Toward Responsible AI Governance in Higher Education: AI Literacy, Use, Perceived Risks, and Policy Needs Among Students at Kalinga State University

Abstract

This cross-sectional study examined four student-level foundations of responsible artificial intelligence (AI) governance at Kalinga State University: AI literacy, patterns of academic use, perceived risks, and expectations for institutional policy. A structured 42-item questionnaire was completed by 667 students. The analysis used frequency, percentage, weighted mean, standard deviation, and Pearson correlation. Respondents were concentrated in the College of Engineering and Information Technology (48.43%), and 48.28% described their digital proficiency as basic. AI literacy was high overall (M = 4.08, SD = 0.60), with the strongest rating for familiarity with AI (M = 4.26). Using the interpretation bands stated in the method, overall AI use was high by tool category (M = 3.51, SD = 0.71) and academic purpose (M = 3.50, SD = 0.76), although the use of AI for data analysis and research remained moderate (M = 3.38). Students also reported high perceived risk (M = 3.99, SD = 0.64) and high policy need (M = 3.91, SD = 0.69). Every pair of major variables was positively associated (p < .001); the strongest relationship linked perceived risks and policy needs (r = 0.771). The results support a governance approach that combines differentiated AI-literacy training, explicit rules for acceptable academic use, privacy and fairness safeguards, and regular consultation with students and faculty.