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Description
The rapid integration of generative artificial intelligence (AI) into higher education has created an urgent need for instructional models that move beyond tool use toward intentional, pedagogically grounded practice. This study presents a structured assignment design that positions AI as a scaffolded collaborator within undergraduate educational psychology courses. Across a multi-part, semester-long sequence, students engage in concept explanation, self-directed inquiry, AI-supported knowledge construction, and reflective documentation of their learning process. Findings from recurring student artifacts indicate progressive gains in conceptual understanding, integration of research sources, and transfer of knowledge to personally meaningful contexts. Students demonstrate increased capacity for self-regulated learning through iterative prompting, evaluation of AI-generated content, and systematic verification of information. Reflective components further reveal the development of metacognitive awareness and a calibrated, critical stance toward AI, shifting from initial over-trust or skepticism to intentional and responsible use. This work contributes a replicable model for integrating generative AI into higher education that foregrounds epistemic agency, metacognition, and ethical AI literacy. By framing AI as a form of adaptive scaffolding within inquiry-based learning, the assignment supports deeper engagement with disciplinary content while preparing students to navigate AI-rich knowledge environments with autonomy and critical judgment.
Publisher Location
Las Vegas (Nev.)
Publication Date
Spring 4-30-2026
Publisher
University of Nevada, Las Vegas
Language
English
Keywords
Generative AI in education; AI literacy; self-regulated learning; metacognition; scaffolding; epistemic agency; educational psychology; inquiry-based learning; higher education pedagogy; formative assessment; student-centered learning; prompt engineering; critical AI use; technology-enhanced learning; learner agency
Disciplines
Educational Assessment, Evaluation, and Research | Science and Mathematics Education | Secondary Education
File Format
File Size
9500 KB
Recommended Citation
Fox, April Ursula, "Learning With AI: A Structured Approach to Student-AI Collaboration" (2026). UNLV Best Teaching Practices Expo. 226.
https://oasis.library.unlv.edu/btp_expo/226
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Included in
Educational Assessment, Evaluation, and Research Commons, Science and Mathematics Education Commons, Secondary Education Commons