Artificial Intelligence (AI) has emerged as a transformative technology in engineering education; however, its pedagogical value depends on structured integration within established educational frameworks. This study investigates the impact of AI-supported instruction on student academic achievement when designed and implemented in alignment with the CDIO (Conceive-Design-Implement-Operate) framework. A quasi-experimental research design was employed in an undergraduate engineering course in Digital Logic. The experimental group participated in AI-supported, CDIO-aligned learning activities emphasizing active learning and integrated learning experiences, while the control group received traditional instruction. Student achievement was measured using pre- and post-tests, and data were analyzed using analysis of covariance (ANCOVA) and effect size calculations. The results demonstrate a statistically significant improvement in learning outcomes for students exposed to AI-supported instruction. The findings provide empirical evidence that AI, when embedded within CDIO-aligned pedagogy, enhances student achievement and supports evidence-based curriculum innovation in engineering education. Specifically, the experimental group achieved a mean post-test score of 82.60 compared to 77.31 in the control group, and ANCOVA results showed a statistically significant difference (F(1,133)=22.47, p<.001).
