Academic Integrity and AI-Dependence of Tertiary Students under College of Education in University of Cabuyao: Basis for School Policy Recommendation

The study investigated the correlation between academic integrity and AI dependence among students from the College of Education at the University of Cabuyao, focusing on behaviors such as cheating, plagiarism, direct source duplication, and paraphrasing. A quantitative descriptive-correlational research design was employed, involving three-hundred-ten (310) selected respondents from first-year to fourth-year levels. The aim was to analyze students' engagement with AI tools in completing academic tasks and examined how this engagement relates to their academic integrity and learning effectiveness. Descriptive correlational statistics were utilized, incorporating a four-point Likert scale, weighted mean, and Pearson correlation to determine the significance of relationships between variables. Findings revealed that a majority of College of Education students demonstrated high levels of AI dependence, often engaging in various forms of academic dishonesty. The correlation between academic integrity and AI dependence in terms of reasoning showed a low correlation, with significant relationship observed in cheating, direct source duplication, and paraphrasing, but not in plagiarism. The analytical aspect, however, showed significant relationship across all variables. In terms of grammar-checking, there was a very low correlation with direct source duplication, indicating minimal association. Similarly, the writing aspect showed a very low correlation with direct source duplication, suggesting no significant relationship. The study underscored the urgent need for comprehensive institutional policies that regulate the ethical use of AI and promote responsible digital behavior. It also highlighted the importance of teacher-led educational frameworks to guide students in maintaining academic integrity. The research recommended the implementation of evidence-based policies aimed at fostering ethical AI usage and upholding academic honesty within higher education institutions.