Sep 2026· Journal of Educational Technology Development and Exchange· 0 citations
TL;DR
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.
Abstract
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.
It is found that GenAI adoption is high globally, 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.
Solomon Opoku· International journal of res...· 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.
Tunisian higher education is operating in something close to a policy vacuum on AI-assisted writing, and it is essential to formulate codes of ethics that incorporate the notion of so-called AI literacy into the educational process of teaching research methods and academic writing.
Mongi Aloui· Review of Artificial Intelli...· 0 citations
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.
O. Apata, Peter Oyewole, S. Ajose et al.· Journal of University Teachi...· 0 citations
The 2030 deadline for the United Nations Agenda for Sustainable Development is approaching. At the present universities’ field reveals a visible tension between stated commitment to sustainability and the structural change to fulfill it. Despite the institutional strategies and curriculum reform thoroughly examined by the literature, less attention has been given to the epistemic assumptions underlying indicator-driven sustainability agendas and to the ways managerial university governance may constrain more impactful approaches to sustainability. This study has two main aims: to examine how the SDGs are understood and used in teaching, research, and governance, including the structural and epistemic barriers reported by respondents; and to assess support for more critical and justice-oriented approaches to sustainability in higher education. Based on a cross-sectional survey of 54 academics recruited through transnational COST Action networks, the study combines descriptive statistics with thematic analysis of open-ended responses. Given the network-based sample, the findings are exploratory. They suggest that institutional engagement with the SDGs is often uneven and formed by existing organizational logics. A substantial majority of respondents support critical reformulation of the SDGs rather than unreflective agreement, pointing to a persistent tension between technocratic approaches to sustainability and broader consideration with epistemic justice. The findings also indicate that a more consequential approach on sustainability in higher education may require stronger recognition of Indigenous, local, community-based and intergenerational knowledge, as well as greater institutional capacity for critical and reflexive engagement beyond metric alignment.
Ivo Veiga, Diogo Guedes Vidal, Marie Rollo et al.· Open Research Europe· 0 citations
The study concluded that effective governance requires combining research evidence, sectoral frameworks, and institutional policies, while translating general principles into clear procedures at the university and course levels, and revealed the need for more specialized policies that address privacy, linguistic equity, data protection, and the transparency.
Mohammed Al Mutawtah· Academic Journal of Research...· 0 citations
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
