Learner Engagement & Motivation in EFL Higher Education: The Pedagogical Role of Generative AI Tools in Educational Ecosystems

This thesis examines how university-level English as a Foreign Language (EFL) learners perceive the pedagogical role of generative artificial intelligence (GenAI) tools within higher education learning ecosystems. Informed by the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) and Self-Determination Theory (SDT), the study examines an intervention that investigates how these tools shape learners’ engagement, motivation, and perceived language development. A descriptive case study design was adopted involving 167 undergraduate learners enrolled in a foundational English programme, drawing on open-ended survey responses using reflexive thematic analysis. Findings indicate that students perceived notable improvements in areas such as writing, vocabulary development, and grammatical awareness, reporting a shift from passive reception of corrective feedback to more autonomous, iterative interaction with GenAI tools. Learners described heightened intrinsic motivation and self-regulation, often engaging with AI tools beyond formal course requirements. The data also highlight influential socio-institutional dynamics, including peer norms, uncertainties surrounding institutional policy, and varying levels of AI and prompt literacy. Students emphasised the need for structured institutional support, explicit usage guidelines, and ethical clarity regarding GenAI adoption. Drawing together UTAUT-2 and SDT, the thesis develops the Generative AI Engagement and Motivation (GAIEM) Framework that captures four interrelated dimensions, Enabling Environment, Mediated Engagement, Internalisation Mechanisms, and Learner Agency, illustrating how GenAI use is embedded within broader educational ecosystems. The study contributes to technology-enhanced language learning by offering empirically grounded insights and actionable recommendations for the ethical, balanced, and pedagogically sound integration of GenAI into EFL curricula. While the research is situated within a single institutional context, it identifies avenues for future work, including longitudinal studies, cross-institutional comparisons, and investigations incorporating teacher perspectives.