Aug 2026· Journal of University Teaching and Learning Practice· 0 citations
TL;DR
The findings indicate that GenAI adoption in African HEIs is expanding but uneven, concentrated in digitally advanced nations, enhancing personalization, multilingual learning, and research productivity, yet raises ethical concerns about academic integrity.
Abstract
Despite Generative AI (GenAI) is transforming higher education globally, its implications for access, inclusion, personalized learning, assessment, and research productivity in African higher education institutions (HEIs) remain underexplored. This review synthesizes empirical evidence on how African HEIs are adopting GenAI, highlighting key opportunities, ethical challenges, and levels of institutional preparedness. We searched six academic databases, including Education Source Ultimate, Web of Science, Academic Search Ultimate, ERIC, APA PsycINFO, and Humanities Search Ultimate for peer-reviewed journal articles and conference papers published in English between 2022 and 2025. Out of the 110 records, 82 were screened after 28 duplicates were removed. We conducted full-text reviews on 51 eligible articles and 39 met the inclusion criteria. Our findings indicate that GenAI adoption in African HEIs is expanding but uneven, concentrated in digitally advanced nations, enhancing personalization, multilingual learning, and research productivity, yet raises ethical concerns about academic integrity. We recommend that institutions integrate GenAI literacy into faculty development and curricula and that policymakers prioritise governance frameworks that balance innovation and ethics.
Generative artificial intelligence (GenAI) has moved from novelty to routine presence in higher education within a few years, yet the evidence on its adoption, ethical implications, and cognitive effects remains fragmented across global, regional, and mechanism-focused literatures that are rarely read together. This narrative review synthesises 43 sources, comprising global systematic reviews and meta-analyses, comparative Global North-South studies, African and Tanzanian policy analyses, Ghana-specific empirical studies, and behavioural models linking GenAI use to critical thinking and ethical creativity. The review traces the evolution of this literature across three waves from 2022 to 2026 and finds that GenAI adoption is high globally, at roughly 74.5% among educators, and is growing rapidly across Africa, but that structural constraints, including limited infrastructure, low AI literacy, and underdeveloped institutional policy, shape a distinctly African pattern of opportunity and risk that global adoption figures obscure. In Ghana specifically, a large tertiary-institution survey shows technical infrastructure as a significant constraint even where urban-rural gaps are not, alongside evidence that roughly a third of surveyed undergraduates report low AI literacy despite substantial GenAI use. Critically, the review identifies that the empirically tested behavioural pathways linking GenAI use to critical thinking and ethical creativity, through self-regulated learning, innovative behaviour, and reduced reliance on prior knowledge, have been tested only in Taiwanese and Chinese settings, leaving open whether the same mechanisms hold under African infrastructural and institutional conditions. The review concludes with practical implications for institutions and policymakers and a concrete future-research agenda centred on this gap, arguing that testing these pathways in Ghana is the field's single most valuable next study.
Solomon Opoku· International journal of res...· 0 citations
With the rapid development of artificial intelligence (AI), generative artificial intelligence (GenAI) has been widely applied in higher education, specifically bringing both opportunities and potential challenges. This review focuses on the application of GenAI in teaching, learning, assessment and institutional governance within the higher education context. By adopting a literature review approach, this paper reviews and analyses research on GenAI in education. The findings reveal that GenAI can effectively improve teaching efficacy, enable personalised learning experiences, and streamline assessment procedures. However, its implementation also draws attention to concerns regarding academic integrity, data privacy, algorithmic bias, and ethical governance. In accordance, higher education institutions should strengthen AI literacy training for faculty and students, while improving institutional guidelines and establishing responsible governance mechanisms. Future research is recommended to conduct longitudinal investigations, cross-cultural comparative analyses, and in-depth studies on teacher professional development, in order to support the sustainable and long-term integration of GenAI into higher education.
Xi Bi· Exploring Science Academic C...· 0 citations
This systematic literature review examines the ethical challenges associated with integrating generative chatbots in educational contexts. Guided by the PRISMA 2020 framework, the review synthesised peer-reviewed empirical and theoretical studies published between 2022 and 2025 and retrieved from Scopus and Web of Science. Following systematic screening and eligibility assessment, 16 studies were included in the final synthesis. The findings identified four primary ethical domains: student data privacy and protection; academic integrity and AI-assisted plagiarism; algorithmic bias and fairness; and institutional governance and policy readiness. While generative chatbots offer significant pedagogical benefits, including personalised learning, enhanced feedback, and expanded access to educational support, their unregulated use may exacerbate digital inequalities, compromise educational integrity, and reinforce existing biases. The review highlights the need for transparent institutional policies, educator training, ethical AI literacy, strong data governance frameworks, and equitable digital infrastructure. These measures are essential to support the responsible, ethical, and inclusive integration of generative AI technologies in education.
This systematic review, conducted in accordance with PRISMA 2020 guidelines, examines the ethical dilemmas associated with the use of Generative Artificial Intelligence (GAI) in education and analyses their implications for the achievement of Sustainable Development Goal 4 (SDG 4), with a focus on inclusive and equitable quality education. The review draws on 24 peer-reviewed studies published between December 2022 and December 2024, covering diverse educational levels and geographical contexts, with a predominance of Global North perspectives and limited representation from the Global South. The analysis reveals four primary themes: academic integrity, algorithmic equity, data privacy, and the potential contribution of GAI to inclusive and quality education. These themes manifest differently across educational levels and contexts, with academic integrity concerns being more prominent in higher education, while issues of access, equity, and infrastructural dependency are more salient in low-resource and underrepresented settings. The findings reveal that current discussions on GAI in education are largely characterized by retrospective and crisis-driven ethical framings, predominantly focused on risks such as plagiarism, bias, and misinformation, while offering limited engagement with proactive, context-sensitive strategies aligned with SDG 4.
Eva García-Beltrán· Journal of Educational Techn...· 0 citations
A conceptual framework offering AI designers, teacher educators, and policymakers a psychologically grounded, empirically mapped, and internationally contextualised basis for developing AI-supported educational systems that advance equity, learner engagement, and meaningful educational transformation is proposed.
Arpana Koul· Review of Artificial Intelli...· 0 citations
This study provides a narrative review of contemporary challenges in teaching English as a Foreign Language (EFL) in higher education across diverse international contexts. It synthesizes evidence from peer-reviewed studies published between 2020 and 2025. The analysis identifies six interrelated domains of difficulty: student-related factors (proficiency, motivation, anxiety), cultural and linguistic diversity, pedagogical and methodological constraints, community attitudes and perceptions, curriculum and assessment systems, and teacher, technological, and institutional limitations. Rather than representing isolated barriers, these challenges interact across policy, institutional, pedagogical, and learner levels. Positive attitudes toward English often coexist with critiques of inequality; Communicative Language Teaching (CLT) is endorsed in policy but undermined by exam-driven curricula; and technology promises innovation yet exacerbates inequities without adequate training and infrastructure. The review argues that sustainable improvement depends on systemic coherence across policy, institutional governance, curriculum design, teacher development, and learner-centered practice rather than isolated interventions. Future research should expand comparative research across underexplored regions, employ longitudinal designs to assess the durability of reforms, and critically examine the role of emerging tools such as artificial intelligence (AI) in language instruction. By integrating evidence across diverse educational contexts into a coherent multi-level framework, the study contributes a holistic perspective on improving EFL teaching in higher education.