Dr. Heeryung Choi is a learning analytics researcher with an interdisciplinary background, focused on bridging theories and data to advance our understanding of human learning. She is currently affiliated with MIT's Center for Transportation and Logistics. She is leading a learning analytics dashboard project for the MITx MicroMasters program in Supply Chain Management, impacting thousands of online students. This project has been recognized with a grant from MIT's Institute for Learning and Innovation (MITili). Her work has been featured in several conferences and journals including Learning Analytics and Knowledge (LAK) and The Internet and Higher Education. She earned her Ph.D. in Information from the University of Michigan and an M.S. in Cognitive Science from Seoul National University. 

Talk: Advancing Learning Analytics: Insights from Trace and Survey Data on Self-Regulated Learning

Attend this talk via Zoom

Abstract: Measurement plays a pivotal role in advancing learning analytics research, especially on self-regulated learning. Self-reported instruments, particularly surveys, have traditionally been the primary source of knowledge on self-regulated learning. Recently, as technology continually advances, researchers have increasingly incorporated trace data into their studies. In this dynamic phase, what we now require are in-depth discussions and practices on how to select and design these measurements to ensure a valid and comprehensive understanding of self-regulated learning. In this talk, I will discuss research approaches of comparing and complementing trace data and survey data for holistic understanding of self-regulated learning. Drawing from my own studies, I will demonstrate how these approaches can contribute to advancement of theory and methodology within the field of learning analytics.