SIDLIT 2026

The rapid integration of Generative AI (Gen AI) into education raises fundamental questions about whether its unique dynamics constitute a new learning paradigm. Utilizing Thomas Kuhn’s theory of paradigm shifts, this presentation investigates whether the anomalies created by Gen AI can be adequately explained by established learning paradigms: Behaviorism, Cognitivism, and Constructivism. Behaviorism cannot fully address the probabilistic autonomy of AI systems. Cognitivism struggles to accommodate cognitive processes distributed across human and AI systems. Constructivism, assuming shared cultural backgrounds, fails to account for dilemmas of authorship when learners co-construct meaning with algorithms. To resolve these anomalies and align with the SIDLIT 2026 theme, "Tech in Education: Transforming Learning for All," this session formally proposes "Generativism." In this new paradigm, learning is a distributed meaning-making process enacted within a human-AI-artifact ecology. Knowledge validation shifts to epistemic reflexivity, requiring learners to critically interrogate and refine both their reasoning and AI-generated outputs. The core mechanism is the "interaction episode," characterized by iterative cycles of prompt-based inquiry, AI generation, learner critique, and refinement. This presentation offers educators and researchers a coherent conceptual framework for designing and analyzing transformative learning environments in the Gen AI era.