Determinants of AI Utilization among Tanzania Higher Learning Students: Examining Trends, Predictors, and Academic Applications

  • Godwin Stephano Mollel Tanzania Institute of Accountancy
Keywords: AI Adoption, Higher Education, Academic Integrity, Generative AI, Student Engagement, Tanzania
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Abstract

This study examines the extent, frequency, and determinants of AI tool utilization among undergraduate students at the Tanzania Institute of Accountancy (TIA), Mbeya Campus. Employing a cross-sectional survey design, data were collected from 238 third-year students across four academic programs using a structured questionnaire. Descriptive and inferential statistical analyses were conducted to assess AI adoption trends and key influencing factors, including chi-square tests, ANOVA, and logistic regression. Findings reveal that ChatGPT (85.7%) is the most widely used AI tool, followed by QuillBot (41.1%) and Grammarly (11.8%), while citation generators have the lowest adoption (2.9%). AI is primarily used for writing assignments (47.5%) and idea generation (38.2%), with limited proofreading, research, and citation application. The study identifies familiarity, accessibility, academic engagement, and peer influence as significant predictors of AI adoption, while formal AI training shows no significant impact. Additionally, AI usage varies significantly across academic programs, highlighting the need for tailored institutional policies. The study concludes that while AI enhances academic productivity, the absence of regulatory frameworks poses challenges related to academic integrity and responsible AI usage. It recommends the development of AI literacy programs, faculty training, and ethical guidelines to ensure AI is integrated effectively into higher education while maintaining academic integrity

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Published
10 April, 2025
How to Cite
Mollel, G. (2025). Determinants of AI Utilization among Tanzania Higher Learning Students: Examining Trends, Predictors, and Academic Applications. East African Journal of Information Technology, 8(1), 57-69. https://doi.org/10.37284/eajit.8.1.2838