Cross-Cultural Adoption of Generative Artificial Intelligence in Higher Education: A Longitudinal Socio-Technical Analysis Using the AI-CLASSIC Framework

James Alexander Gordon on 27th August 2025



Author Information

Lawrence M. Ibeh, Berlin School of Business and Innovation, Germany
Benjamin Bensam Sambiri, Berlin School of Business and Innovation, Germany
Kaddour Chelabi, Berlin School of Business and Innovation, Germany
Sushma Kumari, Berlin School of Business and Innovation, Germany

Abstract

Global interest in Artificial Intelligence (AI), and particularly Generative AI (GenAI), has increased sharply over the past decade. While adoption in higher education is accelerating, it remains uneven across countries, institutions, and cultural contexts. Most existing research emphasises automation efficiency, AI literacy, or short-term classroom use, offering limited insight into how GenAI becomes embedded within educational systems over time. This paper introduces AI-CLASSIC (AI Adoption in Classroom Instruction and Cross-Cultural Comparison), a longitudinal, multi-level socio-technical framework integrating classroom practices, institutional readiness, and societal discourse. Drawing on pilot data from Germany, Nigeria, and India, we demonstrate that similar levels of GenAI usage may arise primarily because of different adoption mechanisms. Regression-based analyses identify perceived usefulness as a universal driver, while risk perception, institutional constraints, and cultural expectations shape adoption pathways differently across contexts. By operationalising adoption, the AI-CLASSIC framework proposes the AI Competency Index (ACI), which will be systematically validated in subsequent longitudinal work. This study advances cross-cultural comparability and provides a scalable foundation for predictive modelling and policy-relevant foresight in AI-enhanced higher education.


Paper Information

Conference: ACE2025
Stream: Design

This paper is part of the ACE2025 Conference Proceedings (View)
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To cite this article:
Ibeh L., Sambiri B., Chelabi K., & Kumari S. (2026) Cross-Cultural Adoption of Generative Artificial Intelligence in Higher Education: A Longitudinal Socio-Technical Analysis Using the AI-CLASSIC Framework ISSN: 2186-5892 – The Asian Conference on Education 2025: Official Conference Proceedings (pp. 485-494) https://doi.org/10.22492/issn.2186-5892.2026.37
To link to this article: https://doi.org/10.22492/issn.2186-5892.2026.37

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