AI-Driven Teacher Preparation: A Constructivist and Cognitive Learning Perspective
TL;DR
It is suggested that effective teacher preparation must transcend content delivery and focus on equipping teachers with adaptive, student-centred methodologies grounded in cognitive science.
Abstract
This paper explores the preparation of teachers through the lens of modern educational and learning theories, with particular attention to how artificial intelligence (AI) can augment educational planning and professional teacher development. Three major theoretical frameworks are examined: (1) Constructivist Theory, rooted in Piaget's cognitive development model, emphasizing the learner's active role in knowledge construction; (2) Meaningful Learning Theory (Ausubel), which underscores the critical link between new knowledge and pre-existing cognitive structures; and (3) Information Organization and Processing Theory, which explains how memory encoding and retrieval affect learning outcomes. The paper further integrates the McCarthy 4MAT model of learning styles to illustrate how AI-driven, learner centred strategies can be operationalized in contemporary teacher preparation programmers. Findings suggest that effective teacher preparation must transcend content delivery and focus on equipping teachers with adaptive, student-centred methodologies grounded in cognitive science.