Jul 2026· International Journal of Studies in Inclusive Education· 0 citations
Abstract
As artificial intelligence (AI) becomes increasingly embedded in higher education, empirical evidence on how institutional governance shapes its equitable and responsible implementation in South African universities remains limited. This study examined how institutional policies and governance practices influence the implementation and equitable use of AI in undergraduate education while contributing to international discourse on responsible AI governance. Guided by an interpretivist research paradigm, the study adopted a qualitative approach and employed a single-case study design within one public university in South Africa. Participants comprised university leaders, academic staff, professional support staff, and undergraduate students involved in or affected by AI governance and implementation. Data were collected through semi-structured interviews, focus group discussions, and document analysis and analysed using thematic analysis supported by inductive coding. The findings indicate that limited policy transparency, context-insensitive governance frameworks, unequal access to AI technologies, and weak institutional accountability can reinforce educational inequalities, particularly among first-generation and under-resourced students. Conversely, participatory governance, transparent decision-making, stakeholder engagement, and enhanced digital literacy promote more equitable and responsible AI implementation. The study proposes a multi-level governance model integrating institutional policy, stakeholder participation, and pedagogical practice to strengthen equitable AI adoption. It concludes that higher education institutions should develop context-sensitive AI governance frameworks, strengthen institutional capacity, and expand equitable access to AI technologies to advance fairness, inclusion, and responsible AI implementation.
Regression analysis showed that AI familiarity, frequency of use, and policy awareness were significantly associated with stronger support for empowerment-oriented governance, which inform a five-pillar framework for responsible AI integration encompassing AI Literacy Integration, Stage-Based Access, Transparent Use Norms, Assessment Innovation, and Faculty Development.
A. Akib, Mohammad Aseer Intisar, Md. Sabbir Ahmed et al.· The Compass· 0 citations
The ability of institutions to leverage opportunities to transform governance in higher education depends on adopting anticipatory governance models that emphasize foresight and stakeholder engagement, as well as adopting changes to the traditional role of both leaders and educators to become data literate, inclusive, collaborative, and forward-thinking.
S. Baroudi· International Journal of Edu...· 1 citation
The study identifies key themes in generative AI governance, including responsible experimentation, transparency, AI literacy and faculty discretion in policy implementation, including responsible experimentation, transparency, AI literacy and faculty discretion in policy implementation.
Abdullah Alotaibi, A. Aseery, Abdulaziz A. Alfayez et al.· British Educational Research...· 0 citations
The study proposes a phased, ethically grounded governance framework tailored to Africa’s educational context, contributing new insights into readiness differentials, governance diffusion, and policy convergence, offering a foundation for inclusive, future-oriented AI policy in African higher education.
Dr. Sixbert Sangwa, Dennis Ngobi, Emmanuel Ekosse et al.· Artificial Intelligence and...· 11 citations· ⚡1
Background
Research-policy partnerships are widely used to support evidence-informed reform, yet how evidence actually shapes policy and practice in low-income education systems remains poorly understood. This article asks how, and under what relational and institutional conditions, evidence generated by Research on Improving Systems of Education (RISE) Ethiopia contributed to national policy on equity, learning and accountability.
Methods/data
The study uses qualitative data, drawing on 22 semi-structured interviews with senior federal policy makers, regional officials, development partners and local non-governmental organisations (NGOs), complemented by documentary analysis of RISE outputs, education sector plans and policy materials.
Approach
Interview transcripts and documents were analysed using a thematic analysis framework, combining deductive coding organised around bounded mutuality, sustained interactivity and policy adaptability with inductive coding of emergent evidence-to-policy contribution pathways.
Results
RISE evidence contributed to the bottom-up design of the four-year Education Transformation Programme and its implementation vehicle, Education Transformation Operation for Learning (2025-2029), supported a reframing of national discourse from schooling expansion towards foundational learning, helped develop an equity narrative grounded in observed learning gains among disadvantaged students within a school year, and informed COVID-19 school-reopening deliberations. Contributions were clearest where trusted relationships, timely decision windows and actionable evidence converged; where any of these elements was weak, policy impact was correspondingly less direct.
Conclusion
The article shows that policy contribution was enabled by relational conditions that allowed evidence to be heard, trusted and acted upon. It offers a transferable framework for embedding research in policy systems and underscores the need for sustained institutional investment in the capacity for evidence use.
M. Araya, Pauline Rose, D. Tiruneh et al.· Evidence & Policy: A Journal...· 0 citations
Applying Critical Policy Analysis and Jencks’ framework of educational opportunity, the study shows that policy silence is not the absence of governance but a governance choice, one that shapes how access, responsibility, and fairness are determined.
A. Miles, Khalid H. Arar· Improving Schools· 0 citations