Author Information
Kim Hung Lam, The Hong Kong Polytechnic University, Hong KongXiaofeng Huang, The Hong Kong Polytechnic University, Hong Kong
Chun Sang Chan, The Hong Kong Polytechnic University, Hong Kong
Kai Pan Mark, The Hong Kong Polytechnic University, Hong Kong
Anthony Ho, The Hong Kong Polytechnic University, Hong Kong
Mitesh Patel, The Hong Kong Polytechnic University, Hong Kong
Abstract
The integration of Generative Artificial Intelligence (GenAI) in educational settings has shown significant potential in enhancing student engagement and learning outcomes. This study explores the development and implementation of GenAI-assisted generated tutorial materials in disciplinary science courses that generated through a collaborative effort between students and staff. The primary objective was to utilize GenAI to create tutorial materials that align with course content, improve understanding, and enhance the overall learning experience.
We conducted an online survey to gather student feedback on the effectiveness of these materials in 2023-4 semester two. The results were overwhelmingly positive, with 100% of students agreeing that the GenAI materials were helpful in aiding their understanding of the subject matter (average score: 4.3 ± 0.5). Additionally, 92% of students believed that these materials could assist their learning process and benefit their understanding of the course material (average score: 4.5 ± 0.7).
According to the opinion of our students, we found out that our students generally found the GenAI-assisted generated tutorial materials good to support their study. Students appreciated that the materials were straightforward and clear. The content was professional, easily understandable with fluent pronunciation, effectively summarizing important key-points. Students believed that the quality output to make the learning content more clear and easy to support their understanding.
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