Towards AI-Enhanced Work-Integrated Learning in ICT Programmes in Resource-Constrained Higher Education Contexts: An Autoethnography of Educator Experiences
DOI:
https://doi.org/10.38140/obp5-2026-10Keywords:
Work-Integrated Learning, equitable, harnessing, professional development, reimaginingAbstract
Work-Integrated Learning (WIL) plays a pivotal role in equipping graduates for professional practice; however, its integration varies in resource-constrained higher education settings, particularly in Information and Communication Technology (ICT) programmes. In such environments, limited availability of industry placements has led to an increased reliance on project-based learning, constituting 60 credits out of a total of 360 programme credits (16.7% of the qualification). Artificial Intelligence (AI) has emerged as a potential tool to enhance WIL through virtual simulations, adaptive feedback, and scalable learning support. Despite its potential, limited attention has been given to how educators engage with and navigate AI-enhanced WIL in disadvantaged contexts. This research adopts a qualitative approach, using a collaborative autoethnographic design involving five ICT lecturers and two WIL coordinators. Data were gathered through structured reflective questionnaires and a facilitated collaborative workshop, and analysed using a hybrid thematic approach that combines inductive and deductive coding informed by socio-technical systems theory. The outcomes reveal five interconnected themes: ambivalent emotional responses, reconceptualisation of pedagogy, a workload paradox, systemic constraints, and context-sensitive strategies for ethical and inclusive AI integration. These results underscore the interaction between social and technical elements and place educators as key figures in navigating AI-enhanced WIL. This study contributes to the academic discourse on AI in higher education by emphasising educator experiences and advocating for contextually grounded and ethically informed practices. It enhances comprehension of how socio-technical conditions influence ethical and inclusive digital advancements in higher education and aligns with UN SDG #4 (Quality Education) and Goal #9 (Industry, Innovation, and Infrastructure)
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