Effects of integrating peer assessment with electromechanical game-based learning on enhancing AI learning and computational thinking of undergraduates

Peer assessment and AIoT board games have emerged as effective game-based learning approaches for enhancing artificial intelligence (AI) education and computational thinking (CT). This study employs a four-group quasi-experimental design to examine their impact on undergraduate learning using a personal audio classifier (PAC). The AIoT board game integrates CT and AI concepts through collaborative, hands-on learning, incorporating peer assessment, problem-solving scenarios, and paired programming. Results indicate that anonymous online peer assessment fosters critical thinking and reduces learning anxiety. The AIoT board game enhances collaboration, creativity, and the practical application of AI concepts. Peer assessment further supports iterative improvement of PAC applications for gameplay. The integration of peer assessment within problem-solving tasks significantly improves learning outcomes, lowering barriers to AI education and preparing students for a technology-driven future. This study highlights the potential of combining AI instructional tools with peer assessment to deepen students’ understanding of AI and CT.