DOI: 10.18848/1835-9795/cgp/a381 ISSN: 2475-9686

Coopetitive Learning Integrated with Generative AI

Hansol Lee
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This study examined the effects of instruction integrating Generative Artificial Intelligence (Gen AI) with coopetitive learning on elementary school students’ AI self-efficacy and sociality. Although Gen AI supports learners’ cognitive activities through individualized assistance, concerns have been raised that it may reduce peer interaction. To address this concern, the study applied a coopetition-based instructional design that combined intragroup cooperation and intergroup competition. A quasi-experimental pretest-posttest control group design was employed with ninety-one sixth-grade students over six weeks and twelve forty-minute sessions. The experimental group participated in coopetition-based learning with Gen AI, while the control group engaged in individual learning with Gen AI. The collected data were analyzed using mixed-design analysis of variance (ANOVA). The results revealed statistically significant interaction effects between group and time for both AI self-efficacy and sociality. Although both groups improved from pretest to posttest, the gains in the experimental group were significantly greater than those in the control group. These findings suggest that integrating a coopetitive structure with Gen AI can enhance learners’ confidence in using AI, while promoting social competence through peer interaction. By providing empirical evidence of the complementary integration of human interaction and AI support, this study underscores the importance of instructional design that addresses both cognitive and social outcomes in AI-enhanced learning environments.

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