Large-Scale Analysis Reveals Inconsistent Definitions of Learner Agency and Autonomy Across 14,000 Publications
A new preprint analyzing over 14,000 publications finds that the concepts of 'learner agency' and 'autonomy' are used inconsistently across educational research, with existing measurement scales systematically neglecting the social and relational dimension of these constructs. Researchers extracted nearly 9,000 definitions and 2,700 scale items, identifying three core dimensions: regulation/control of learning, intrinsic motivation, and sociocultural action. The findings suggest that generative AI tools in education are being designed around a narrow slice of what agency and autonomy actually mean, potentially stunting the full range of learner development.
A preprint submitted to arXiv in June 2026 presents a large-scale semantic analysis of how 'learner agency' and 'autonomy' are conceptualized and measured across more than 14,000 educational research publications. Drawing on 8,954 definitions and 2,700 scale items, the authors used a computational semantic pipeline to map the definitional landscape of these two constructs, finding they resolve into three dimensions: regulation and control of learning tasks, intrinsic motivation and internal decision-making, and sociocultural or relational action. The study empirically quantifies what the authors call the 'jingle-jangle' fallacy — the widespread problem of different researchers using the same terms to mean different things, or different terms to mean the same thing. A key finding is that existing measurement scales disproportionately capture the first two dimensions while systematically underrepresenting the sociocultural one. Critically, the paper finds that current generative AI applications in education concentrate almost exclusively on learning regulation and control, effectively narrowing the behavioral and developmental repertoire that AI-mediated environments are built to support. The authors argue this has direct implications for how researchers conceptualize, measure, and design interventions around learner agency and autonomy going forward.
What's missing
As a preprint, this work has not yet undergone formal peer review, and the validity of the semantic analysis pipeline — including its ability to reliably distinguish between the three proposed dimensions — has not been independently evaluated. The study's scope is limited to published definitions and scale items and may not capture how practitioners in classrooms or AI development teams actually operationalize these concepts.
What different sources said
- arXiv cs.AICenter
Large-scale semantic mapping of learner agency and autonomy reveals what measurement and generative AI research overlook
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