Studies exploring disfluency effect and influence of fonts on memory

Designed and conducted by: Mary Dyson and David Březina

This repo contains materials for two studies we have conducted in the first half of 2018 with the goal to explore a disfluency effect and influence of fonts and their legibility on memory.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Study reports

We described the studies and some of the results in a conference presentation at the ICTVC 7 conference in Patras in June 2019. Find brief reports about the studies on Design Regression mini-journal:

• Exploring disfluency: Are designers too sensitive to harder-to-read typefaces? (mostly about study 1)
• The sequel to exploring disfluency: Do we remember the visual appearance of words? (mostly about study 2)

Contents of this repo

This repo includes:

• the website we used to collect participants’ responses
• the data/responses collected
• Jupyter notebooks used to process the data and provide descriptive statistics

We have used other software to analyze the data.

Website

The website was served using GitHub Pages directly from this repo. The code is saved in docs/. You can preview it by visiting https://mrbrezina.github.io/disfluency-study/ (the responses will not get saved).

The website uses Javascript to navigate between inidividual steps of the study and request responses from participants. The responses from each participant were saved using a GetForm service.

The samples (words and non-words set in one of two studied fonts) are generated using a Python script (see samples/generate-samples.py) based on the data/samples-databases.

Data

For the databases of words and non-words, see data/samples-databases.

The “raw“ data collected from the website (via GetForm) before any processing is saved in data/raw/ folder. The processed data is stored in data/data.csv and data/data_aggregated.csv. For description of the data format, see the data-processing notebook.

Jupyter notebooks

Jupyter notebooks used to process and analyze the data are stored in the notebooks/ folder.

• notebooks/1 Process raw data.ipynb View using NBViewer
• notebooks/2 Descriptive statistics.ipynb View using NBViewer