Exploring the Effectiveness of Generative AI as a Learning Tool in Engineering Education: An Analysis of Student Experiences and Perceptions

Artificial Intelligence (AI) is increasingly adopted by educational institutions, particularly as a generative AI (GenAI) tool for e‐learning. This study explores the effectiveness of using GenAI with engineering students at a leading university in Saudi Arabia and the Middle East. It aims to assess GenAI's impact in the College of Engineering and examine gender‐based differences in how students utilize AI as a learning tool. The study also investigates how students from different engineering majors utilize AI in their learning. To achieve this objective, an online survey with 15 questions was distributed to 403 engineering students to analyze their perceptions of AI adoption in education. The study employs two non‐parametric rank‐based statistical tests: the Mann–Whitney test to analyze gender differences, and the Kruskal–Wallis test to examine how various engineering disciplines such as industrial, electrical, mechanical, civil, chemical, nuclear, and mining engineering influence GenAI adoption. The findings reveal significant differences between male and female students in their experiences with GenAI, particularly regarding inaccurate or misleading responses, accurate and reliable responses, and their opinions regarding the users from applied academic field toward GenAI adoption. The results also indicate notable differences among engineering majors in their proficiency with GenAI features, their experiences with hallucinated responses, their views on using GenAI in theoretical disciplines, and their trust in the accuracy of information provided by ChatGPT. These findings support educational decision‐makers in integrating AI as a learning technology for engineering students and in understanding student engagement with AI tools in education.