Talk Title: What and How Students Read: A Data-driven Insight
Talk Abstract: Reading is an integral part of learning. The purpose of reading to learn is to comprehend meaning from informational texts. Reading comprehension tasks require self-regulated learning (SRL) behaviors – to plan, monitor, and evaluate one’s reading strategies. Students without SRL skills may struggle in reading which in turn may inhibit them to acquire domain-specific knowledge. Thus, understanding students reading behavior and SRL usage is important for intervention. Digital reading platforms can provide opportunities to learn and practice SRL strategies in classroom settings. These platforms log rich array of student and teacher interaction data with the systems. Retrospective analysis of these logged data can derive insights– which can be used to support tailored interventions by instructors and students in complex learning activities. In this talk, I will discuss students’ science reading and SRL behaviors, and connect those behaviors with performance within a digital literacy platform, Actively Learn. The talk consists of two studies (i) identifying patterns that differ between productive and unproductive students (iI) analyzing the association of teachers’ behavior and students’ SRL usage. I will finish my talk by underlying possible future directions.
Bio: Effat Farhana is a Ph.D. Candidate in the Computer Science Department at North Carolina State University working with Dr. Collin F. Lynch in the ArgLab research group. She received her B.S. in Computer Science and Engineering from Bangladesh University of Engineering and Technology. Her research focuses on mining educational software to derive data-driven heuristics, machine learning, and designing interpretable machine learning algorithms.