacent side lengths:
", - "Rectangle A: (12 short side)/(20 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
", - "Rectangle B: (6 short side)/(10 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
", - "Rectangle C: (9 short side)/(15 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
", - "Rectangle D: (6 short side)/(20 long side) = (3 short side)/(10 long side) = (0.3 short side)/(1 long side)
", - "The ratio of the length of the short side to the length of the long side is the same for all three similar rectangles. The rectangle that is not similar to the others has a different ratio.
", - "If the scale factors for both length and width are equivalent, two rectangles are similar.
", - "The scale factors are:
" + "Rectangles: A, B, and C are similar.
Possible explanation:
Because the shapes are rectangles, all the angles will be 90˚. So, corresponding angles will have the same measures.
To determine similarity of these rectangles, students may use scale factors or ratios.
Ratio of adjacent side lengths:
Rectangle A: (12 short side)/(20 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
Rectangle B: (6 short side)/(10 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
Rectangle C: (9 short side)/(15 long side) = (3 short side)/(5 long side) = (0.6 short side)/(1 long side)
Rectangle D: (6 short side)/(20 long side) = (3 short side)/(10 long side) = (0.3 short side)/(1 long side)
The ratio of the length of the short side to the length of the long side is the same for all three similar rectangles. The rectangle that is not similar to the others has a different ratio.
If the scale factors for both length and width are equivalent, two rectangles are similar.
The scale factors are:
" ] } }, - {"display": "teacher", "id": "21AUG20200149pm", "title": "Scale factors for similar Rectangles A, B, and C", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_Initial_Challenge_1.png"}}, - {"display": "teacher", "id": "WTNLpOzp7NnIBqAn", "title": "Text 1", "content": {"type": "Text", "format": "html", "text": ["If the scale factors for both length and width are equivalent, two rectangles are similar.
"]}}, { + "id": "21AUG20200149pm", + "title": "Scale factors for similar Rectangles A, B, and C", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_Initial_Challenge_1.png" + } + }, + { + "id": "WTNLpOzp7NnIBqAn", + "title": "Text 1", "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "If the scale factors for both length and width are equivalent, two rectangles are similar.
" + ] + } + }, + { "id": "D42ENgHpU-YlUiFP", "title": "Text 2", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Note: If figures are similar, their ratios of corresponding side lengths will be equivalent. The ratio of adjacent side lengths within a figure gives an indication of the shape of the original figure (and image) since it compares measures within one figure. The ratio of side lengths is not enough to know of a figure is scaled, corresponding angles measures must be equivalent.
", - "After finding scale factors like those in this Problem, many students will discuss the advantages of finding the ratio of the adjacent side lengths for measurements like these.
" + "Note: If figures are similar, their ratios of corresponding side lengths will be equivalent. The ratio of adjacent side lengths within a figure gives an indication of the shape of the original figure (and image) since it compares measures within one figure. The ratio of side lengths is not enough to know of a figure is scaled, corresponding angles measures must be equivalent.
After finding scale factors like those in this Problem, many students will discuss the advantages of finding the ratio of the adjacent side lengths for measurements like these.
" ] } }, { "id": "rGyS1Rt0W_Js6z2H", "title": "Text 3", - "content": {"type": "Text", "format": "html", "text": ["• If two rectangles are similar, write as many ratios as possible of adjacent side lengths in one rectangle compared to the corresponding adjacent side lengths in the other rectangle. What do you notice?
"]} + "content": { + "type": "Text", + "format": "html", + "text": [ + "• If two rectangles are similar, write as many ratios as possible of adjacent side lengths in one rectangle compared to the corresponding adjacent side lengths in the other rectangle. What do you notice?
" + ] + } }, - {"display": "teacher", "id": "Q8-PdqSOVbZqWwS_", "title": "Text 4", "content": {"type": "Text", "format": "html", "text": ["The ratios of adjacent sides of similar figures are equivalent.
", "See some examples of ratios above.
"]}} + { + "id": "Q8-PdqSOVbZqWwS_", + "title": "Text 4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The ratios of adjacent sides of similar figures are equivalent.
See some examples of ratios above.
" + ] + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-4/problem-1/introduction/content.json b/curriculum/sas/investigation-4/problem-1/introduction/content.json index 875d24229..d349592c9 100644 --- a/curriculum/sas/investigation-4/problem-1/introduction/content.json +++ b/curriculum/sas/investigation-4/problem-1/introduction/content.json @@ -3,59 +3,86 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "We can enhance a report or story by adding photographs, drawings, or diagrams. If we place a graphic in an electronic document, we can enlarge, reduce, or move it. When we click on the graphic, it appears inside a frame with handles along the sides, such as the figure shown below." + "We can enhance a report or story by adding photographs, drawings, or diagrams. If we place a graphic in an electronic document, we can enlarge, reduce, or move it. When we click on the graphic, it appears inside a frame with handles along the sides, such as the figure shown below.
" ] } }, - {"id": "-6wzAUG202201df4at43q56pM", "title": "Original image", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_1_In_28_fish_350w.png"}}, - {"content": {"type": "Text", "format": "html", "text": ["We can change the size and shape of the image by dragging the handles."]}}, - {"id": "-6wzAUG202201df47pM", "title": "Stretched images", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_1_In_29_fish_resized_350w.png"}}, - {"content": {"type": "Text", "format": "html", "text": ["How did this technique produce these variations of the original shape? Which of these images appears to be similar to the original? Why?"]}}, { + "id": "-6wzAUG202201df4at43q56pM", + "title": "Original image", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_In_28_fish_350w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "We can change the size and shape of the image by dragging the handles.
" + ] + } + }, + { + "id": "-6wzAUG202201df47pM", + "title": "Stretched images", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_In_29_fish_resized_350w.png" + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "How did this technique produce these variations of the original shape? Which of these images appears to be similar to the original? Why?
" + ] + } + }, + { + "id": "document_Text_4", "content": { "type": "Text", "format": "html", "text": [ - "Recall from our work in the Comparing Quantities unit that a ratio is a comparison of two quantities such as two lengths. The rectangle around the original photo is about 10 centimeters tall and 8 centimeters wide. We can say
", - "For every 10 cm of height there are 8 cm of width.", - "Or", - "The ratio of height to width is 10 to 8.", - "This table gives the ratios of height to width for the images.
" + "Recall from our work in the Comparing Quantities unit that a ratio is a comparison of two quantities such as two lengths. The rectangle around the original photo is about 10 centimeters tall and 8 centimeters wide. We can say
For every 10 cm of height there are 8 cm of width.OrThe ratio of height to width is 10 to 8.
This table gives the ratios of height to width for the images.
" ] } }, - {"id": "-6wzAUG202201dardtf47pM", "title": "What do you notice about the height-to-width ratios?", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_1_In_30_image_table_350w.png"}}, { + "id": "-6wzAUG202201dardtf47pM", + "title": "What do you notice about the height-to-width ratios?", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_In_30_image_table_350w.png" + } + }, + { + "id": "document_Text_5", "content": { "type": "Text", "format": "html", "text": [ - "The comparisons “10cm to 8cm” and “5cm to 4cm” are equivalent ratios. We can scale the ratio 10 to 8 down by multiplying each quantity by 1/2. Or we could scale the ratio 5 to 4 up by multiplying each quantity by 2.
", - "Equivalent ratios are like equivalent fractions. In fact, ratios are often written in fraction form. You can express equivalent ratios with equations. A proportion is an equation stating that two ratios are equal.
", - "For every 10 cm of height there are 8 cm of width
", - "10 to 8 equals 5 to 4
", - " 10 cm height 5 cm height", - "_________________ = ___________________", - " 8 cm width 4 cm width" + "The comparisons “10cm to 8cm” and “5cm to 4cm” are equivalent ratios. We can scale the ratio 10 to 8 down by multiplying each quantity by 1/2. Or we could scale the ratio 5 to 4 up by multiplying each quantity by 2.
Equivalent ratios are like equivalent fractions. In fact, ratios are often written in fraction form. You can express equivalent ratios with equations. A proportion is an equation stating that two ratios are equal.
For every 10 cm of height there are 8 cm of width
10 to 8 equals 5 to 4
10 cm height 5 cm height_________________ = ___________________ 8 cm width 4 cm width
" ] } }, { + "id": "document_Text_6", "content": { "type": "Text", "format": "html", "text": [ - "We can also say:", - "For every 8 cm of width there are 10 cm in height or 8 to 10.", - "How can you express this in fraction form?
", - "What information does each ratio written in fraction fraction form represent in the similar figures?", - "For the set of figures of the student holding the fish, the original figure is similar to the figure on the right. Notice that the ratios are equal.
", - "We know that a scale factor relates each length in a figure to the corresponding length in its image. In this problem we will explore ratios of adjacent side lengths within figures.", - "For the diagrams in this problem, all measurements are drawn to scale unless otherwise noted." + "We can also say:For every 8 cm of width there are 10 cm in height or 8 to 10.
How can you express this in fraction form?
What information does each ratio written in fraction fraction form represent in the similar figures?
For the set of figures of the student holding the fish, the original figure is similar to the figure on the right. Notice that the ratios are equal.
We know that a scale factor relates each length in a figure to the corresponding length in its image. In this problem we will explore ratios of adjacent side lengths within figures.For the diagrams in this problem, all measurements are drawn to scale unless otherwise noted.
" ] } } diff --git a/curriculum/sas/investigation-4/problem-1/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-4/problem-1/nowWhatDoYouKnow/content.json index dbbfbc00a..a8e68e999 100644 --- a/curriculum/sas/investigation-4/problem-1/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-4/problem-1/nowWhatDoYouKnow/content.json @@ -2,16 +2,32 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["What information do the ratios of adjacent side lengths within two similar figures provide about similar figures? How are these ratios helpful in solving problems?"]}}, - {"id": "-AUG20220211PM", "title": "Did You Know?: Non-rectangular buildings", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_1_DYK.jpg"}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "What information do the ratios of adjacent side lengths within two similar figures provide about similar figures? How are these ratios helpful in solving problems?
" + ] + } + }, + { + "id": "-AUG20220211PM", + "title": "Did You Know?: Non-rectangular buildings", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_DYK.jpg" + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "If two shapes have corresponding angles with the same measure and the ratios of adjacent side lengths are equivalent, the shapes are similar. If the ratios of corresponding adjacent side lengths are equal, the multiplicative relationship is the same which means the shape lengths are scaled in the same way.
", - "These ratios are helpful when you find missing side lengths related to two similar figures.
" + "If two shapes have corresponding angles with the same measure and the ratios of adjacent side lengths are equivalent, the shapes are similar. If the ratios of corresponding adjacent side lengths are equal, the multiplicative relationship is the same which means the shape lengths are scaled in the same way.
These ratios are helpful when you find missing side lengths related to two similar figures.
" ] } } diff --git a/curriculum/sas/investigation-4/problem-1/whatIf/content.json b/curriculum/sas/investigation-4/problem-1/whatIf/content.json index d662eabf5..690e69003 100644 --- a/curriculum/sas/investigation-4/problem-1/whatIf/content.json +++ b/curriculum/sas/investigation-4/problem-1/whatIf/content.json @@ -2,8 +2,24 @@ "type": "whatIf", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["Students in Ms. Kelly’s class used different strategies to decide which of the following triangles were similar. Examine each strategy. Is it correct? Explain why.
" + ] + } + }, + { + "id": "21AUG20200150pm", + "title": "Triangles A, B, C, and D", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_IC_33_triangles_350w.png" + } + }, { "id": "NBABTiigdVH6JWFi", "title": "Text 5", @@ -11,28 +27,18 @@ "type": "Text", "format": "html", "text": [ - "Rolland’s Strategy
", - "", - "
If two triangles are similar, then corresponding angles are equal.
", - "So, I found the angles of each triangle.
", - "Triangles A, C, and D have corresponding equal angles. I checked the corresponding ratio of adjacent sides and found that they were equal.
", - "So, triangles A, C, and D are similar.
" + "Rolland’s Strategy
If two triangles are similar, then corresponding angles are equal.
So, I found the angles of each triangle.
Triangles A, C, and D have corresponding equal angles. I checked the corresponding ratio of adjacent sides and found that they were equal.
So, triangles A, C, and D are similar.
" ] } }, { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Triangles: A, C, and D are similar. The corresponding angle measures of those triangles are congruent. (Note: Students have to use the fact that the sum of the angle measures in a triangle is 180˚. More exact measures of the angles for the triangles are 29.99˚, 61.02˚, and 88.98˚.)", - "
Ratio of adjacent side lengths – longest side to short side lengths:
", - "Triangle A: 8 to 4 = 2 to 1
", - "Triangle C: 12 to 6 = 2 to 1
", - "Triangle D: 20 to 10 = 2 to 1
", - "Triangle B: 12 to 9 = 1 1/3 to 1
", - "The unit rate of the length of one side to the length of an adjacent side is equivalent for all three similar triangles. The triangle that is not similar to the others has a different rate.
" + "Triangles: A, C, and D are similar. The corresponding angle measures of those triangles are congruent. (Note: Students have to use the fact that the sum of the angle measures in a triangle is 180˚. More exact measures of the angles for the triangles are 29.99˚, 61.02˚, and 88.98˚.)
Ratio of adjacent side lengths – longest side to short side lengths:
Triangle A: 8 to 4 = 2 to 1
Triangle C: 12 to 6 = 2 to 1
Triangle D: 20 to 10 = 2 to 1
Triangle B: 12 to 9 = 1 1/3 to 1
The unit rate of the length of one side to the length of an adjacent side is equivalent for all three similar triangles. The triangle that is not similar to the others has a different rate.
" ] } }, @@ -43,57 +49,133 @@ "type": "Text", "format": "html", "text": [ - "Jessica’s Strategy
", - "", - "
I found the scale factor for corresponding sides.
", - "The scale factor from triangle A to triangle C is 3/2 or 1.5. That is, we can multiple a side length of triangle A by 1.5 to get the side length of the corresponding side length in Triangle C.
", - "We can also say the scale factor from triangle C to A is 2/3 or 0.666…
", - "Since each side is scaled up by the same scale factor triangles A and C are similar.
", - "I used this method to show that triangle A is similar to triangle D. So, A, C, and D are similar triangles.
" + "Jessica’s Strategy
I found the scale factor for corresponding sides.
The scale factor from triangle A to triangle C is 3/2 or 1.5. That is, we can multiple a side length of triangle A by 1.5 to get the side length of the corresponding side length in Triangle C.
We can also say the scale factor from triangle C to A is 2/3 or 0.666…
Since each side is scaled up by the same scale factor triangles A and C are similar.
I used this method to show that triangle A is similar to triangle D. So, A, C, and D are similar triangles.
" ] } }, { - "display": "teacher", "id": "SZ3g0U6mQJ0BbPAu", "title": "Text 6", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "The strategy works.
", - "Triangles: A, C, and D are similar.
", - "The corresponding angle measures of those triangles are congruent.
", - "Note: Students have to use the fact that the sum of the angle measures in a triangle is 180˚. More exact measures of the angles for the triangles are 29.99˚, 61.02˚, and 88.98˚.
", - "The scale factors are:
" + "The strategy works.
Triangles: A, C, and D are similar.
The corresponding angle measures of those triangles are congruent.
Note: Students have to use the fact that the sum of the angle measures in a triangle is 180˚. More exact measures of the angles for the triangles are 29.99˚, 61.02˚, and 88.98˚.
The scale factors are:
" ] } }, - {"display": "teacher", "id": "21AUG20200151pm", "title": "Scale factors for similar Triangles A, C, and D", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_Initial_Challenge_2.png"}}, + { + "id": "21AUG20200151pm", + "title": "Scale factors for similar Triangles A, C, and D", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_Initial_Challenge_2.png" + } + }, { "id": "tkGNAXnwxXBo4M4s", "title": "Text 10", "content": { "type": "Text", "format": "html", - "text": ["If we know two figures are similar, we can use this information to finding missing measurements. The pairs of figures in each set are similar. Find the missing side lengths x or y in each pair. Explain your reasoning.
"] + "text": [ + "If we know two figures are similar, we can use this information to finding missing measurements. The pairs of figures in each set are similar. Find the missing side lengths x or y in each pair. Explain your reasoning.
" + ] + } + }, + { + "id": "-AUG20220204PM", + "title": "Four sets of similar figures with missing side lengths", + "content": { + "type": "Image", + "url": "sas/images/SS_4_1_WhatIf_4Shapes.jpg" + } + }, + { + "id": "-AUG20220205PM", + "title": "Sample reasoning for similar triangles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_What_If_Set_4.png" } }, - {"id": "-AUG20220204PM", "title": "Four sets of similar figures with missing side lengths", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_1_WhatIf_4Shapes.jpg"}}, - {"display": "teacher", "id": "-AUG20220205PM", "title": "Sample reasoning for similar triangles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_What_If_Set_4.png"}}, - {"display": "teacher", "id": "-AUG20220206PM", "title": "Sample reasoning for similar rectangles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_What_If_Set_5.png"}}, - {"display": "teacher", "id": "-AUG20220207PM", "title": "Sample reasoning for similar parallelograms", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_What_If_Set_6.png"}}, - {"display": "teacher", "id": "-AUG20220208PM", "title": "Sample reasoning for irregular figures", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/reasoningIrregular4_1.png"}}, - {"content": {"type": "Text", "format": "html", "text": ["Yes. I proportion can be solved to find the distance from Stake 3 to Tree 1.
"]}}, - {"display": "teacher", "id": "-AUG20220210PM", "title": "Sample reasoning to find the missing side length", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-1_What_If_8.jpg"}}, { + "id": "-AUG20220206PM", + "title": "Sample reasoning for similar rectangles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_What_If_Set_5.png" + } + }, + { + "id": "-AUG20220207PM", + "title": "Sample reasoning for similar parallelograms", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_What_If_Set_6.png" + } + }, + { + "id": "-AUG20220208PM", + "title": "Sample reasoning for irregular figures", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/reasoningIrregular4_1.png" + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Is Alejandra correct? Explain why or why not.Alejandra’s Strategy I can use the ratio of adjacent sides to find the distance across the river in Problem 3.3.
" + ] + } + }, + { + "id": "-AUG20220209PM", + "title": "Diagram of the river with similar triangles", + "content": { + "type": "Image", + "url": "sas/images/4-1_What_If_B.png" + } + }, + { + "id": "document_Text_4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Yes. I proportion can be solved to find the distance from Stake 3 to Tree 1.
" + ] + } + }, + { + "id": "-AUG20220210PM", + "title": "Sample reasoning to find the missing side length", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-1_What_If_8.jpg" + } + }, + { + "id": "document_Text_5", "display": "teacher", "content": { "type": "Text", "format": "html", - "text": ["This gives a side length of 120 feet for the short side of the larger triangle. To find the distance across the river, we have to subtract the 30 feet from Stake 1 to Stake 3. That gives us a distance of 90 feet across the river.
"] + "text": [ + "This gives a side length of 120 feet for the short side of the larger triangle. To find the distance across the river, we have to subtract the 30 feet from Stake 1 to Stake 3. That gives us a distance of 90 feet across the river.
" + ] } } ] diff --git a/curriculum/sas/investigation-4/problem-2/initialChallenge/content.json b/curriculum/sas/investigation-4/problem-2/initialChallenge/content.json index d91a7d991..4f430fb2e 100644 --- a/curriculum/sas/investigation-4/problem-2/initialChallenge/content.json +++ b/curriculum/sas/investigation-4/problem-2/initialChallenge/content.json @@ -2,17 +2,35 @@ "type": "initialChallenge", "content": { "tiles": [ - {"id": "HVO_UABj7CO7pYUY", "title": "Text 1", "content": {"type": "Text", "format": "html", "text": ["Below are descriptions for two experiments that can help us find the height of an object using similar triangles.
"]}}, { + "id": "HVO_UABj7CO7pYUY", + "title": "Text 1", "content": { "type": "Text", "format": "html", "text": [ - "One method for finding heights of objects is called the “mirror method”. Ashton’s class experiments with the mirror method. They want to understand how it works. They use it to measure the height of their principal. From science class, they knew that light reflects off a mirror at the same angle (angle of reflection) at which it hits the mirror (angle of incidence). This creates two similar right triangles." + "Below are descriptions for two experiments that can help us find the height of an object using similar triangles.
" ] } }, - {"id": "21AUG2022M20214pm", "title": "Mirror method", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_2_Mirror_IC.png"}}, + { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "One method for finding heights of objects is called the “mirror method”. Ashton’s class experiments with the mirror method. They want to understand how it works. They use it to measure the height of their principal. From science class, they knew that light reflects off a mirror at the same angle (angle of reflection) at which it hits the mirror (angle of incidence). This creates two similar right triangles.
" + ] + } + }, + { + "id": "21AUG2022M20214pm", + "title": "Mirror method", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_Mirror_IC.png" + } + }, { "id": "Kgs1t9rZB89gXWnX", "title": "Text 2", @@ -20,52 +38,99 @@ "type": "Text", "format": "html", "text": [ - "On a sunny day, any upright object casts a shadow. A middle school class used the shadow method to measure the Statue of Liberty. The diagram shows two triangles.
", - "The triangles sides are the height of the object, the length of the objects shadow, and the side connecting these two points. This creates two similar right triangles.
" + "On a sunny day, any upright object casts a shadow. A middle school class used the shadow method to measure the Statue of Liberty. The diagram shows two triangles.
The triangles sides are the height of the object, the length of the objects shadow, and the side connecting these two points. This creates two similar right triangles.
" + ] + } + }, + { + "id": "21AUG2022M20217pm", + "title": "Shadow Method", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_IC_39_statue_liberty_500w.png" + } + }, + { + "id": "document_Text_2", + "content": { + "type": "Text", + "format": "html", + "text": [ + "The triangles are scaled. The angles located at the mirror are congruent. If we imagined flipping the triangle created by the distance from the mirror to Ashton, we can see the triangles are similar. These triangles look like the ones that we created with the rep-tiles and with measuring the river distance.
" + "Mirror Method
The triangles are scaled. The angles located at the mirror are congruent. If we imagined flipping the triangle created by the distance from the mirror to Ashton, we can see the triangles are similar. These triangles look like the ones that we created with the rep-tiles and with measuring the river distance.
" ] } }, - {"display": "teacher", "id": "21AUG2022M20215pm", "title": "Diagram showing similar triangles in the mirror method", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_2_Initial_Challenge_2.png"}}, { + "id": "21AUG2022M20215pm", + "title": "Diagram showing similar triangles in the mirror method", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_Initial_Challenge_2.png" + } + }, + { + "id": "document_Text_4", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Shadow Method", - "The statue and the stick are at a right angle to the ground. Another angle is formed by the sun and the ground. For two nearby points at a common time, the sun appears at the same angle, making these corresponding angles congruent. The third angle must be the same in each triangle since all three interior angles of a triangle must add to 180 degrees.", - "The length of the shadow depends on the height of the object. The shadow of the taller object will be longer. The stick and its shadow are two legs of the right triangle, and the statue and its shadow also form a right triangle. These two triangles are similar. You can compare the lengths of shadows, and then you will get the scale factor. Then you can find the height of the statue using the scale factor and the length of the stick. " + "Shadow Method
The statue and the stick are at a right angle to the ground. Another angle is formed by the sun and the ground. For two nearby points at a common time, the sun appears at the same angle, making these corresponding angles congruent. The third angle must be the same in each triangle since all three interior angles of a triangle must add to 180 degrees.The length of the shadow depends on the height of the object. The shadow of the taller object will be longer. The stick and its shadow are two legs of the right triangle, and the statue and its shadow also form a right triangle. These two triangles are similar. You can compare the lengths of shadows, and then you will get the scale factor. Then you can find the height of the statue using the scale factor and the length of the stick.
" ] } }, - {"content": {"type": "Text", "format": "html", "text": ["Principal
", "72 inches from the floor to the principal’s eyes.
"]}}, - {"display": "teacher", "id": "21AUG2022M20216pm", "title": "Sample reasoning to find the principal’s height", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_2_Initial_Challenge_3.png"}}, { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Principal
72 inches from the floor to the principal’s eyes.
" + ] + } + }, + { + "id": "21AUG2022M20216pm", + "title": "Sample reasoning to find the principal’s height", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_Initial_Challenge_3.png" + } + }, + { "id": "xBNE3N6-nY7NutSb", "title": "Text 4", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Statue of Liberty
", - "We cannot tell the height of the statue without knowing the measurements. To find the height, we can compare the lengths of shadows to get the scale factor. Then you can find the height of the statue using the scale factor and the length of the stick.
", - "Statue shadow ÷ stick shadow → gives scale factor
", - "Scale factor • height of stick → height of statue
" + "Statue of Liberty
We cannot tell the height of the statue without knowing the measurements. To find the height, we can compare the lengths of shadows to get the scale factor. Then you can find the height of the statue using the scale factor and the length of the stick.
Statue shadow ÷ stick shadow → gives scale factor
Scale factor • height of stick → height of statue
" ] } } diff --git a/curriculum/sas/investigation-4/problem-2/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-4/problem-2/nowWhatDoYouKnow/content.json index b05fbcb21..a00db2d19 100644 --- a/curriculum/sas/investigation-4/problem-2/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-4/problem-2/nowWhatDoYouKnow/content.json @@ -2,16 +2,24 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["If two figures are similar, how can you use information about the figures to find unknown lengths, perimeters, areas, or angle measures?"]}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "If two figures are similar, how can you use information about the figures to find unknown lengths, perimeters, areas, or angle measures?
" + ] + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "For lengths and perimeters, you can use the scale factor and/or the ratio of adjacent side lengths. When two figures are similar, the ratios of corresponding adjacent side lengths will be equal. Also, when two figures are similar, the ratio of corresponding side lengths across two figures will be equal.
", - "For areas, you can use the scale factor. When the scale factor from figure A to figure B is , the area of the figure B will be a times a, or a2 times the area of the figure A.
", - "For angle measures, you can use the fact that the corresponding angles measures in two similar figures are equal. You can find missing angle measures by looking at corresponding angle measures in the similar figure.
" + "For lengths and perimeters, you can use the scale factor and/or the ratio of adjacent side lengths. When two figures are similar, the ratios of corresponding adjacent side lengths will be equal. Also, when two figures are similar, the ratio of corresponding side lengths across two figures will be equal.
For areas, you can use the scale factor. When the scale factor from figure A to figure B is , the area of the figure B will be a times a, or a2 times the area of the figure A.
For angle measures, you can use the fact that the corresponding angles measures in two similar figures are equal. You can find missing angle measures by looking at corresponding angle measures in the similar figure.
" ] } }, @@ -22,13 +30,19 @@ "type": "Text", "format": "html", "text": [ - "Did You Know?
", - "Special cameras on satellites, airplanes, and ships take images of large areas on earth. They use the images to calculate lengths and areas of shapes. This process is called remote sensing. Some use of remote sensing is tracking forest fires, erupting volcanoes, ocean floor, growth of cities or forests,
", - "https://www.usgs.gov/faqs/what-does-georeferenced-mean?qt-news_science_products=0#qt-news_science_products
" + "Did You Know?
Special cameras on satellites, airplanes, and ships take images of large areas on earth. They use the images to calculate lengths and areas of shapes. This process is called remote sensing. Some use of remote sensing is tracking forest fires, erupting volcanoes, ocean floor, growth of cities or forests,
https://www.usgs.gov/faqs/what-does-georeferenced-mean?qt-news_science_products=0#qt-news_science_products
" ] } }, - {"id": "75CjbzNx65gXDxBN", "title": "Satellite Photography", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/satellitePhotography.png", "filename": "curriculum/stretching-and-shrinking/images/satellitePhotography.png"}}, + { + "id": "75CjbzNx65gXDxBN", + "title": "Satellite Photography", + "content": { + "type": "Image", + "url": "sas/images/satellitePhotography.png", + "filename": "sas/images/satellitePhotography.png" + } + }, [ { "id": "e8nNwJ9kewksRjzF", @@ -37,13 +51,19 @@ "type": "Text", "format": "html", "text": [ - "Georeferencing means that the internal coordinate system of a digital map or aerial photo can be related to a ground system of geographic coordinates.
", - "A georeferenced digital map or image has been tied to a known Earth coordinate system, so users can determine where every point on the map or aerial photo is located on the Earth's surface.
", - "https://www.usgs.gov/faqs/what-does-georeferenced-mean?qt-news_science_products=0#qt-news_science_products
" + "Georeferencing means that the internal coordinate system of a digital map or aerial photo can be related to a ground system of geographic coordinates.
A georeferenced digital map or image has been tied to a known Earth coordinate system, so users can determine where every point on the map or aerial photo is located on the Earth's surface.
https://www.usgs.gov/faqs/what-does-georeferenced-mean?qt-news_science_products=0#qt-news_science_products
" ] } }, - {"id": "uiQTIoGN0awEH10M", "title": "Georeferencing", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/survey.png", "filename": "curriculum/stretching-and-shrinking/images/survey.png"}} + { + "id": "uiQTIoGN0awEH10M", + "title": "Georeferencing", + "content": { + "type": "Image", + "url": "sas/images/survey.png", + "filename": "sas/images/survey.png" + } + } ], { "id": "4ARO2ZR2ty2IzBl-", diff --git a/curriculum/sas/investigation-4/problem-2/whatIf/content.json b/curriculum/sas/investigation-4/problem-2/whatIf/content.json index fcab88fa1..9fba11cc9 100644 --- a/curriculum/sas/investigation-4/problem-2/whatIf/content.json +++ b/curriculum/sas/investigation-4/problem-2/whatIf/content.json @@ -9,17 +9,7 @@ "type": "Text", "format": "html", "text": [ - "Situation A: The Experiments
", - "1. Use the mirror method to find the height of a tall object in your school.
", - "The Mirror Experiment
", - "", - "
Equipment
", - "Instructions for the Experiment
", - "Note that you will need to form two right triangles.
", - "Situation A: The Experiments
1. Use the mirror method to find the height of a tall object in your school.
The Mirror Experiment
Equipment
Instructions for the Experiment
Note that you will need to form two right triangles.
2. Use the shadow method to find the height of a tall object near your school.
", - "The Shadow Experiment
", - "Equipment
", - "Instructions for the Experiment
", - "Note that you will need to form two right triangles.
", - "2. Use the shadow method to find the height of a tall object near your school.
The Shadow Experiment
Equipment
Instructions for the Experiment
Note that you will need to form two right triangles.
Student results will vary. The strategies give approximate measurements.
Learning to limit the variables that impact the measures takes some time and experience. Students will get “messy” data. When looking at results of groups who measured the same item, variables that impact the differences can be discussed.
The applications allow students to see a use of similarity.
Note: These strategies are used to get “indirect” measures by people working in various fields such as outside design and construction.
" + ] + } + }, + { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Cameras on satellites or planes are used to find distances on earth. The following figure shows a tree and its image in a camera. The two triangles created are similar.
If the height of the image is 14 mm, the focal length is 35 mm, and the distance from the object is 10 m. What is the height of the tree?
" + ] + } + }, + { + "id": "21AUG2022M20218pm", + "title": "Labeled diagram of similar triangles created by camera lenses", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_WhatIf_B_Ans.jpg" + } + }, + { + "id": "21AUG2022M20219pm", + "title": "Diagram of similar triangles created by camera lenses", + "content": { + "type": "Image", + "url": "sas/images/SS_4_2_Camera.png" + } + }, + { + "id": "document_Text_2", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Student results will vary. The strategies give approximate measurements.
", - "Learning to limit the variables that impact the measures takes some time and experience. Students will get “messy” data. When looking at results of groups who measured the same item, variables that impact the differences can be discussed.
", - "The applications allow students to see a use of similarity.
", - "Note: These strategies are used to get “indirect” measures by people working in various fields such as outside design and construction.
" + "Using ratio of adjacent sides reasoning:
" ] } }, { + "id": "21AUG2022M20220pm", + "title": "Sample reasoning using ratio of adjacent sides", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-2_What_If_Situation_B_2.png" + } + }, + { + "id": "document_Text_3", + "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "If the height of the image is 14 mm, the focal length is 35 mm, and the distance from the object is 10 m. What is the height of the tree?
" + "Using scale factor reasoning:
" ] } }, - {"display": "teacher", "id": "21AUG2022M20218pm", "title": "Labeled diagram of similar triangles created by camera lenses", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_2_WhatIf_B_Ans.jpg"}}, - {"id": "21AUG2022M20219pm", "title": "Diagram of similar triangles created by camera lenses", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_2_Camera.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Using ratio of adjacent sides reasoning:
"]}}, - {"id": "21AUG2022M20220pm", "title": "Sample reasoning using ratio of adjacent sides", "display": "teacher", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-2_What_If_Situation_B_2.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Using scale factor reasoning:
"]}}, - {"display": "teacher", "id": "21AUG2022M20221pm", "title": "Sample reasoning using scale factor", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-2_What_If_Situation_B_3.png"}} + { + "id": "21AUG2022M20221pm", + "title": "Sample reasoning using scale factor", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-2_What_If_Situation_B_3.png" + } + } ] }, "supports": [] diff --git a/curriculum/sas/investigation-4/problem-3/initialChallenge/content.json b/curriculum/sas/investigation-4/problem-3/initialChallenge/content.json index e97fdff89..81b635183 100644 --- a/curriculum/sas/investigation-4/problem-3/initialChallenge/content.json +++ b/curriculum/sas/investigation-4/problem-3/initialChallenge/content.json @@ -3,129 +3,340 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", "text": [ - "The Art Club created sets of figures, some of which had an imposter.
", - "For each set,
", - "The Art Club created sets of figures, some of which had an imposter.
For each set,
For measurements, see Teaching Aid 4.3.
", "Rectangles 2 and 3 are similar
"]}}, - {"display": "teacher", "id": "21AUG20220241PM", "title": "Geometric reasoning for similar Rectangles 2 and 3", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_6.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Ratio reasoning
"]}}, - {"display": "teacher", "id": "21AUG20220242PM", "title": "Ratio reasoning for similar and non-similar rectangles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_7.png"}}, { + "id": "document_Text_2", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "For measurements, see Teaching Aid 4.3.
Rectangles 2 and 3 are similar
" + ] + } + }, + { + "id": "21AUG20220241PM", + "title": "Geometric reasoning for similar Rectangles 2 and 3", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_6.png" + } + }, + { + "id": "document_Text_3", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Ratio reasoning
" + ] + } + }, + { + "id": "21AUG20220242PM", + "title": "Ratio reasoning for similar and non-similar rectangles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_7.png" + } + }, + { + "id": "document_Text_4", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Possible Reasoning:
Rectangle #1 is not similar to the #2 or #3.
From #1 to #2, corresponding sides grow by 2 (short side) or 3 (long side).
From #1 to #3, corresponding side grow by 3 (short side) or 4.5 (long side).
The ratio of short to long sides for the rectangle #1 would not be equivalent to the ratio of short to long sides for either #2 or #3.
" + ] + } + }, + { + "id": "21AUG20220243PM", + "title": "Geometric reasoning for non-similar Rectangle 1", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_4.png" + } + }, + { + "id": "document_Text_5", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Rectangles #2 and #3 are similar
Corresponding angles are equivalent. All angles are 90˚ in rectangles.
Comparing rectangle #2 to rectangle #3
Scale Reasoning:
From #2 to# 3, scale factor is 1.5.
From #3 to #2, scale factor is 2/3.
" + ] + } + }, + { + "id": "document_Text_6", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Stars 1 and 3 are similar
Possible Reasoning:
Star #2 is not a scale drawing because corresponding angles are not equivalent to either Star #1 or #3.
Scale Reasoning
" + ] + } + }, + { + "id": "21AUG20220244PM", + "title": "Scale factor reasoning for similar Stars 1 and 3", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_3.png" + } + }, + { + "id": "document_Text_7", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Ratio Reasoning:
" + ] + } + }, + { + "id": "21AUG20220245PM", + "title": "Ratio reasoning for similar and non-similar stars", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_5.png" + } + }, + { + "id": "document_Text_8", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Flags 1 and 3 are similar
Possible Reasoning:
All corresponding angles have the same measures in all three flags.
The triangle on Flag #1 and #2 are congruent. Students must use the measures of the whole shape including the pole. The length of the pole makes Flag #2 not similar to the other flags.
All corresponding angles have the same measures in all three flags.
Scale Reasoning:
" + ] + } + }, + { + "id": "21AUG20220246PM", + "title": "Scale factor reasoning for similar Triangles 1 and 3", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_10.png" + } + }, + { + "id": "document_Text_9", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Ratio Reasoning:
Shape #1 is small and difficult to get an accurate measure. But with the ratios, it shows that Shape #1 and Shape #3 almost have equivalent ratios. (within our measuring error)
" + ] + } + }, + { + "id": "21AUG20220247PM", + "title": "Ratio reasoning for similar and non-similar triangles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_11.png" + } + }, + { + "id": "document_Text_10", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Circles – all circles are similar to other circles
Possible Reasoning:
All circles are the same shape. Any radius can be scaled to find a corresponding radius. Any diameter can be scaled to find a corresponding diameter.
" + ] + } + }, + { + "id": "21AUG20220248PM", + "title": "Ratio reasoning for circles", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_11.png" + } + }, + { + "id": "document_Text_11", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Possible Reasoning:
", - "Rectangle #1 is not similar to the #2 or #3.
", - "From #1 to #2, corresponding sides grow by 2 (short side) or 3 (long side).
", - "From #1 to #3, corresponding side grow by 3 (short side) or 4.5 (long side).
", - "The ratio of short to long sides for the rectangle #1 would not be equivalent to the ratio of short to long sides for either #2 or #3.
" + "Squares – all squares are similar to other squares
" ] } }, - {"display": "teacher", "id": "21AUG20220243PM", "title": "Geometric reasoning for non-similar Rectangle 1", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_4.png"}}, { + "id": "21AUG20220249PM", + "title": "Ratio reasoning for squares", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_11.png" + } + }, + { + "id": "document_Text_12", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Rectangles #2 and #3 are similar
", - "Corresponding angles are equivalent. All angles are 90˚ in rectangles.
", - "Comparing rectangle #2 to rectangle #3
", - "Scale Reasoning:
", - "From #2 to# 3, scale factor is 1.5.
", - "From #3 to #2, scale factor is 2/3.
" + "Possible Reasoning:
The corresponding angles will be 90˚.
Scale Reasoning:
For corresponding side lengths, you can always find a scale factor.
Ratio Reasoning:
Adjacent sides will always be equivalent ratios of side to side.
" ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Stars 1 and 3 are similar
", "Possible Reasoning:
", "Star #2 is not a scale drawing because corresponding angles are not equivalent to either Star #1 or #3.
", "Scale Reasoning
"]}}, - {"display": "teacher", "id": "21AUG20220244PM", "title": "Scale factor reasoning for similar Stars 1 and 3", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_3.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Ratio Reasoning:"]}}, - {"display": "teacher", "id": "21AUG20220245PM", "title": "Ratio reasoning for similar and non-similar stars", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_5.png"}}, { + "id": "document_Text_13", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Flags 1 and 3 are similar
", - "Possible Reasoning:
", - "All corresponding angles have the same measures in all three flags.
", - "The triangle on Flag #1 and #2 are congruent. Students must use the measures of the whole shape including the pole. The length of the pole makes Flag #2 not similar to the other flags.
", - "All corresponding angles have the same measures in all three flags.
", - "Scale Reasoning:
" + "Hats 1 and 3 are similar
Possible Reasoning:
Why Shape #2 is not a scale drawing:
" ] } }, - {"display": "teacher", "id": "21AUG20220246PM", "title": "Scale factor reasoning for similar Triangles 1 and 3", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_10.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Ratio Reasoning:
", "Shape #1 is small and difficult to get an accurate measure. But with the ratios, it shows that Shape #1 and Shape #3 almost have equivalent ratios. (within our measuring error)
"]}}, - {"display": "teacher", "id": "21AUG20220247PM", "title": "Ratio reasoning for similar and non-similar triangles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_11.png"}}, { + "id": "21AUG20220250PM", + "title": "Ratio reasoning for similar and non-similar hats", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_16.png" + } + }, + { + "id": "document_Text_14", "display": "teacher", "content": { "type": "Text", "format": "html", - "text": ["Circles – all circles are similar to other circles
", "Possible Reasoning:
", "All circles are the same shape. Any radius can be scaled to find a corresponding radius. Any diameter can be scaled to find a corresponding diameter.
"] + "text": [ + "Hats #1 and #3 are similar
Corresponding angles are equivalent
Scale Reasoning:
Shape #1 to Shape# 2 is scale factor = 2.
Shape #2 to Shape #1 is scale factor = ½ .
" + ] } }, - {"display": "teacher", "id": "21AUG20220248PM", "title": "Ratio reasoning for circles", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_11.png"}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Squares – all squares are similar to other squares
"]}}, - {"display": "teacher", "id": "21AUG20220249PM", "title": "Ratio reasoning for squares", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_11.png"}}, { + "id": "21AUG20220251aPM", + "title": "Geometric reasoning for similar Hats 1 and 3", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Possible Reasoning:
", - "The corresponding angles will be 90˚.
", - "Scale Reasoning:
", - "For corresponding side lengths, you can always find a scale factor.
", - "Ratio Reasoning:
", - "Adjacent sides will always be equivalent ratios of side to side.
" + "Ratio Reasoning:
" ] } }, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Hats 1 and 3 are similar
", "Possible Reasoning:
", "Why Shape #2 is not a scale drawing:
"]}}, - {"display": "teacher", "id": "21AUG20220250PM", "title": "Ratio reasoning for similar and non-similar hats", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_16.png"}}, { + "id": "21AUG20220252PM", + "title": "Geometric reasoning for similar Hats 1 and 3", "display": "teacher", - "content": {"type": "Text", "format": "html", "text": ["Hats #1 and #3 are similar
", "Corresponding angles are equivalent
", "Scale Reasoning:
", "Shape #1 to Shape# 2 is scale factor = 2.
", "Shape #2 to Shape #1 is scale factor = ½ .
"]} + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_17.png" + } }, - {"display": "teacher", "id": "21AUG20220251aPM", "title": "Geometric reasoning for similar Hats 1 and 3", "content": {"type": "Text", "format": "html", "text": ["Ratio Reasoning:
"]}}, - {"display": "teacher", "id": "21AUG20220252PM", "title": "Geometric reasoning for similar Hats 1 and 3", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_17.png"}}, - {"display": "teacher", "id": "21AUG20220455PM", "title": "Ratio reasoning for similar and non-similar hats", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/4-3_Initial_Challenge_18.png"}}, { + "id": "21AUG20220455PM", + "title": "Ratio reasoning for similar and non-similar hats", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/4-3_Initial_Challenge_18.png" + } + }, + { + "id": "document_Text_15", "display": "teacher", "content": { "type": "Text", - "format": "markdown", + "format": "html", "text": [ - "Corresponding lengths of similar figures increase by the scale factor.", - "Corresponding angles of similar figures have the same measure.", - "Perimeters are lengths, so they increase by the scale factor.", - "Areas increase by the scale factor • scale factor because the length has a scale factor increase in two dimensions." + "" ] } } diff --git a/curriculum/sas/investigation-4/problem-3/nowWhatDoYouKnow/content.json b/curriculum/sas/investigation-4/problem-3/nowWhatDoYouKnow/content.json index 220e83464..7c1b3ac75 100644 --- a/curriculum/sas/investigation-4/problem-3/nowWhatDoYouKnow/content.json +++ b/curriculum/sas/investigation-4/problem-3/nowWhatDoYouKnow/content.json @@ -2,18 +2,43 @@ "type": "nowWhatDoYouKnow", "content": { "tiles": [ - {"content": {"type": "Text", "format": "html", "text": ["What are strategies for identifying if shapes have been scaled (similar figures) or if the shapes are imposters?"]}}, - {"id": "21AUG20220503PM", "title": "Did You Know?: Non-rectangular buildings", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/SS_4_3_NWDYK.png"}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "What are strategies for identifying if shapes have been scaled (similar figures) or if the shapes are imposters?
" + ] + } + }, + { + "id": "21AUG20220503PM", + "title": "Did You Know?: Non-rectangular buildings", + "content": { + "type": "Image", + "url": "sas/images/SS_4_3_NWDYK.png" + } + }, + { + "id": "document_Text_2", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Answers will vary. There are many possible solutions. Some possible answers:
", - "Answers will vary. There are many possible solutions. Some possible answers:
Yes. The corresponding angles will be 90˚. For corresponding side lengths, you can always find a scale factor. Adjacent sides will always be equivalent ratios of side to side.
"]}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Freda’s Claim** All circles are similar."]}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["Yes. All circles are the same shape. Any radius can be scaled to find a corresponding radius. Any diameter can be scaled to find a corresponding diameter.
"]}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Juan’s Claim** All quadrilaterals are similar."]}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["No. All of the following shapes are quadrilaterals. None of them are similar to the other.
"]}}, - {"display": "teacher", "id": "YBpMcjE1W-Ha652l", "title": "Examples of non-similar quadrilaterals", "content": {"type": "Image", "url": "curriculum/stretching-and-shrinking/images/nonSimilarQuads4_2.png", "filename": "curriculum/stretching-and-shrinking/images/nonSimilarQuads4_2.png"}}, - {"content": {"type": "Text", "format": "markdown", "text": ["**Sze’s Claim** All triangles are similar if their corresponding angles are equal."]}}, { + "id": "document_Text_1", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_2", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Yes. The corresponding angles will be 90˚. For corresponding side lengths, you can always find a scale factor. Adjacent sides will always be equivalent ratios of side to side.
" + ] + } + }, + { + "id": "document_Text_3", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_4", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Yes. If all of the angles have equivalent measures, the triangles will have the same basic shape. The corresponding side lengths can be scaled to form a similar triangle.
", - "We saw this idea when we had reptiles.
", - "And we used this idea when measuring the river.
" + "Yes. All circles are the same shape. Any radius can be scaled to find a corresponding radius. Any diameter can be scaled to find a corresponding diameter.
" ] } }, { + "id": "document_Text_5", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_6", "display": "teacher", - "id": "hZT1f8Uxa4UP_9d0", - "title": "Similar Triangles in Rep-tiles", "content": { - "type": "Geometry", - "board": {"properties": {"axisMin": [-4.186, -2.093], "axisRange": [26.23, 17.486], "axisNames": ["x", "y"], "axisLabels": ["x", "y"]}}, - "objects": [ - {"type": "image", "parents": {"url": "curriculum/stretching-and-shrinking/images/clipboard-image", "coords": [0, 0], "size": [10.87431693989071, 7.213114754098361]}, "properties": {"id": "IZE4DNq8ehRdNoUC"}}, - {"type": "point", "parents": [7.87011612021858, 3.0850580601092896], "properties": {"id": "HqsyZzkT7qwKF1yI", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [4.5701161202185805, 2.78505806010929], "properties": {"id": "v68Lgant-ZfThAcY", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [6.5701161202185805, 0.9850580601092895], "properties": {"id": "rJeg1GI3mWlxMCBO", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["HqsyZzkT7qwKF1yI", "v68Lgant-ZfThAcY", "rJeg1GI3mWlxMCBO"], "properties": {"id": "v0Udd-Z4PVHwSsC6"}}, - {"type": "point", "parents": [4.646217554644807, 2.7760416666666687], "properties": {"id": "aU_R4N3Y2hRHGuF9", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [1.3462175546448067, 2.476041666666669], "properties": {"id": "_zb662FuwMtcXoWj", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [3.3462175546448076, 0.6760416666666687], "properties": {"id": "xavRTiDZhKjte5tt", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["aU_R4N3Y2hRHGuF9", "_zb662FuwMtcXoWj", "xavRTiDZhKjte5tt"], "properties": {"id": "ZgS-32NV1YjgF7xA"}}, - {"type": "point", "parents": [5.778850751366122, 4.8958418715847], "properties": {"id": "QYyIzZ33bihqIkfy", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [2.478850751366121, 4.5958418715847005], "properties": {"id": "yYE9PgzRNXCR6KC6", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [4.478850751366121, 2.8958418715847003], "properties": {"id": "BJuAUiOi08f4gtm9", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["QYyIzZ33bihqIkfy", "yYE9PgzRNXCR6KC6", "BJuAUiOi08f4gtm9"], "properties": {"id": "hKls22r5OqoE2QAI"}}, - {"type": "point", "parents": [0.2073742597390704, 0.49940912791490233], "properties": {"id": "J9YuthiuorJOLLXz", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [10.586527138203499, 1.0508082760636899], "properties": {"id": "T-Zgg1efvg_3d67S", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "point", "parents": [3.26973631919428, 6.775570965633871], "properties": {"id": "LRYmAA0aTj1MnX_d", "snapToGrid": true, "snapSizeX": 0.1, "snapSizeY": 0.1}}, - {"type": "polygon", "parents": ["J9YuthiuorJOLLXz", "T-Zgg1efvg_3d67S", "LRYmAA0aTj1MnX_d"], "properties": {"id": "D078io5PeAJEXXWe"}} + "type": "Text", + "format": "html", + "text": [ + "No. All of the following shapes are quadrilaterals. None of them are similar to the other.
" + ] + } + }, + { + "id": "YBpMcjE1W-Ha652l", + "title": "Examples of non-similar quadrilaterals", + "display": "teacher", + "content": { + "type": "Image", + "url": "sas/images/nonSimilarQuads4_2.png", + "filename": "sas/images/nonSimilarQuads4_2.png" + } + }, + { + "id": "document_Text_7", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_8", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "Yes. If all of the angles have equivalent measures, the triangles will have the same basic shape. The corresponding side lengths can be scaled to form a similar triangle.
We saw this idea when we had reptiles.
And we used this idea when measuring the river.
" + ] + } + }, + { + "id": "document_Text_9", + "content": { + "type": "Text", + "format": "html", + "text": [ + "" + ] + } + }, + { + "id": "document_Text_10", + "display": "teacher", + "content": { + "type": "Text", + "format": "html", + "text": [ + "SOLUTION:
Circles are not polygons. However, like any other shape, circles can be scaled.
Circles have measures, such as, the radius or diameter.
" ] } }, - {"content": {"type": "Text", "format": "markdown", "text": ["**Matt’s Claim** Circles are not similar since the do not have angles or side lengths."]}}, - {"display": "teacher", "content": {"type": "Text", "format": "html", "text": ["SOLUTION:
", "Circles are not polygons. However, like any other shape, circles can be scaled.
", "Circles have measures, such as, the radius or diameter.
"]}}, { + "id": "document_Text_11", "content": { "type": "Text", "format": "html", "text": [ - "1. Is this possible? Show your reasoning with sketches of the shapes.
", - "2. Include enough information to show which shapes are similar and which one is the imposter.
" + "José challenges his group to create another set of shapes that contains an imposter. He suggests that they use coordinate rules to create the set.
1. Is this possible? Show your reasoning with sketches of the shapes.
2. Include enough information to show which shapes are similar and which one is the imposter.
" ] } }, { + "id": "document_Text_12", "display": "teacher", "content": { "type": "Text", "format": "html", "text": [ - "Answers will vary. There are many possible solutions. Some possible answers:
", - "Students may elect to use draw tiles, table tiles, or graph tiles, or a combination, to answer this question. Note that students can also elect to work this on paper, take a picture, and load that into an image tile to capture the work in the platform." + "Answers will vary. There are many possible solutions. Some possible answers:
Students may elect to use draw tiles, table tiles, or graph tiles, or a combination, to answer this question. Note that students can also elect to work this on paper, take a picture, and load that into an image tile to capture the work in the platform.
" ] } } diff --git a/curriculum/sas/teacher-guide/investigation-0/problem-1/summarize/content.json b/curriculum/sas/teacher-guide/investigation-0/problem-1/summarize/content.json index b9e8279be..2ff3144a0 100644 --- a/curriculum/sas/teacher-guide/investigation-0/problem-1/summarize/content.json +++ b/curriculum/sas/teacher-guide/investigation-0/problem-1/summarize/content.json @@ -3,10 +3,13 @@ "content": { "tiles": [ { + "id": "document_Text_1", "content": { "type": "Text", "format": "html", - "text": ["Problem Summary
", "This Problem is intended to help both educators and students to learn how software features work in CLUE. There is no extended teacher guide. You will find teacher guides in other problems.
"] + "text": [ + "Problem Summary
This Problem is intended to help both educators and students to learn how software features work in CLUE. There is no extended teacher guide. You will find teacher guides in other problems.
" + ] } } ] diff --git a/images/uploads/brainblog.png b/images/uploads/brainblog.png new file mode 100644 index 000000000..5c694031f Binary files /dev/null and b/images/uploads/brainblog.png differ