STUDENTS’ PERCEPTIONS OF ARTIFICIAL INTELLIGENCE IN UNIVERSITY LEARNING: BENEFITS, LIMITATIONS, AND ETHICAL CONCERNS

Abstract

Artificial intelligence (AI) is increasingly being used in higher education, offering opportunities to improve teaching effectiveness, student learning, and personalized academic support. However, its integration also raises concerns regarding academic integrity, data privacy, information accuracy, and overdependence. This study examined university students’ perceptions of AI in learning, focusing on its benefits, limitations, and ethical concerns. A quantitative approach and descriptive survey design were employed. Data were collected from 200 students, including 100 from Government College University Faisalabad (GCUF) and 100 from The University of Faisalabad (TUF), using a structured questionnaire based on a five-point Likert scale. The data were analyzed using SPSS Version 26 through descriptive statistics, an independent-samples t-test, and multiple regression analysis. The findings revealed an overall positive perception of AI-supported learning, with a grand mean of 4.18 (SD = 0.78) for perceived opportunities. Personalized learning received a mean score of 4.21, while teaching effectiveness, student learning outcomes, and administrative support also received high ratings. ChatGPT was the most frequently reported AI tool (88%), followed by Grammarly AI (81%). Despite these perceived benefits, students expressed considerable ethical concerns, particularly regarding academic dishonesty and plagiarism (M = 4.41) and data privacy (M = 4.34). Students at TUF reported significantly more positive perceptions of AI integration than those at GCUF (t = -3.82, p < .001). Regression analysis showed that perceived AI opportunities and personalized learning positively predicted perceptions of AI-supported teaching and learning, whereas ethical concerns and implementation challenges negatively predicted them. The study concludes that AI has considerable perceived potential in university education, but its responsible integration requires clear institutional policies, digital infrastructure, ethical awareness, and continued human supervision.