Large-scale semantic mapping of learner agency and autonomy reveals what measurement and generative AI research overlook
For researchers and practitioners in education and AI, this work clarifies conceptual confusion and highlights gaps in measurement and AI-mediated learning design.
The study extracted 8,954 definitions and 2,700 scale items from over 14,000 publications to map the semantic landscape of learner agency and autonomy, revealing three dimensions (task, person, sociocultural) and quantifying the jingle-jangle fallacy. It found that existing scales underrepresent the sociocultural dimension and that generative AI research focuses narrowly on learning regulation and control.
Learner agency and autonomy are foundational to personal development, yet a pervasive "jingle-jangle" fallacy (i.e. identical terms denoting different constructs, distinct terms denoting identical ones) has substantially hindered cumulative knowledge. Treating meaning as a phenomenon constituted through use in linguistic practice, we extracted 8,954 definitions and 2,700 scale items from over 14,000 publications, to investigate how researchers actually used learner agency and autonomy with a semantic analysis pipeline. The definitional landscape of two constructs resolves into three dimensions: regulation and control of learning (task), intrinsic motivation and internal decision-making (person), and social-relational action (sociocultural), thereby empirically quantifying the jingle-jangle fallacy. Existing scales, however, systematically underrepresent the sociocultural dimension. Critically, current generative AI research in education concentrates on learning regulation and control, narrowing the behavioral repertoire that AI-mediated learning environments are designed to cultivate. Beyond conceptual clarification, this work carries direct implications for conceptualization, measurement, and practice towards supporting the multidimensional learner agency and autonomy.