Large-scale semantic mapping of learner agency and autonomy reveals what measurement and generative AI research overlook

2026-06-09

AI Summary

This study addresses the persistent conceptual confusion in learner agency and autonomy research—marked by jingle-jangle fallacies (i.e., “same name, different constructs” and “different names, same construct”) and a neglect of sociocultural dimensions. Drawing on a corpus of over 14,000 publications, the authors extracted 8,954 definitions and 2,700 scale items, leveraging large-scale text mining, semantic analysis, and construct mapping to empirically quantify this terminological ambiguity for the first time. They propose a unified framework integrating task-, individual-, and sociocultural-level dimensions. Findings reveal that existing measurement instruments substantially underrepresent sociocultural factors, while generative AI research in education disproportionately emphasizes learning regulation. The study provides a theoretically grounded and empirically informed foundation for multidimensional agency assessment and the design of AI-enhanced educational environments.

Abstract

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.

Problem

• learner agency
• autonomy
• jingle-jangle fallacy
• semantic mapping
• sociocultural dimension

Innovation

• semantic mapping
• learner agency
• autonomy
• jingle-jangle fallacy
• generative AI in education