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From Gradual Release of Responsibility to Gradual Release of Technology: A Case for the Staged Use of AI in Formal Education
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DOI：10.3390/educsci16081291.png)
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Abstract
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Debate over the role of generative artificial intelligence in formal education is marked by sharply divergent claims about its effects on student learning. Much of this disagreement reflects a failure to distinguish AI-supported performance from durable learning. This conceptual article aims to address a central gap in the literature by focusing on when and how students should be guided to rely on AI. It introduces the Gradual Release of AI Technology (GRAIT) model, extending Pearson and Gallagher’s gradual release of responsibility to the staged use of generative AI technologies in K-12 education. The model distinguishes gradual release of responsibility, which concerns who performs the cognitive work, from gradual release of AI technology, which concerns when and how that work may be scaffolded, augmented, or offloaded to AI. Three phases are proposed: independent cognition, where foundational knowledge and skills are developed without AI; shared cognition, where AI is introduced through teacher-guided interaction; and offloaded and reallocated cognition, where learners strategically delegate and reallocate aspects of thinking while retaining evaluative judgement. Progression depends on demonstrated knowledge, skill proficiency, epistemic understanding, and AI literacy. The central question thus addresses when and how AI use should be staged according to learner readiness.
Keywords:
gradual release of AI technology
generative artificial intelligence
cognitive offloading
learning versus performance
metacognition
expertise development
instructional scaffolding
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