Impact of DMCT-CDIO Dual Mainline Computational Thinking Integrated Engineering Education on Students' Computational Thinking, Motivation and Engagement

Engineering education (CDIO) plays a crucial role in developing students' comprehensive abilities, solving real-world problems, and addressing future technological challenges. As information technology advances rapidly, effectively integrating advanced teaching models to enhance students' engineering literacy and computational thinking has become a key focus in educational reform. This study examines the effects of the DMCT-CDIO dual-mainline computational thinking-integrated engineering education model on students' computational thinking, motivation, engagement, and cognitive load. Conducted in a data mining course at a teacher training university in China, the study involved 76 second-year undergraduates. The experimental group (n=38) followed the DMCT-CDIO model, while the control group (n=38) implemented the traditional CDIO model. ANOVA results indicated that the experimental group demonstrated significant improvements in intrinsic motivation, behavioral engagement, emotional engagement, and computational thinking (including algorithmic thinking, critical thinking, and problem-solving ability), outperforming the control group. Additionally, the experimental group exhibited significantly lower cognitive load. These findings offer valuable insights for educators and researchers, suggesting future research directions, such as further integrating the DMCT-CDIO model with engineering learning, exploring the relationship between psychological variables and academic performance, and analyzing the cognitive development of computational thinking and engineering practice behaviors among diverse student groups. These efforts aim to optimize instructional design based on empirical data.