The (Human + Machine) Learning lab (HPML lab) at the University of Illinois Urbana–Champaign (UIUC) conducts research on educational psychology, machine learning, and how these areas intersect. The lab consists primarily of people in the School of Information Sciences (iSchool) and the Department of Educational Psychology.
We develop data mining approaches to better understand and adapt to the experiences of students in digital learning environments. We focus especially on examining machine learning models and learning environments to reduce systematic biases against students, and thus improve the inclusiveness of online learning. As the lab name suggests, we take an interdisciplinary approach to answering research questions in areas like:
- Educational psychology – e.g., how does natural language in discussion forums reveal students’ metacognitive thought processes?
- Educational data mining/learning analytics – e.g., how can we reduce biases in accuracy for machine learning models across student demographics?
- Human–computer interaction – e.g., does promoting self-regulated learning behaviors in learning software improve student outcomes?
And more! We’re often looking for students, from undergraduates to perspective PhD students, so if these research areas are interesting to you, consider applying.