Artificial intelligence meets PBL: transforming computer-robotics programming motivation and engagement

摘要

In response to the growing demand for innovative instructional strategies in STEM education, we examine the effectiveness of AI-supported Problem-Based Learning (PBL) in improving students’ engagement, intrinsic motivation, and academic achievement. Traditional pedagogies often fail to sustain learner interest and problem-solving skills, particularly in computing disciplines, which informed our focus on integrating artificial intelligence into PBL to address these gaps. We adopted a quasi-experimental design with a non-equivalent pretest–posttest control group structure, involving 87 s-year undergraduates enrolled in Computer Robotics Programming courses in Nigeria Universities. Participants were divided into two groups: the experimental group ( n = 45, University of Nigeria) received AI-supported PBL instruction, while the control group ( n = 42, Nnmadi Azikwe University) engaged in traditional PBL. We ensured the reliability and validity of our instruments, with Cronbach’s alpha values exceeding 0.70, composite reliability > 0.70, and AVE > 0.50. Data were analyzed using one-way multivariate analysis of covariance (MANCOVA) to assess the combined and individual effects of instructional method, controlling for prior programming experience. Results revealed a significant multivariate effect of instructional method on the combined outcomes, Wilks’ Λ = 0.134, F (3, 82) = 176.93, p < 0.001, η 2 = 0.866. Univariate analyses showed that AI-supported PBL significantly improved engagement (η 2 = 0.694), motivation (η 2 = 0.690), and achievement (η 2 = 0.519) compared to traditional PBL. We conclude that integrating AI into active learning environments transforms cognitive and skills learning outcomes. We recommend that curriculum designers, educators and policymakers prioritize AI-enhanced pedagogies and invest in faculty training for sustainable STEM education. This approach promises to advance learner-centered instruction and equip graduates for the challenges of a technology-driven future.