AI-Assisted Research Workshop: A Strategy to Enhance Engagement and Motivation in Engineering Education

Abstract

The use of artificial intelligence (AI) in higher education is opening new opportunities to enhance research skills and motivation. This study presents the implementation and evaluation of an AI-assisted research workshop designed to improve engagement, basic research competencies, and vocational interest in scientific writing among undergraduate engineering students. The workshop integrated generative AI tools throughout various stages of the research process, including literature review, data analysis, and scientific writing, while emphasizing ethical considerations and responsible AI use. A mixed-methods approach, combining pre- and post-tests, perception surveys, and the MUSIC motivation inventory-was employed to assess the intervention's impact. Results demonstrated a statistically significant improvement in students' understanding of basic research and scientific writing concepts <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(p&lt;0.001)$</tex>. The MUSIC model indicated high motivation across all dimensionsempowerment, usefulness, success, interest, and caring-with over 93% agreement levels. Qualitative feedback highlighted strong perceptions of AI's usefulness and relevance to academic work, alongside some concerns about trust and ethical issues. The workshop also positively influenced students' vocational orientation toward research, Overall, these findings underscore the potential of AI tools, when integrated within 2 well-structured and ethically guided frameworks, to catalyze student engagement, skill development, and sustained interest in learning and research.

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