Asked & Answered: Using AI to Nudge Student Metacognition and Responsibility for Learning.

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Bibliographic Details
Title:	Asked & Answered: Using AI to Nudge Student Metacognition and Responsibility for Learning.
Authors:	Fritz, John¹, Abrams, Josh¹, Bass, Sarah¹, Braunschweig, Suzanne¹, Carpenter, Tara¹, McAllister, Nancy¹, Penniston, Thomas¹
Source:	Online Learning. Jun2026, Vol. 30 Issue 2, p63-81. 19p.
Subject Terms:	Metacognition, Self-regulated learning, Individualized instruction, Retrieval practice, Team learning approach in education, Formative evaluation, *Academic achievement, Artificial intelligence in education
Abstract:	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 selfregulated 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. Can AI help? ● 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. While successful, AI could streamline the curation of these student-crowdsourced study guides, which could be key to faculty colleagues adopting the approach. ● 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. This helps students form effective study groups, a skill valued by faculty but difficult to implement, especially for at-risk students. 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 vs. where they’d like to be—especially after taking a high-stakes midterm or final exam. [ABSTRACT FROM AUTHOR]
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Database:	Education Research Complete

Description
Abstract:	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 selfregulated 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. Can AI help? ● 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. While successful, AI could streamline the curation of these student-crowdsourced study guides, which could be key to faculty colleagues adopting the approach. ● 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. This helps students form effective study groups, a skill valued by faculty but difficult to implement, especially for at-risk students. 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 vs. where they’d like to be—especially after taking a high-stakes midterm or final exam. [ABSTRACT FROM AUTHOR]
ISSN:	24725749
DOI:	10.24059/olj.v30i2.5848