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Towards developing a learning analytics dashboard for a massive online robotics competition
Journal
IEEE Global Engineering Education Conference, EDUCON
ISSN
21659559
Date Issued
2022-01-01
Author(s)
Kodumuru, Saketh
Lucas, Brendan
Sabanwar, Vivek
Patil, Sachin
Avudiappan, Deepa
Parikh, Parth
Arya, Kavi
Abstract
A Learning Analytics Dashboard is a quick and efficient way for instructors to track the activities of students. In massive online learning scenarios like an international robotics competition, a dashboard is a critical tool for instructors to ensure continuous engagement of participants. Previous research on learning analytics dashboards focused on the effectiveness of dashboards and learning analytics on students along with factors affecting its success. This research discusses a dashboard developed for a massive robotics competition through which each year thousands of students are trained in engineering skills in an online Project Based Learning approach. The dashboard is developed using the dataset for the competition conducted during September 2020 to April 2021 in which more than 10,000 undergraduate students from 572 academic institutions across 7 countries participated. Team characteristics like demographics, feedback, scores, online activity, etc. are considered to cluster teams and develop models to predict the retention of participants. The Machine Learning (ML) model was able to achieve an accuracy of 80.7% and a recall value of 83.9% to identify dropping teams. Clustering provided insights on how these characteristics affected the performance of participants. These predictions along with participant engagement and feedback data was displayed on the dashboard. This visualization helps instructors identify teams requiring guidance or scaffolds to continue participation. Feedback from instructors shows the dashboard to be a promising tool for effectively managing massive online competitions.
Volume
2022-March
Subjects