Browsing by Author "Mahenge, Michael"

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    Determinants of artificial intelligence use in research at higher learning institutions of Tanzania
    (African Quarterly Social Science Review, 2025) Mbilinyi, Augustino Peter; Mwalukasa, Nicholous; Mahenge, Michael
    Artificial Intelligence (AI) is increasingly recognized as a transformative tool in higher education, yet its adoption for research purposes in Tanzanian Higher Learning Institutions (HLIs) remains limited. This study assessed the determinants of using AI in HEIs of Tanzania, specifically, the study examined the extent of AI usage in research and the factors influencing its adoption, it was guided by the Unified Theory of Acceptance and Use of Technology (UTAUT) model. A cross-sectional research design with a mixed-methods approach was used. The target population for the study comprised 1872 academic staff, however, only 253 participants were studied. The study sample was selected using systematic, purposive, and convenience sampling techniques from Sokoine University of Agriculture (SUA), Mbeya University of Science and Technology (MUST), and the University of Dodoma (UDOM). Collected data was coded on IBM SPSS version 20. Descriptive statistical analysis, such as mean, frequency, and percentages, was used, and multiple linear regression was used to analyze the determinants of using AI in Research activities. The findings revealed that AI tools, such as Grammarly, QuillBot, and ChatGPT, were primarily used for research tasks such as grammar checking, paraphrasing, and brainstorming ideas. Moreover, ChatGPT was used in brainstorming and literature reviews. Furthermore, the study reveals that performance expectancy (β=0.23), effort expectancy (β =0.20), teaching experience (β =-.039), and workload (β =-.083) significantly influenced AI adoption. The study concludes that AI tools were seldom used for research purposes. The study recommends that, in order to enhance AI usage, there is a need for universities to create awareness and increase knowledge on AI among academics, as well as to integrate AI tools into the research life cycle.