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

Fei Qin, Xiaobo Liu, Yaowen Zhang, Xuming Li, Fei Wang +3 more
6/9/2026
cs.AI

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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.

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Cite this paper

@article{qin2026largescale,
  title  = {Large-scale semantic mapping of learner agency and autonomy reveals what measurement and generative AI research overlook},
  author = {Fei Qin and Xiaobo Liu and Yaowen Zhang and Xuming Li and Fei Wang and Mutlu Cukurova and Jingjing Chen and Yu Zhang},
  year   = {2026},
  eprint = {2606.10881},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2606.10881v1}
}

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