Evaluation of AI-generated Passages for Reading Practice: An application of causal forests

Walter L. Leite; Qian Shen; Wonchae Lee; Sierra Evans; Sienna Perez; Wei Li; Jinnie Shin

Evaluation of AI-generated Passages for Reading Practice: An application of causal forests

Walter L Leite, Qian Shen, Wonchae Lee, Sierra Evans, Sienna Perez, Wei Li, Jinnie Shin

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Abstract

This study presents a causal approach for evalu- ating automated generation of reading passages for early readers. It consists of estimating the average treatment effect of a candidate model, then conditional average treatment effects with causal forests. We apply it to evaluate a fine- tuned model for a digital literacy platform

Anthology ID:: 2026.aimecon-main.27
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:: 245–252
Language:
URL:: https://aclanthology.org/2026.aimecon-main.27/
DOI:
Bibkey:
Cite (ACL):: Walter L Leite, Qian Shen, Wonchae Lee, Sierra Evans, Sienna Perez, Wei Li, and Jinnie Shin. 2026. Evaluation of AI-generated Passages for Reading Practice: An application of causal forests. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 245–252, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).
Cite (Informal):: Evaluation of AI-generated Passages for Reading Practice: An application of causal forests (Leite et al., AIME-Con 2026)
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PDF:: https://aclanthology.org/2026.aimecon-main.27.pdf

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@inproceedings{leite-etal-2026-evaluation,
    title = "Evaluation of {AI}-generated Passages for Reading Practice: An application of causal forests",
    author = "Leite, Walter L  and
      Shen, Qian  and
      Lee, Wonchae  and
      Evans, Sierra  and
      Perez, Sienna  and
      Li, Wei  and
      Shin, Jinnie",
    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.27/",
    pages = "245--252",
    ISBN = "979-8-9983004-0-0",
    abstract = "This study presents a causal approach for evalu- ating automated generation of reading passages for early readers. It consists of estimating the average treatment effect of a candidate model, then conditional average treatment effects with causal forests. We apply it to evaluate a fine- tuned model for a digital literacy platform"
}

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%0 Conference Proceedings
%T Evaluation of AI-generated Passages for Reading Practice: An application of causal forests
%A Leite, Walter L.
%A Shen, Qian
%A Lee, Wonchae
%A Evans, Sierra
%A Perez, Sienna
%A Li, Wei
%A Shin, Jinnie
%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 leite-etal-2026-evaluation
%X This study presents a causal approach for evalu- ating automated generation of reading passages for early readers. It consists of estimating the average treatment effect of a candidate model, then conditional average treatment effects with causal forests. We apply it to evaluate a fine- tuned model for a digital literacy platform
%U https://aclanthology.org/2026.aimecon-main.27/
%P 245-252

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Markdown (Informal)

[Evaluation of AI-generated Passages for Reading Practice: An application of causal forests](https://aclanthology.org/2026.aimecon-main.27/) (Leite et al., AIME-Con 2026)

Evaluation of AI-generated Passages for Reading Practice: An application of causal forests (Leite et al., AIME-Con 2026)

ACL

Walter L Leite, Qian Shen, Wonchae Lee, Sierra Evans, Sienna Perez, Wei Li, and Jinnie Shin. 2026. Evaluation of AI-generated Passages for Reading Practice: An application of causal forests. In Proceedings of the Artificial Intelligence in Measurement and Education Conference (AIME-Con): Full Papers, pages 245–252, Wyndham Grand Pittsburgh Downtown, Pittsburgh, Pennsylvania, United States. National Council on Measurement in Education (NCME).