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Developing an AI-Based Application for Linguistic Analysis of Deaf Learners' L2 Writing (Short Paper)

Authors Aryane Santos Nogueira , Ana Célia Ribeiro Bizigato Portes

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Document Identifiers

Subject Classification

ACM Subject Classification
  • Applied computing → Education
  • Computing methodologies → Natural language processing
Keywords
  • Deaf education
  • Second language writing
  • Linguistic analysis
  • Generative AI
  • Natural Language Processing

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Abstract

The teaching of written language as a second language (L2) to deaf students remains a critical challenge in bilingual education. This is also the case for written Portuguese in Brazil, where difficulties persist particularly in the analysis of students' written production and its use in pedagogical decision-making. This paper presents the ongoing development of a Minimum Viable Product (MVP) aimed at supporting the qualified linguistic analysis of texts produced by deaf learners. Rather than functioning as a correction tool, the system is conceived as a pedagogically oriented analytical assistant, designed to identify patterns related to formal aspects of writing and their functional-communicative impact. The proposed model is structured around three analytical subdimensions (FORM_PROD, FORM_IMP, and FORM_FUN) and implemented through a prompt-based architecture using a Large Language Model (LLM). Preliminary results from a pilot study with five learner texts suggest the feasibility of distinguishing between formal instability and communicative effectiveness, generating interpretable and pedagogically relevant outputs. These findings point to the potential of AI to support language teaching in bilingual contexts involving deaf learners.

Cite As Get BibTex

Aryane Santos Nogueira and Ana Célia Ribeiro Bizigato Portes. Developing an AI-Based Application for Linguistic Analysis of Deaf Learners' L2 Writing (Short Paper). In 15th Symposium on Languages, Applications and Technologies (SLATE 2026). Open Access Series in Informatics (OASIcs), Volume 144, pp. 11:1-11:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.SLATE.2026.11

Author Details

Aryane Santos Nogueira
  • UNICAMP, Campinas-SP, Brasil
Ana Célia Ribeiro Bizigato Portes
  • UNICAMP, Campinas-SP, Brasil
  • FATEC, Mogi Mirim-SP, Brasil

Funding

São Paulo Research Foundation - FAPESP n.2022/05908-0 Teaching, Research and Extension Support Fund - FAEPEX/UNICAMP n. 3348/24.

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