Asked & Answered
Using AI to Nudge Student Metacognition and Responsibility for Learning
DOI:
https://doi.org/10.24059/olj.v30i2.5848Keywords:
pedagogical innovation, Metacognition, generative AI, student responsibility for learningAbstract
This reflective case study examines how the University of Maryland, Baltimore County (UMBC) is exploring the use of AI to personalize, scale, and nudge students to become more self-regulated learners. Specifically, four courses, varying in discipline, size, and use of technology, collectively share a common pedagogical goal of cultivating students' willingness and ability to learn how to learn through AI-assisted formative practice. For example: UMBC’s largest two courses (CHEM 101 & 102), each with over 800 students annually, are using AI to create a “24/7 prof” and formative learning environment, based in part, on “spaced practice” to counter ineffective student cramming for exams. While effective, students struggle to replicate these strategies on their own in later courses. A lab science course for non-STEM majors (SCI 100), with 600 students annually, asks students to create their own practice questions and answers for extra credit. A smaller course for students on academic probation (UNIV 102), with 20 students per section, is using AI to inform a team-based extra credit practice environment for weekly quizzes. In each use case, the goal is to use technology that provides students with a personalized learning environment akin to a virtual “Holodeck” for practice that refines their ability and willingness to honestly and accurately assess what they currently know, understand and can do, and close the gap between where they see themselves and where they would like to be.
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Copyright (c) 2026 John Fritz, Josh Abrams, Sarah Bass, Suzanne Braunschweig, Tara Carpenter, Nancy McAllister, Thomas Penniston
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