"Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses"
Members of UCI's Digital Learning Lab (DLL) have published a paper in Proceedings of the 9th International Conference on Learning Analytics & Knowledge (LAK). The title of the paper is "Utilizing Learning Analytics to Map Students' Self-Reported Study Strategies to Click Behaviors in STEM Courses." Authors are Fernando Rodriguez, Renzhe Yu, Jihyun Park, Mariela Rivas, Mark Warschauer, and Brian Sato.
Informed by cognitive theories of learning, this work examined how students' self-reported study patterns (spacing vs. cramming) corresponded to their engagement with the Learning Management System (LMS) across two years in a large biology course. We specifically focused on how students accessed non-mandatory resources (lecture videos, lecture slides) and considered whether this pattern differed by underrepresented minority (URM) status. Overall, students who self-reported utilizing spacing strategies throughout the course had higher grades than students who reported cramming throughout the course. When examining LMS engagement, only a small percentage of students accessed the lecture videos and lecture slides. Applying a negative binomial regression model to daily counts of click activities, we also found that students who utilized spacing strategies accessed LMS resources more often but not earlier before major deadlines. Moreover, this finding was not different for underrepresented students. Our results provide some initial evidence showing how spacing behaviors correspond to accessing learning resources. However, given the lack of general engagement with LMS resources, our results underscore the value of encouraging students to utilize these resources when studying course material.
Access to the paper: https://dl.acm.org/citation.cfm?doid=3303772.3303841