FROM LEARNING ASSISTANT TO LEARNING DEPENDENCY: HOW ARTIFICIAL INTELLIGENCE USAGE, CRITICAL THINKING DISPOSITION, AND ACADEMIC PERFORMANCE AMONG MATHEMATICS EDUCATION STUDENTS
DOI:
https://doi.org/10.56773/bj.v5i2.169Keywords:
artificial intelligence, AI usage, academic performance, critical thinking dispositionAbstract
The rapid adoption of artificial intelligence (AI) in higher education has transformed students' learning practices, particularly in completing academic assignments and projects. However, the extent to which AI use influences academic performance remains inconclusive. This study investigated the effects of overall AI usage, the percentage of AI use in course projects, and mathematical disposition on undergraduate students' Grade Point Average (GPA). A quantitative correlational design was employed involving 39 undergraduate students. Data were collected using a validated AI usage questionnaire, a mathematical disposition questionnaire, self-reported percentage of AI use in course projects, and students' GPA. Multiple linear regression analysis was conducted after verifying the assumptions of normality, multicollinearity, and independence of residuals. The regression model was statistically significant (F = 6.247, p = .002) and explained 34.9% of the variance in GPA (R² = .349). Among the predictors, only the percentage of AI use in course projects significantly predicted GPA (β = −0.614, p < .001), whereas overall AI usage (p = .651) and mathematical disposition (p = .695) were not significant predictors. These findings indicate that AI use itself is not associated with lower academic performance. Instead, students' reliance on AI in completing course projects appears to be associated with GPA. Excessive dependence on AI-generated outputs without critical evaluation, revision, verification using credible academic sources, and integration of students' own reasoning may reduce the quality of academic work. Therefore, AI should be utilized as a learning assistant that supports critical thinking, creativity, and problem-solving rather than replacing students' independent intellectual engagement. The findings highlight the importance of promoting AI literacy and responsible AI use in higher education.
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