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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Information Systems and Informatics
Bester Chimbo
University of South Africa
Computer Science & IT

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Adoption of Sustainable and Human-Centered Explainable AI in Higher Education. An Extended UTAUT Perspective Fine Masimba; Bester Chimbo; Kudakwashe Maguraushe
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13124

Abstract

As Artificial Intelligence permeates higher education, concerns regarding its "black-box" nature, ethical implications and environmental sustainability have intensified. This study develops and empirically validates an Extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework to investigate the factors influencing AI adoption among students in Zimbabwean universities. The model integrates five contemporary AI constructs which are perceived explainability, trust in AI, perceived human-centeredness, perceived sustainability and perceived fairness into the traditional UTAUT1 framework. Data were collected through a structured Likert-scale questionnaire from a sample of 352 students across major Zimbabwean HEIs. Regression analysis was employed to examine the relationships among constructs. The extended model explains 68.4% of the variance in behavioural intention (R² = 0.684). Results indicate that while performance expectancy and trust in AI are the strongest predictors, perceived explainability and human-centeredness significantly enhance adoption intentions. Surprisingly, perceived sustainability emerged as a nascent but significant driver, reflecting a growing awareness of "Green AI." The findings provide critical theoretical contributions by bridging the gap between instrumental adoption drivers and human-centric design. Practically, the study offers a roadmap for university administrators and AI developers in developing countries to foster transparent, fair and sustainable AI ecosystems.
Advancing Inclusive Educational VR: A Bibliometric Study of Interface Design Kudakwashe Maguraushe; Fine Masimba; Bester Chimbo
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1271

Abstract

While virtual reality (VR) has shown transformative potential in education, its accessibility and inclusivity for learners with disabilities remain insufficiently explored. This study offers the first bibliometric mapping of educational VR interface design for inclusivity, analysing 4,735 documents from 1,714 sources (2020-2025) using Biblioshiny and VOSviewer. The analysis reveals a 13.22% annual publication growth rate, an average of 10 citations per document, and an international co-authorship rate of 25.85%, reflecting both rapid expansion and increasing collaboration. Dominant research themes include user experience, usability, and the metaverse, while underexplored areas such as cognitive accessibility and neurodiverse learners highlight emerging opportunities. The findings demonstrate a concentration of scholarly activity in North America and Asia, with limited representation from the Global South. Practically, the study informs developers on designing adaptive interfaces, guides educators in implementing inclusive VR pedagogies, and provides policymakers with evidence for promoting equitable digital learning ecosystems. By identifying trends, gaps, and collaboration patterns, this research advances the discourse on inclusive educational VR and underscores the need for interdisciplinary, AI-driven accessibility strategies that ensure equitable participation for all learners.
Integrating Human-Centered AI into the Technology Acceptance Model: Understanding AI-Chatbot Adoption in Higher Education Fine Masimba; Kudakwashe Maguraushe; Bester Chimbo
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1316

Abstract

Artificial intelligence (AI) is transforming education by enhancing assessments, personalizing learning, and improving administrative efficiency. However, the adoption of AI-powered chatbots in higher education remains limited, primarily due to concerns about trust, transparency, explainability, perceived control, and alignment with human values. While the Technology Acceptance Model (TAM) is commonly used to explain technology adoption, it does not fully address the challenges posed by AI systems, which require human-centered safeguards. To address this gap, this study extends TAM by incorporating Human-Centered AI (HCAI) principles—explainability, transparency, trust, and perceived control—resulting in the HCAI-TAM framework. An empirical study with 300 respondents was conducted using a structured English questionnaire, and regression analysis was applied to assess the relationships among variables. The model explained 65% (R² = 0.65) of the variance in behavioral intention and 55% (R² = 0.55) in usage behavior. The findings highlight that integrating HCAI principles into TAM enhances user adoption of AI chatbots in higher education, contributing both theoretically and practically.
Co-Authors Fine Masimba Kudakwashe Maguraushe