Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

Title:Do LLM Tutors Actually Teach? A Process-Centered Synthesis of the Tutoring Loop

Abstract:Large language models can produce fluent tu- toring dialogue, but whether they actually help students learn remains unclear. We present a process-centered synthesis of LLM tutoring that follows the path from learner-state infer- ence to pedagogical action, tutor training, eval- uation, and student simulation. This view ex- poses a central gap: implementing a tutoring component does not establish that it works or that its outputs meaningfully affect later stages. A structured study-level audit shows that peda- gogical evaluation is common, while evidence becomes much thinner for learner-conditioned intervention, human learning gains, and espe- cially transfer or delayed retention. Human studies nevertheless provide a conditional posi- tive result: LLM tutors can improve learning, but benefits depend on pedagogical structure, learner engagement, and how learning is mea- sured. We argue that progress requires validat- ing the interfaces between tutoring stages, not only improving individual components.

Computation and Language (cs.CL)

arXiv:2610.15692 [cs.CL]

(or arXiv:2610.15692v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.15692 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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