Reimagining Teaching and Learning in the Age of AI: Inclusive, Student-Centred and Analytics-Driven Approaches for a Transformed SOTL Landscape

Reimagining Teaching and Learning in the Age of AI: Inclusive, Student-Centred and Analytics-Driven Approaches for a Transformed SOTL Landscape

Kabelo Benedict Mjone & Motalenyane Alfred Modise

Issue: Vol.7 No.1 2026 Article 8 pp. 96 – 112
DOI: https://doi.org/10.38159/ehass.2026718| Published online 25th February 2026
© 2026 The Author(s). This is an open access article under the CCBY license (http://creativecommons.org/licenses/by/4.0/).

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ABSTRACT

This study explores how Artificial Intelligence (AI) can transform Scholarship of Teaching and Learning (SoTL) by integrating student-centred pedagogy with learning analytics to create more inclusive, adaptive, and equitable educational environments. The purpose of the study is to critically examine how AI-driven systems such as adaptive learning platforms, intelligent tutoring, and predictive analytics can personalise instruction, enhance learner engagement, and inform pedagogical decisions through data-driven insights. Using a qualitative secondary research design, the study systematically reviews and synthesises peer-reviewed literature, institutional reports, and policy frameworks published between 2019 and 2024. The findings indicate that AI technologies can significantly enhance teaching effectiveness and learner inclusion when coupled with evidence-based and ethical implementation. However, challenges persist regarding data privacy, algorithmic bias, and unequal access to digital infrastructure, particularly in the Global South. The discussion underscores the importance of embedding AI integration within a humanistic and ethical framework to ensure transparency, fairness, and contextual sensitivity. The study recommends that higher education institutions develop robust governance policies, strengthen the digital infrastructure, and invest in continuous professional development to improve the literacy and ethical competence of educators. The study contributes to scholarship by providing a conceptual synthesis of how AI, inclusivity, and analytics intersect within SoTL, offering a framework for ethically grounded, student-centred educational transformation. It advances understanding of how evidence-informed AI practices can bridge pedagogical equity gaps and shape the future of inclusive learning in the digital era.

Keywords: Artificial Intelligence, Inclusive Pedagogy, Learning Analytics, Student-Centred Teaching, SoTL

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ABOUT AUTHOR(S)

Kabelo Benedict Mjone is an emerging researcher based in Welkom, Free State, South Africa. He works at the Central University of Technology, where he is building his academic and research journey as a novice researcher. Kabelo is passionate about learning, growth, and producing meaningful scholarly contributions. Driven by hard work and dedication, he continues to develop his research skills and looks forward to publishing more academic outputs in the future. His commitment to excellence and continuous improvement guides his aspirations as he advances in the research community.

Professor Modise Motalenyane Alfred is a distinguished South African scholar, educator, and academic leader whose contributions have significantly advanced accounting education, educational leadership, and rural education development in Southern Africa. He currently serves as Assistant Dean: Research, Innovation and Engagement in the Faculty of Humanities at the Central University of Technology, Free State (CUT), where he previously held several leadership positions, including Acting Senior Director for Research Development Support and Postgraduate Studies, Acting Assistant Dean: Teaching and Learning, and Departmental Manager in the Faculty of Economic and Management Sciences (Teacher Education).

TO CITE ARTICLE

Mjone, Kabelo Benedict, and Motalenyane Alfred Modise. “Reimagining Teaching and Learning in the Age of AI: Inclusive, Student-Centred and Analytics-Driven Approaches for a Transformed SoTL Landscape.” E-Journal of Humanities, Arts and Social Sciences 7, no.1 (2026): 96 – 112. https://doi.org/10.38159/ehass.2026718