THE IMPACT OF ARTIFICIAL INTELLIGENCE-BASED LEARNING ON STUDENTS CRITICAL THINKING AND ACADEMIC ACHIEVEMENT IN HIGHER

Abstract

This study aims to examine the impact of Artificial Intelligence-based learning on students’ critical thinking skills and academic achievement in higher education. The research employed a quantitative approach with a quasi-experimental design involving two groups: an experimental group that received AI-based learning intervention and a control group that experienced conventional learning. The participants consisted of undergraduate students selected through purposive sampling. Data were collected using a critical thinking test and academic achievement scores, then analyzed using descriptive statistics, normality testing, homogeneity testing, independent samples t-test, and effect size analysis. The findings revealed that students in the experimental group demonstrated higher critical thinking performance than those in the control group. The mean score of critical thinking in the experimental group was 82.45, while the control group obtained a mean score of 74.30. The independent samples t-test showed a statistically significant difference between the two groups, t(78) = 4.27, p < 0.001. In terms of academic achievement, the experimental group also achieved a higher mean score of 85.10 compared to the control group, which obtained 76.85. These results suggest that AI-based learning has a positive and significant impact on enhancing students’ critical thinking skills and academic achievement in higher education. The study implies that integrating artificial intelligence into learning environments can support personalized learning, increase student engagement, and improve higher-order thinking skills.