Explore the Role of Artificial Intelligence to Support Teachers at Higher Education Institutions in South Punjab
Year: 2025
Type: article
Study design: Observational Study
Abstract: Artificial Intelligence (AI) is rapidly transforming higher education worldwide by enabling innovative teaching and learning practices. This study explores the perceptions, attitudes, and intentions of university teachers toward AI adoption in public-sector higher education institutions in South Punjab, Pakistan. Employing a quantitative cross-sectional survey design, data were collected from 300 faculty members across multiple universities utilizing a self-developed Likert-scale questionnaire assessing constructs such as perceived usefulness, perceived ease of use, self-efficacy, and institutional support. Descriptive and inferential statistics, including correlation and multiple regression analyses, were performed utilizing SPSS to examine factors influencing AI adoption intention. The results reveal that perceived usefulness is the strongest predictor of faculty intention to integrate AI tools in their instructional practices, followed by perceived ease of use, self-efficacy, and institutional support. While overall attitudes towards AI were positive, infrastructural limitations and inadequate institutional support were noted as barriers to effective implementation. Differences in adoption intention were observed across academic ranks, with senior faculty showing greater readiness to adopt AI technologies. No significant gender differences were found. This study highlights the critical require for tailored professional development programs and enhanced technological infrastructure to support AI integration in South Punjab’s universities. The findings contribute valuable region-specific insights to policymakers, administrators, and educators aiming to leverage AI for improving teaching quality and digital transformation in Pakistan’s higher education sector.
DOI: 10.59075/c098vs88
Institutions: Ghazi University, Yangzhou University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4414110532