Harnessing UniAnalytics: Exploring the Role of Engagement and Collaboration in Student Success in Jupyter Notebook Environments

Abstract

Whether and how students engage, and the ways in which they collaborate during learning activities, are critical determinants of academic success. These factors become even more significant in computational learning environments where digital tools mediate interactions. In this thesis, we examine the relationship between student engagement, collaboration, and academic success in a Jupyter Notebook-based learning environment. We utilize regression and multilevel models to identify key engagement and collaboration behaviors observing their impact on three key measures of student success: performance on assignments, on the final exam, and overall course grade. From our analyses, we find that certain engagement metrics such as execution frequency are strong predictors of success. We also found that other metrics such as higher error rates and prolonged idle time are negatively associated with all 3 of our measures of success. Our chosen collaboration metrics do not show significant correlations with student success, raising questions about how collaborative learning is assessed in digital environments. This thesis hopes to contribute to the growing field of learning analytics by providing empirical evidence on how digital engagement behaviors impact student success. The ultimate goal of this work is to offer insights that can enhance teaching strategies and educational outcomes in computational classrooms that rely on digital tool such as Jupyter Notebook.