| Texto completo | |
| Autor(es): |
Falvo, Venilton, Jr.
;
Marcolino, Anderson da Silva
;
Bruno, Diego Renan
;
Martins Falvo, Catherine Helen
;
Osorio, Fernando Santos
;
Barbosa, Ellen Francine
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2024 IEEE FRONTIERS IN EDUCATION CONFERENCE, FIE; v. N/A, p. 9-pg., 2024-01-01. |
| Resumo | |
This full research paper expands on the results and discussions from a case study conducted within a Brazilian EdTech company. It focuses on the accuracy of AI-based speech recognition models for automatic transcription of video lectures, aiming to improve the accessibility of Learning Objects (LOs), especially the audible ones. Previous work assessed the quality of automatic transcriptions in English, Portuguese, and Spanish from Speech-To-Text (STT) services provided by major market players (Amazon, Google, IBM, Microsoft, and OpenAI), using a quantitative approach based on lexical similarity algorithms. Statistically significant differences were identified between the providers and languages evaluated, indicating that STT service can affect the quality of audible OAs enriched with transcriptions or subtitles. This study introduces a new dimension of analysis by incorporating the perceptions of technology students on the accuracy of automatic transcriptions, gathered through an anonymous survey with 56 participants. The survey captured mainly quantitative data using a Likert scale on the accuracy of transcriptions. To provide a comprehensive analysis, this study employs a data triangulation approach, integrating (1) quantitative data from lexical similarity methods, (2) quantitative data from the survey, and (3) findings from a complementary review of the literature. The qualitative analysis, applying Grounded Theory principles to both the survey data and the bibliographic review, enables the exploration of emerging themes and enriches the understanding of factors influencing the quality of automatic transcriptions. This effort underscores the importance of a user-centered perspective and demonstrates the complexity of evaluating STT technologies, pointing to the necessity for future research that combines quantitative and qualitative methods. Additionally, it highlights the relevance of STT in various educational contexts and the need to align such technologies with principles of accessibility and inclusion. By aiming to create more accessible LOs, this work emphasizes the need to develop solutions that ensure inclusion and equity in educational access, reflecting a concerted effort to meet the diverse needs of learners and promote a more welcoming and inclusive learning environment. (AU) | |
| Processo FAPESP: | 18/26636-2 - Engenharia de Software e Tecnologias Educacionais: Estabelecendo Mecanismos de Apoio ao Ensino e Aprendizagem |
| Beneficiário: | Ellen Francine Barbosa |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |