Transforming Engineering Education with Artificial Intelligence and Digital Storytelling: Evidence from Learning, Motivation, and Competency Development

Abstract

In the context of the ongoing transformation of engineering education driven by artificial intelligence, this study examines the impact of digital storytelling co-created with generative AI as an innovative pedagogical strategy to enhance learning, motivation, and competency development in STEM environments. The intervention was implemented in an undergraduate course on Analysis of Electromagnetic Systems, involving 170 university students divided into an experimental group (n = 90) and a control group (n = 80). The central challenge required students in the experimental group to explain a complex STEM concept to a non-expert audience through scientific narratives supported by generative AI tools such as ChatGPT, Midjourney, and Runway, integrating textual, visual, and audiovisual resources. In contrast, the control group addressed the same technical content using traditional instructional strategies based on conventional technical reports. Results show statistically significant improvements in the experimental group across technical competencies, including mathematical modeling, programming, and visualization, as well as transversal competencies such as scientific communication, critical thinking, and collaboration. A strong correlation was also identified between student motivation and academic performance (r = 0.79, p < 0.001). Inferential analyses using t-tests, ANOVA, and regression models confirmed a medium-to-high effect size. Overall, the findings indicate that the intentional pedagogical integration of artificial intelligence with digital storytelling fosters dual coding, meaningful learning, deeper conceptual understanding, and sustained student engagement. Aligned with the Tec21 educational model and Sustainable Development Goal 4 (Quality Education), this study provides robust empirical evidence.