Author(s):
The Need: As online learning becomes more prevalent especially after the onset of COVID pandemic, there’s a pressing need to identify students’ learning strategies and level of engagement in online learning environments, and understand how they change change over the semester. Moreover, for an increasingly diverse student population, it is increasingly important to design and improve learning environments that could enable students to progress at different paces by providing ample opportunities for self-assessments.
Guiding Questions: How can we reliably and efficiently identify students’ learning strategie, by analyzing the click-stream event logs from online platforms, and synthesize information contained from single events to repeated patterns observed over days or weeks? How do we use those information to evaluate the effectiveness of the design of learning environments and instructional contents?
Outcomes: In this poster, we will first introduce Online Learning Modules, a mastery-based flexible learning environment that allow different students to proceed on their own pace. The system also significantly improves instructor’s ability to share and reuse online learning resources. We then introduce our multi-level clustering analysis algorithm that is able to detect different types of student learning strategies from analyzing students’ click-stream data from Online Learning Modules, and track the change over an entire semester. Finally, we will evaluate the effectiveness of instructional interventions that are designed to promote beneficial learning behavior such as spreading out the work.
Broader Impacts: This work has three major broader impact: first, it lays the groundwork for liberating instructors from repetitively delivering knowledge in the classroom, and allow them to create, evaluate and improve learning resources and learning environments. Second, the online learning modules reduces the barrier for the creation, sharing and adoption of open education resources for students. Finally, it allows students with diverse incoming knowledge to actively select the learning resources they need, and proceed at their own pace of learning, thereby improving the equity in STEM education.
