Improving Attitudes Towards Calculus through Inquiry-Driven Collaborative Learning Model + ChatGPT among Preservice Mathematics Teachers: A Quasi-Experimental Study

Abstract

This study investigated the effect of Inquiry-Driven Collaborative Learning enriched with ChatGPT (IDCL+ChatGPT) on pre-service teachers’ attitudes toward calculus in Kaduna State, Nigeria. Anchored on Social Cognitive Theory, the study adopted a quasi-experimental pretest-posttest non-equivalent control group design. The population comprised 1,122 NCE II Mathematics students in public NCE-awarding institutions in Kaduna State, from which 133 students were selected. Participants were assigned to IDCL+ChatGPT (n = 53), IDCL-only (n = 45), and conventional teaching (n = 35) groups. Data were collected using the Calculus Attitude Questionnaire (CAQ), validated by experts, with a reliability coefficient of 0.811. Descriptive statistics addressed the research questions, while ANCOVA and Bonferroni post hoc tests tested hypotheses at the 0.05 significance level. Results revealed a significant group effect on posttest attitude scores, F(2,129) = 27.630, p < .001, partial η² = .300. Bonferroni comparisons showed that IDCL+ChatGPT significantly outperformed conventional teaching (p < .001), while IDCL-only also significantly outperformed conventional teaching (p < .001). However, the difference between IDCL+ChatGPT and IDCL-only was not significant (p = .071). The study concludes that IDCL effectively fosters positive attitudes toward calculus, while ChatGPT provides additional instructional support that enriches students’ learning experiences and supports meaningful classroom interaction and engagement