Document Type
Conference Proceeding
Publication Date
2026
Abstract
Notetaking is a vital practice in engineering education, where students must capture technical content in real time. This study compared peer-collaborative and AI-assisted notetaking with traditional approaches, focusing on benefits, challenges, and links to performance. Using mixed-methods design, data were collected from 81 undergraduate engineering students at Ateneo de Manila University. Surveys provided quantitative measures, analyzed through descriptive statistics, chi-square tests, and Spearman's correlation, while qualitative responses offered contextual insights. Results on Likert scale of 1 (low) to 5 (high) showed that peer-collaborative notetaking was highly valued for social learning (M = 4.30) and error detection (M = 4.25), though hindered by uneven participation (M = 4.07) and expertise gaps (M = 3.91). AI-assisted notetaking offered cognitive benefits (M = 3.69) and accessibility (M = 3.59) but raised significant concerns about ethics (M = 4.27) and accuracy (M = 4.25). Chi-square results confirmed significant variation in use, χ2(14, N=81) = 65.26, p < .001. Correlation analysis indicated no significant relationship between peer collaboration and grades (ρ = -0.177, p = 0.115), while AI-assisted notetaking showed a moderate, significant positive correlation (ρ = 0.407, p < .001). Findings suggest that peer collaboration supports engagement and understanding, while AI tools enhance performance but pose ethical risks. A blended approach is recommended, combining collaborative depth with AI efficiency under clear academic guidelines. © 2026 IEEE.
Recommended Citation
Galicia, J. K. A. (2026). AI-assisted and peer-collaborative notetaking in engineering education: Benefits, challenges, and links to academic performance. Ateneo de Manila University.
