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arXiv 2610.31335: What the submission does not show: Complexifying cognitive offloading in students' mathematical work with LLMs

Source: Metraipolis archive
Original: https://arxiv.org/abs/2610.31335
License (as archived): CC-BY-4.0
Archived: 2026-10-25T04:22:04.521Z
SHA-256 of the archived text: 85ef095daddad293f99a6f4a69703ea6a2068960fc327505bec546626db66f1f
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How to cite

arXiv 2610.31335: What the submission does not show: Complexifying cognitive offloading in students' mathematical work with LLMs — Metraipolis archive, https://arxiv.org/abs/2610.31335 (CC-BY-4.0); archived copy: https://metraipolis.com/documento/dc_bf8a54289ffa (Metraipolis archive dc_bf8a54289ffa, sha256 85ef095daddad293f99a6f4a69703ea6a2068960fc327505bec546626db66f1f)

BibTeX

@misc{dcbf8a54289ffa,
  title = {arXiv 2610.31335: What the submission does not show: Complexifying cognitive offloading in students' mathematical work with LLMs},
  howpublished = {Metraipolis archive},
  url = {https://arxiv.org/abs/2610.31335},
  note = {License CC-BY-4.0; archived copy https://metraipolis.com/documento/dc_bf8a54289ffa; sha256 85ef095daddad293f99a6f4a69703ea6a2068960fc327505bec546626db66f1f},
  year = {2026}
}

Archived text

Reproduced under CC-BY-4.0. Attribution: Metraipolis archive, https://arxiv.org/abs/2610.31335. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

A common concern is that using large language models (LLMs) lets students offload mathematical work that tasks are designed to elicit. Yet such claims often rest on outcomes (e.g., submitted solutions), rather than on evidence of students' work with LLMs. We followed 23 first-year linear algebra students as they solved three differently designed homework tasks with LLMs. Drawing on self-regulated learning and choice-affluent environments, we interpreted each of 429 prompts as a trace of a regulatory event and compared 59 chatlogs with the problem solutions the students submitted. Prompts formed five structures, casting the LLM mainly as a solver, explainer, or validator. The mix of structures shifted across the tasks, and ten of the 15 students who completed all three tasks changed their dominant structure. Most final submissions stayed close to LLM output, including those that followed exchanges in which students had explained, conjectured, and checked their own ideas. We conclude that an LLM-aided submission is not a trustworthy marker of students' offloading of the mathematical work, and that offloading needs to be examined in each regulatory space and part by part rather than as a whole.

Articolo: «What the submission does not show: Complexifying cognitive offloading in students' mathematical work with LLMs» — Kontorovich, Igor'; Wallach, Miriam N. (2026-10-22), arXiv:2610.31335, categoria cs.CY (informatica e società).
Fonte: https://arxiv.org/abs/2610.31335
Licenza dell'articolo indicata su arXiv: CC-BY-4.0 — https://creativecommons.org/licenses/by/4.0. Qui solo titolo, autori e abstract (non modificato), con attribuzione; il testo integrale resta su arXiv.
Consultato il 2026-10-25T04:21:59Z dalla pagina pubblica dell'articolo (robots.txt rispettato). Depositato dalla Gilda dei Bibliotecari. Abstract in lingua originale.