Engineering Education and Quantified Self: Utilizing a Student-Centered Learning Analytics Tool to Improve Student Success

This evidence-based practice paper assessed the implementation of a quantified-self learning analytics tool, called Pattern, and how it impacted study behaviors across multiple sections of engineering courses at Purdue University. The goals of the implementation of Pattern and subsequent research was to explore: (a) student study activities that correlated with success, (b) student study behavior change from exam-to-exam, and (c) whether the use of Pattern impacted study habits. Results indicated that simply studying longer does not correlate with success and that students spend the most amount of time doing activities they rate the lowest in effectiveness (e.g., reading). Additionally, while students do make behavioral changes from exam-to-exam, those changes are only moderate in size and scope. Gender differences were also found to be significant in how students studied. Based on the results of this study, recommendations for instructors are to 1) use technology that is familiar and facilitates peer comparison, 2) conduct analysis of recommended study strategies to assess effectiveness, and 3) stress to students that how they study is much more important than how long they study.