@inproceedings{galletti-etal-2026-evaluating,
title = "Evaluating Therapist-in-the-Loop {NLP} in Comprehension Rehabilitation for Children with {SEND}",
author = "Galletti, Martina and
Marchesi, Caterina and
Pasqua, Eleonora",
editor = "Atwell, Katherine and
Borah, Angana and
Dementieva, Daryna and
Kreiss, Elisa and
Kotonya, Neema and
Liu, Jiarui and
Olson, Liz and
Wan, Ruyuan and
Zhao, Jieyu",
booktitle = "Proceedings of the Fifth Workshop on {NLP} for Positive Impact ({NLP}4{PI})",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.nlp4pi-1.16/",
pages = "175--187",
ISBN = "979-8-89176-495-8",
abstract = "Personalized rehabilitation can improve educational and clinical outcomes for children with special educational needs and disabilities (SEND), but creating individualized reading exercises, comprehension questions, lexical supports, and progress reports remains time-consuming for clinicians. We present ARTIS, a therapist-in-the-loop and natural-language-processing (NLP)-assisted platform that supports reading-comprehension rehabilitation while preserving expert oversight, and evaluate its deployment in a real clinical setting. We report a ten-session intervention involving ten children aged 9{--}11 years at a speech and language rehabilitation centre. Across the intervention, platform comprehension accuracy remained relatively stable, while pre/post analyses showed stronger gains in vocabulary knowledge and lexical competence than in standardized reading-comprehension scores. Changes in platform accuracy were positively associated with changes in standardized comprehension outcomes, although these exploratory results should be interpreted cautiously. Overall, the study demonstrates the feasibility of integrating therapist-supervised NLP into a real rehabilitation workflow and highlights its potential to facilitate personalized material preparation while maintaining clinician oversight."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="galletti-etal-2026-evaluating">
<titleInfo>
<title>Evaluating Therapist-in-the-Loop NLP in Comprehension Rehabilitation for Children with SEND</title>
</titleInfo>
<name type="personal">
<namePart type="given">Martina</namePart>
<namePart type="family">Galletti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Caterina</namePart>
<namePart type="family">Marchesi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Eleonora</namePart>
<namePart type="family">Pasqua</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-10</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Fifth Workshop on NLP for Positive Impact (NLP4PI)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Katherine</namePart>
<namePart type="family">Atwell</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Angana</namePart>
<namePart type="family">Borah</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Daryna</namePart>
<namePart type="family">Dementieva</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elisa</namePart>
<namePart type="family">Kreiss</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Neema</namePart>
<namePart type="family">Kotonya</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jiarui</namePart>
<namePart type="family">Liu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Liz</namePart>
<namePart type="family">Olson</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ruyuan</namePart>
<namePart type="family">Wan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jieyu</namePart>
<namePart type="family">Zhao</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Budapest, Hungary</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-495-8</identifier>
</relatedItem>
<abstract>Personalized rehabilitation can improve educational and clinical outcomes for children with special educational needs and disabilities (SEND), but creating individualized reading exercises, comprehension questions, lexical supports, and progress reports remains time-consuming for clinicians. We present ARTIS, a therapist-in-the-loop and natural-language-processing (NLP)-assisted platform that supports reading-comprehension rehabilitation while preserving expert oversight, and evaluate its deployment in a real clinical setting. We report a ten-session intervention involving ten children aged 9–11 years at a speech and language rehabilitation centre. Across the intervention, platform comprehension accuracy remained relatively stable, while pre/post analyses showed stronger gains in vocabulary knowledge and lexical competence than in standardized reading-comprehension scores. Changes in platform accuracy were positively associated with changes in standardized comprehension outcomes, although these exploratory results should be interpreted cautiously. Overall, the study demonstrates the feasibility of integrating therapist-supervised NLP into a real rehabilitation workflow and highlights its potential to facilitate personalized material preparation while maintaining clinician oversight.</abstract>
<identifier type="citekey">galletti-etal-2026-evaluating</identifier>
<location>
<url>https://aclanthology.org/2026.nlp4pi-1.16/</url>
</location>
<part>
<date>2026-10</date>
<extent unit="page">
<start>175</start>
<end>187</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Evaluating Therapist-in-the-Loop NLP in Comprehension Rehabilitation for Children with SEND
%A Galletti, Martina
%A Marchesi, Caterina
%A Pasqua, Eleonora
%Y Atwell, Katherine
%Y Borah, Angana
%Y Dementieva, Daryna
%Y Kreiss, Elisa
%Y Kotonya, Neema
%Y Liu, Jiarui
%Y Olson, Liz
%Y Wan, Ruyuan
%Y Zhao, Jieyu
%S Proceedings of the Fifth Workshop on NLP for Positive Impact (NLP4PI)
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-495-8
%F galletti-etal-2026-evaluating
%X Personalized rehabilitation can improve educational and clinical outcomes for children with special educational needs and disabilities (SEND), but creating individualized reading exercises, comprehension questions, lexical supports, and progress reports remains time-consuming for clinicians. We present ARTIS, a therapist-in-the-loop and natural-language-processing (NLP)-assisted platform that supports reading-comprehension rehabilitation while preserving expert oversight, and evaluate its deployment in a real clinical setting. We report a ten-session intervention involving ten children aged 9–11 years at a speech and language rehabilitation centre. Across the intervention, platform comprehension accuracy remained relatively stable, while pre/post analyses showed stronger gains in vocabulary knowledge and lexical competence than in standardized reading-comprehension scores. Changes in platform accuracy were positively associated with changes in standardized comprehension outcomes, although these exploratory results should be interpreted cautiously. Overall, the study demonstrates the feasibility of integrating therapist-supervised NLP into a real rehabilitation workflow and highlights its potential to facilitate personalized material preparation while maintaining clinician oversight.
%U https://aclanthology.org/2026.nlp4pi-1.16/
%P 175-187
Markdown (Informal)
[Evaluating Therapist-in-the-Loop NLP in Comprehension Rehabilitation for Children with SEND](https://aclanthology.org/2026.nlp4pi-1.16/) (Galletti et al., NLP4PI 2026)
ACL