Artificial Intelligence in Higher Education: A Case Study of Faculty Teaching Methodologies at a Private University

Abstract

This qualitative case study investigates faculty perspectives on artificial intelligence (AI) integration within a private university context, examining pedagogical, administrative, and ethical implications. Data collected through semi-structured interviews with faculty across four disciplines revealed ambivalent yet cautiously optimistic attitudes. Participants acknowledged AI’s potential to enhance personalized learning and reduce bureaucratic burdens through automation. However, three critical barriers emerged: (1) insufficient institutional technological infrastructure, (2) lack of systematic faculty training programs, and (3) unresolved ethical dilemmas surrounding data privacy, algorithmic bias, and academic integrity. Notably, while faculty welcomed AI as a supplemental tool, they unanimously emphasized the irreplaceable role of human judgment in pedagogy. The study contributes to emerging scholarship on educational technology by proposing an ethical implementation framework that reconciles efficiency gains with core academic values. Practical recommendations address policy development and targeted professional training to support responsible adoption. These findings offer timely insights for higher education institutions navigating AI integration while preserving pedagogical integrity and equity considerations.