Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Putting It All Together: Combining Learning Analytics Methods and Data Sources to Understand Students’ Approaches to Learning Programming

Version 1 : Received: 13 April 2021 / Approved: 15 April 2021 / Online: 15 April 2021 (09:40:33 CEST)

A peer-reviewed article of this Preprint also exists.

López-Pernas, S.; Saqr, M.; Viberg, O. Putting It All Together: Combining Learning Analytics Methods and Data Sources to Understand Students’ Approaches to Learning Programming. Sustainability 2021, 13, 4825. López-Pernas, S.; Saqr, M.; Viberg, O. Putting It All Together: Combining Learning Analytics Methods and Data Sources to Understand Students’ Approaches to Learning Programming. Sustainability 2021, 13, 4825.

Journal reference: Sustainability 2021, 13, 4825
DOI: 10.3390/su13094825

Abstract

Learning programming is a complex and challenging task for many students. It in-volves both understanding theoretical concepts and acquiring practical skills. Hence, analyzing learners’ data from online learning environments alone fails to capture the full breadth of stu-dents’ actions if part of their learning process takes place elsewhere. Moreover, existing studies on learning analytics applied to programming education have mainly relied on frequency analysis to classify students according to their approach to programming or to predict academic achieve-ment. However, frequency analysis provides limited insights into the individual time-related characteristics of the learning process. The current study examines students’ strategies when learning programming, combining data from the learning management system and from an au-tomated assessment tool. To gain an in-depth understanding of students’ learning process as well as of the types of learners, we used learning analytics methods that account for the temporal order of learning actions. Our results show that students have special preferences for specific learning resources when learning programming, namely slides that support search, and copy and paste. We also found that videos are relatively less consumed by students, especially while working on programming assignments. Lastly, students resort to course forums to seek help only when they struggle.

Subject Areas

automated assessment; computer science; learning analytics; process mining; programming; sequence mining

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.