Generative AI in higher education: examining its influence on student engagement, learning outcomes, and ethical awareness

Abstract

The accelerated integration of Artificial Intelligence (AI) into higher education has introduced both transformative opportunities and complex ethical challenges across teaching, learning, and academic governance. This study explores university students’ awareness, perceptions, and usage patterns of AI technologies, particularly generative AI, and assesses their influence on academic engagement and perceived performance. Employing a structured quantitative methodology, survey data were collected from 300 students across diverse disciplines. Descriptive and inferential analyses, including multiple linear regression, were conducted to identify key predictors of AI-driven academic outcomes. Findings reveal that perceived benefits of AI and student engagement are strong positive predictors of improved academic performance, while access-related disparities emerge as significant barriers. Additionally, ethical concerns, policy awareness, and trust in AI-generated content shape students’ attitudes and behaviors, indicating that cognitive and contextual factors influence the educational impact of AI. Grounded in a theoretical framework integrating the Technology Acceptance Model (TAM) and Constructivist Learning Theory, this research highlights AI’s dual role as both an enabler and disruptor of equitable education. It calls for the implementation of transparent governance structures, equitable digital infrastructure, and ethical AI literacy within academic institutions. This study contributes to the evolving discourse on responsible AI adoption in education and offers practical guidance for policymakers, educators, and technology developers aiming to enhance academic integrity and digital inclusion in the AI age.