Bridging Artificial Intelligence, Equity, and Innovation in Early Childhood Teacher Education: Strategic Recommendations and Future Directions

Abstract

This chapter assesses how artificial intelligence (AI) is being integrated into Early Childhood Teacher Education (ECTE), focusing on equity, ethics, and innovation in relation to Work-Integrated Learning (WIL). It draws upon Bronfenbrenner's socio-ecological systems model, Wenger's concept of communities of practice, and critical equity and transformative pedagogies. The chapter conceptualises AI-mediated WIL as a relational ecosystem linking pre-service teachers, mentors, lecturers, and EdTech developers. A qualitative multiple case study methodology was employed to examine the experiences of urban, peri-urban, and rural-based pre-service teachers, mentors, and college lecturers in relation to the use of AI-based WIL. Data were collected through various methods, including semi-structured interviews, focus group discussions, and document analysis. Data collection and analysis involved the application of thematic and cross-case methodologies. Findings from the research indicate a tri-narrative approach whereby AI can provide increased levels of reflection, strengthen mentoring, and enhance opportunities for collaboration and innovation for ECTE students. However, differences in the availability of infrastructure, digital competencies, and ethical governance can limit access to equitable participation. Equitable access to AI-based WIL will require support mechanisms such as mentorship, participatory governance, and support from colleagues and institutions. As such, the RAIIF provides an evidence-based framework for the effective implementation of AI at micro, meso, and macro levels through ethical oversight, co-created innovation, and ongoing professional development. Finally, the chapter will provide recommendations for policymakers and practitioners to promote equitable, culturally responsive, and ethically governed AI-mediated WIL.