Model of AI acceptance in higher education: arguing teaching staff and students perspectives

Abstract

Purpose

Artificial intelligence (AI) is constantly evolving and is poised to significantly transform the world, affecting nearly every sector and aspect of society. As AI continues to evolve, it is expected to create a more dynamic, efficient and personalized education system, supporting lifelong learning and adapting to the needs and pace of each student. In this research, we focus on testing the model of AI acceptance in higher education (HE) through human interaction-based factors including attitudes, competencies and openness to experience. Perceived benefits were our expectation to enhance AI acceptance in HE.

Design/methodology/approach

To test the model, we collected data from Arab HE institutions by spreading an online questionnaire. The sample consisted of 1,152 of teaching staff and students in Arab region, which were selected randomly. Partial least squares structural equation modeling (PLS-SEM) was employed to determine the interrelated dependence of relationships among variables. Furthermore, processing analysis was conducted to ensure the reliability and validity of questionnaires, multicollinearity and factor loading, in which the items were tested one more time to ensure their validity after translation into Arab language.

Findings

Results reveal that adopted attitude, digital competency and openness to experience have positive and significant relationship with both perceived benefits and AI acceptance in HE in the Arab region. The results also demonstrate the indirect impact of digital factors on AI acceptance in existence of perceived benefits, which was important in the validation of the model.

Originality/value

The research contributes to AI acceptance theory and research by providing evidence of AI acceptance in the Arab region. As generative AI applications continue to expand and change, the way we accept and interact with them will be different. This model could be adopted by authorities to facilitate the acceptance of AI in Arab HE institutions.

Citation

Hazaimeh, M. and Al-Ansi, A.M. (2024), "Model of AI acceptance in higher education: arguing teaching staff and students perspectives", International Journal of Information and Learning Technology, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJILT-01-2024-0005