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Applying Learning Analytics in Programming Courses: A Feasibility Analysis on VisCode



The commencement of Learning Analytics (LA) dates back to 2011 in response to the proliferation of Big Data. Its primary objective is to leverage data analysis outcomes with the goal of enhancing teaching and learning quality. Through the past decade, scholars have evolved LA concepts to incorporate Precision Education and Learning Analytics 2.0. Recently, Kyoto University introduced BookRoll, an e-book tool fortified with data collection capabilities. Researchers have utilized BookRoll's tracking logs to assess the efficacy of distance learning during the COVID-19 pandemic. This led to the enabling of new designs in learning activities, forecasts of at-risk students, unearthed students' learning strategies, and even organized dataset challenge events to foster research advancement. In summary, BookRoll can serve as a prototype for online learning environment research and development. The objective of this research is to evaluate the potential of VisCode programming software, as a means of supporting the development of Learning Analytics (LA) in programming courses. To this end, the study employs BookRoll as a benchmark for comparison. A total of 160 participants in programming courses were involved, and the data collected from them (the LBLS160 dataset) was reviewed. Additionally, the study analyzed the data challenge workshop that utilized this dataset. Based on the findings, it can be concluded that VisCode has the potential to contribute to the development of future LA research.

Parallel abstracts


Parallel keywords

Learning analytics VisCode BookRoll


Akçapınar, G., Hasnine, M. N., Majumdar, R., Flanagan, B., & Ogata, H. (2019). Developing an early-warning system for spotting at-risk students by using eBook interaction logs. Smart Learning Environments, 6(1), 1-15.
Akçapinar, G., Hasnine, N. M., Majumdar, R., Chen, A. M.-R., Flanagan, B., & Ogata, H. (2020). Exploring temporal study patterns in eBook-based learning. 28th International Conference on Computers in Education Conference Proceedings,
Bobea, M., Park, S., Flanagan, B., & Lu, O. H. (2023). Improving the Prediction Accuracy of Student Performance in a Cross-Semester Scenario Utilizing a Domain Adaptation Approach. Data Challange Workshop on the 13th International Learning Analytics & Knowledge Conference,
Chen, A. M.-R., Majumdar, R., Hwang, G.-J., Lin, Y.-H., Akçapınar, G., Flanagan, B., & Ogata, H. (2020). Improving EFL students’ learning achievements and behaviors using a learning analytics-based e-book system. Proceedings of 28th International Conference on Computers in Education Conference Proceedings,
Chen, C.-H., & Su, C.-Y. (2019). Using the BookRoll e-book system to promote self-regulated learning, self-efficacy and academic achievement for university students. Journal of Educational Technology & Society, 22(4), 33-46.