A Motion of Learning: Transitional Space as A Pedagogical Framework

Abstract Book of the 11th International Conference on Research in Education, Teaching and Learning

Year: 2026

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A Motion of Learning: Transitional Space as A Pedagogical Framework

Dr. Eilat Toker

ABSTRACT:

What is the space between shared knowledge and personal knowledge? Winnicott called it the transitional space, a zone belonging neither to object nor subject, but to the motion between them. This presentation proposes that this space constitutes the psychological and pedagogical foundation of all meaningful learning, and that generative AI is a tool capable of generating it within the formal school learning environment. The model’s point of departure is philosophical: contemporary education moves between two worldviews. Modernism posits unified knowledge, a single truth, and a fixed pace for all. Postmodernism recognizes the plurality of perspectives, the subjectivity of the learner, and the legitimacy of diverse learning pathways. The tension between them is not a paradox to be resolved, it is a creative engine to be designed. The “Motion of Learning” model realizes this through an explicit architecture: a Shared Core embodying the “modern” and Personal Learning Paths embodying the “postmodern.” The continuous movement between these two poles generates the transitional space itself. Generative AI is the operational engine that transforms this philosophical tension into actionable personalized learning: through continuous formative assessment and adaptive planning grounded in four dimensions of individual difference: Pace, Interest, Environment, and Style (PIES). It enables each learner to move between the core and their own path, exercising bounded autonomy. AI-integrated learning is, therefore, not a technological substitute, it is the realization of the Winnicottian transitional space: a personalized learning environment emerging within the tension between modernism and postmodernism, enabling motion within it.

Keywords: Transitional Space, Personalized Learning, Generative AI, Modernism–Postmodernism, Core–Pathway Duality