Research Article

Evaluating Generative AI Integration in Higher Education: A Mixed-Methods Study of Student Engagement and Academic Integrity in Pakistani Universities

28 reads
Digit. Soc. Rev., 2026, 1 (1), 22-28, doi: , ISSN 3106-8987

Abstract

The rapid proliferation of Generative Artificial Intelligence (GenAI) platforms such as ChatGPT, Claude, and Gemini has fundamentally transformed the higher education landscape, presenting concurrent opportunities for personalized learning and challenges to academic integrity. This study investigates the impact of GenAI integration on student cognitive engagement, self-directed learning, and academic honesty within Pakistani higher education institutions (HEIs). Utilizing a concurrent embedded mixed-methods research design, quantitative data were gathered from a stratified sample of undergraduate and postgraduate students (N = 482) across public and private universities in Pakistan, complemented by qualitative semi-structured interviews with students and academic faculty (N = 24). Structural Equation Modeling (PLS-SEM) revealed that GenAI tool utilization significantly predicts enhanced cognitive and behavioral engagement (β = 0.42, p < 0.001), particularly as an equalizer for non-native English speakers in academic writing and conceptual scaffolding. However, thematic analysis highlighted pervasive uncertainty regarding institutional guidelines, fear of false plagiarism accusations due to unreliable detection software, and varying ethical standards among departments. The findings emphasize that punitive measures are ineffective and advocate for clear institutional frameworks, assessment redesign, and AI literacy programs tailored to the socio-technical realities of developing higher education systems.

Keywords higher education student engagement generative ai academic integrity Pakistani Universities
Authors 3

The team behind this paper

3 authors, 3 institutions.

This paper Charles University Charles University 1 author American University of Beirut — Lebanon American University of … 1 author National Taiwan University — Taiwan National Taiwan Univers… 1 author Prof. Elena Rostova — corresponding author ER Prof. Elena Rostova ✉ Dr. Tariq Al-Mansoor TA Dr. Tariq Al-Mansoor Prof. Mei-Ling Chen MC Prof. Mei-Ling Chen

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28 reads over 1 month.

#2 most read in this journal this month
28
August 2026

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Bibliographic Information

Prof. Elena Rostova, Dr. Tariq Al-Mansoor, Prof. Mei-Ling Chen, (2026). Evaluating Generative AI Integration in Higher Education: A Mixed-Methods Study of Student Engagement and Academic Integrity in Pakistani Universities, Digital & Social Review, 1(1): 22-28
Bibtex Citation
@article{prof._elena_rostova2026dsr,
author = {Prof. Elena Rostova and Dr. Tariq Al-Mansoor and Prof. Mei-Ling Chen},
title = {Evaluating Generative AI Integration in Higher Education: A Mixed-Methods Study of Student Engagement and Academic Integrity in Pakistani Universities},
journal = {Digital & Social Review},
year = {2026},
volume = {1},
number = {1},
pages = {22-28},
doi = {},
url = {https://scimatic.org/index.php/show_manuscript/9179}
}
APA Citation
Rostova, P.E., Al-Mansoor, D.T., Chen, P.M., (2026). Evaluating Generative AI Integration in Higher Education: A Mixed-Methods Study of Student Engagement and Academic Integrity in Pakistani Universities. Digital & Social Review, 1(1), 22-28. https://doi.org/

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