Accessibility, Learning Motivation, and Personalised Learning Experience of AI Chatbots: Associations with Students’ Academic Performance
DOI:
https://doi.org/10.55573/JISED.118775Keywords:
artificial intelligence chatbots, academic performance, accessibility, learning motivation, personalised learning, higher educationAbstract
This study examined the relationship between selected dimensions of AI chatbot use and students’ academic performance among full-time undergraduate students at a Malaysian higher education institution. Specifically, the study investigated whether academic performance differed by gender and whether accessibility, learning motivation, and personalised learning experience associated with AI chatbots significantly predicted academic performance. A cross-sectional quantitative survey was conducted using a 30-item questionnaire administered through Google Forms. Data collected from 297 respondents were analysed using an independent-samples t-test and multiple linear regression. The independent-samples t-test indicated no statistically significant difference in academic performance between male and female students, t(295) = 1.605, p = .110. The multiple linear regression model was statistically significant, F = 41.021, p < .001, explaining 29.6% of the variance in academic performance (R² = .296). Accessibility was positively associated with academic performance (B = .105, p = .050), while learning motivation (B = .249, p < .001) and personalised learning experience (B = .259, p < .001) demonstrated statistically significant positive associations. Overall, the findings suggest that accessibility, learning motivation, and personalised learning experience are important factors associated with students’ academic performance in the context of AI chatbot use. The findings provide insights for students, educators, and higher education institutions seeking to integrate AI chatbots effectively as supplementary learning tools.
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