Evaluating Generative AI as a Pedagogical Tool for Creative Problem-Solving in University Classrooms

Abstract

This study investigated the effectiveness of generative artificial intelligence (AI) as a pedagogical tool for enhancing creative problem-solving (CPS) skills and divergent thinking (DT) among undergraduate students. A quasi-experimental pretest-posttest control group design was employed with 120 education students at a private university in Palembang, Indonesia. Participants were assigned to an experimental group (n = 60) that engaged in a 12-week AI-assisted learning intervention within an Educational Psychology course, and a control group (n = 60) receiving conventional instruction. Creative problem-solving was measured using the Creative Problem-Solving Performance Inventory (CPSPI, α = 0.89), while divergent thinking was assessed through an adapted Torrance Tests of Creative Thinking (TTCT, ICC = 0.91). Results from mixed ANOVA revealed a significant interaction effect for CPS, F(1,118) = 89.34, p < .001, partial η² = 0.431. MANOVA confirmed significant multivariate differences across all outcome measures, Pillai’s V = 0.482, F(5,114) = 21.24, p < .001. Large effect sizes were observed for CPS (Hedges’ g = 1.66) and DT (Hedges’ g = 1.18). These findings suggest that structured integration of generative AI into university pedagogy can substantially improve students’ creative problem-solving and divergent thinking capacities.