Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers

Michael P. Hemenway; Justin O. Barber; Martha Bellows; Susan Lottridge

Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers

Michael P. Hemenway, Justin O. Barber, Martha Bellows, Susan Lottridge

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Abstract

We present a production system for hierarchical analytic writing feedback that uses frontier LLMs to generate training data for fine-tuned transformer models. Applied to Grade 5 opinion essays, the system scores 5 competency dimensions and 31 binary feedback codes, achieving agreement approaching inter-rater levels from training sets of 300–500 essays.

Anthology ID:: 2026.aimecon-main.58
Volume:: Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
Month:: October
Year:: 2026
Address:: Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
Editors:: Joshua Wilson, Christopher Ormerod, Magdalen Beiting-Parrish
Venue:: AIME-Con
SIG:
Publisher:: National Council on Measurement in Education (NCME)
Note:
Pages:: 516–524
Language:
URL:: https://aclanthology.org/2026.aimecon-main.58/
DOI:
Bibkey:
Cite (ACL):: Michael P. Hemenway, Justin O. Barber, Martha Bellows, and Susan Lottridge. 2026. Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 516–524, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers (Hemenway et al., AIME-Con 2026)
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PDF:: https://aclanthology.org/2026.aimecon-main.58.pdf

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@inproceedings{hemenway-etal-2026-hierarchical,
    title = "Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers",
    author = "Hemenway, Michael P.  and
      Barber, Justin O.  and
      Bellows, Martha  and
      Lottridge, Susan",
    editor = "Wilson, Joshua  and
      Ormerod, Christopher  and
      Beiting-Parrish, Magdalen",
    booktitle = "Proceedings of the Artificial Intelligence in Measurement and Education Conference ({AIME}-Con): Full Papers",
    month = oct,
    year = "2026",
    address = "Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States",
    publisher = "National Council on Measurement in Education (NCME)",
    url = "https://aclanthology.org/2026.aimecon-main.58/",
    pages = "516--524",
    ISBN = "979-8-9983004-0-0",
    abstract = "We present a production system for hierarchical analytic writing feedback that uses frontier LLMs to generate training data for fine-tuned transformer models. Applied to Grade 5 opinion essays, the system scores 5 competency dimensions and 31 binary feedback codes, achieving agreement approaching inter-rater levels from training sets of 300{--}500 essays."
}

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%0 Conference Proceedings
%T Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers
%A Hemenway, Michael P.
%A Barber, Justin O.
%A Bellows, Martha
%A Lottridge, Susan
%Y Wilson, Joshua
%Y Ormerod, Christopher
%Y Beiting-Parrish, Magdalen
%S Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers
%D 2026
%8 October
%I National Council on Measurement in Education (NCME)
%C Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States
%@ 979-8-9983004-0-0
%F hemenway-etal-2026-hierarchical
%X We present a production system for hierarchical analytic writing feedback that uses frontier LLMs to generate training data for fine-tuned transformer models. Applied to Grade 5 opinion essays, the system scores 5 competency dimensions and 31 binary feedback codes, achieving agreement approaching inter-rater levels from training sets of 300–500 essays.
%U https://aclanthology.org/2026.aimecon-main.58/
%P 516-524

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Markdown (Informal)

[Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers](https://aclanthology.org/2026.aimecon-main.58/) (Hemenway et al., AIME-Con 2026)

Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers (Hemenway et al., AIME-Con 2026)

ACL

Michael P. Hemenway, Justin O. Barber, Martha Bellows, and Susan Lottridge. 2026. Hierarchical Analytic Writing Feedback with Fine-Tuned Transformers. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 516–524, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).