From Execution to Education: A Bloom-Aligned Framework for Measuring Educational Control in LLMs

Introduces a Bloom-aligned framework for measuring 'educational control' in LLMs: the ability to preserve a task's instructional intent while shifting its cognitive demand toward higher-order Bloom levels, offering a metric for evaluating whether AI assistance scaffolds or shortcuts learning. The work connects to broader debates about how Generative AI systems reshape Student Experience and the conditions under which AI support scaffolds rather than undermines learning. It has direct implications for Pedagogy AI Mistakes and the risk of Over Reliance when assistants absorb too much of the cognitive load. Findings also bear on AI Literacy and Self Regulated Learning, and on how institutions should govern Student Experience and Academic Integrity. Practitioners in Higher Ed and teachers can use the evidence to calibrate when to deploy LLM-based help and how to pair it with feedback that preserves learning gains.

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S. Bekkouch, T. Constantinou, M. Ovaere, et al. (2026). From Execution to Education: A Bloom-Aligned Framework for Measuring Educational Control in LLMs. arXiv:2607.08009.