The rapid integration of Artificial Intelligence tools into the daily academic practices of undergraduate students has raised significant questions about the long-term consequences for independent learning, cognitive development, and measurable academic outcomes. This study examines the extent to which student dependence on AI tools influences learning outcomes across four dimensions: conceptual understanding, academic performance, independent study habits, and exam preparedness. Employing a quantitative, descriptive-correlational research design, structured questionnaire data were collected from 150 undergraduate students selected through stratified random sampling at College Name during the academic year 2024-2025. Primary data were analysed using descriptive statistics and chi-square tests of independence. All four research hypotheses were confirmed at the 0.05 level of statistical significance, establishing that higher levels of AI dependence are significantly associated with diminished conceptual understanding, weakened independent study habits, and reduced exam preparedness, even as moderate AI use correlates with improved surface-level learning outcomes. The paper concludes with targeted recommendations for educators, students, and institutional policymakers aimed at fostering a healthy and cognitively productive relationship with AI tools in higher education
Gaikwad et al. (Mon,) studied this question.