Factors Shaping the Adoption of Artificial Intelligence Tools by Higher Education Students in Tanzania

Dickson  Utonga; John K.  Gwanyemba; Jacob J.  Kilamlya

doi:10.52919/arebus.v6i01.79

Dickson Utonga Department of Project Planning and Management, Tengeru Institute of Community Development, P. O. Box 1006, Arusha, Tanzania https://orcid.org/0000-0001-9037-2825
John K. Gwanyemba Department of Project Planning and Management, Tengeru Institute of Community Development, P. O. Box 1006, Arusha, Tanzania https://orcid.org/0000-0001-6242-9556
Jacob J. Kilamlya Department of Project Planning and Management, Tengeru Institute of Community Development, P. O. Box 1006, Arusha, Tanzania https://orcid.org/0009-0005-9417-1242

DOI: https://doi.org/10.52919/arebus.v6i01.79

Keywords: Adoption, Perceived Usefulness, Ease of Use, Resource Availability, Higher Education Students, Artificial Intelligence Tools

Abstract

Artificial Intelligence (AI) has emerged as a significant innovation with far-reaching global impacts. Nevertheless, students in higher education institutions utilise AI tools inconsistently for various reasons, affecting their practical use. This research examines the factors influencing the adoption of AI tools for academic purposes, specifically learning and research, by higher education students in Tanzania. The study involved 142 students from diverse higher learning institutions and employed a binary probit regression framework to analyse these factors. The results indicate that access to technology increases the likelihood of students adopting AI tools. Additionally, their perceived ease of use and usefulness positively influence the likelihood of adoption. Gender analysis reveals that female students are less likely to adopt AI tools than their male counterparts. Moreover, limited user-friendliness negatively impacts AI tool adoption. The findings highlight the necessity of improving user-friendly interfaces, enhancing technological access, and providing technical support to promote adoption. This research contributes to our understanding of the dynamics of AI adoption in higher education contexts, offering practical implications for policymakers, academic institutions, and developers interested in encouraging the use of AI among students.

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