CSCL Poster
#694: Encouraging Deeper Learning with GenAI: A Review of Pedagogical Constraints on GenAI and Their Impact in Higher Education
Wed Jun 17, 4:15 PM–5:45 PM · Outdoors
Generative AI & Large Language Models Higher Education & Undergraduate Learning Inquiry-Based Learning & Productive Failure AI in Education
This paper reviews how generative AI (GenAI) can be pedagogically constrained to promote deeper learning in higher education. Analyzing 15 intervention studies comparing constrained GenAI use with free or no GenAI use, we found three delivery methods (process, activity, and tool levels), operationalized through five mechanisms. Results show primarily positive impacts on performance, motivation, and higher order thinking, though nearly half rely on self-reports. The findings highlight the role of constraints in GenAI use, and invite further research explicitly linking constraints to outcomes.
Speakers
- Shuang Geng — Boston University
Authors
Shuang Geng, Di Fan, Juhong Eom, Gahyun Callie Sung