Data and analysis scripts for the paper:
Rodríguez-Triana, M. J., Prieto, L. P., Martínez-Monés, A., Asensio-Pérez, J. I., & Dimitriadis, Y. (2018). Monitoring Collaborative Learning Activities: Exploring the Differential Value of Collaborative Flow Patterns for Learning Analytics. In Proceedings of the 18th IEEE International Conference on Advanced Learning Technologies (ICALT18).
Abstract: Collaborative learning flow patterns (CLFPs) encode solutions to recurrent pedagogical problems, which have been successfully applied to the design of learning experiences. However, the pedagogical knowledge encoded in these patterns has seldom been exploited in learning analytics (LA). This paper analyzes four of the most common CLFPs to extract the intrinsic constraints that lead to a successful collaborative learning activity, and use them to enhance existing LA solutions. To understand the added value of applying such codified knowledge in LA, we present evidence from five authentic case studies in which such constraints aided university teachers in monitoring complex collaborative scripts. The results not only illustrate quantitatively such added value but also unearth qualitative benefits, such as raising practitioners’ awareness about how the current state of activities may affect future phases of the script.
- Clone or download this repository
- Open the file
DataAnalysis-ICALT18.Rmdin RStudio - Knit the file in RStudio, to generate an HTML analysis report
- That's it! Enjoy :)