PearProgram: Towards Fruitful Collaboration in Computing Education Research and the Learning Sciences

Abstract

Computer Education Research has not made widespread use of relevant research in the Learning Sciences. Our research seeks to understand pair programming learning dynamics using established Learning Sciences frames to improve pedagogical methods and practices in Computer Science learning. We have developed PearProgram to work as both a learning tool and a data-gathering tool. Students who used the tool engaged more actively in the courses and attained higher pass rates. Additionally, analysis of qualitative data points to the importance of Dual-Space Model and Positioning frameworks in understanding the dynamics of a generative pair programming session. These findings suggest careful attention by the facilitator to offer structure and explicit decision making about roles can shape pair success in assignments and augment implicit learning.