The Impact of AI-Powered Adaptive Learning on Student Teachers' Pedagogical Practices

Abstract

The incorporation of teacher technologies that stimulate student reasoning and provide personalized feedback modifies classroom dynamics and challenges traditional teacher roles (R. Rathmell, 2018). AI-powered adaptive learning programs that monitor, predict, communicate, and adjust content based on learner needs have the potential to inform teaching choices and reshape pedagogical approaches. Prior research has examined how novice teachers accommodate AI-adaptive learning when planning lessons and facilitating student learning, often revealing shifts in instructional choices. However, an understanding of the relationship between the utilization of such platforms and the pedagogical practices of student teachers remains absent. This study analyses evidence gathered through questionnaires, interviews, and observations from 56 student teachers across multiple institutions to consider the role of AI-powered adaptive learning in pedagogical decision-making and instructional practice.

Findings demonstrate that adaptive learning influences the pedagogical practices of student teachers, enabling personalization of instruction and encouraging engagement with student-centred pedagogies. The study, therefore, highlights the potential of AI-powered platforms to transform the practices and identities of teachers and underscores the importance of equipping student teachers to leverage these technologies effectively.