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

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-informe