Dr. Quigley's research studies students’ engagement with learning technologies in the classroom. He analyzes students’ use of tools with a mixed-methods approach, using analytics, surveys, observations and interviews to demonstrate the impact of improved tool design and the incorporation of real-time feedback based on novel analytics on the student learning experience. This leads to three questions that drive his research trajectory: 1) How can we use analytics to automatically characterize students’ engagement with science and engineering practices at scale? 2) How can we use digital learning tool design to promote successful use of science and engineering practices? 3) How do students’ use of these practices influence their engagement and learning? This mix of analytics, design, and educational research allows for the exploration of new frontiers in the space of designing adaptive learning technologies.
Learning Analytics, Human Computer Interaction, User Centered Design, Machine Learning, Learning Sciences, Personalized Learning, Digital Learning