Teaching practices analysis through audio signal processing
Resumen:
Remote teaching has been used successfully with the evolution of videoconference solutions and broadband internet availability. Even several years before the global COVID 19 pandemic, Ceibal used this approach for different educational programs in Uruguay. As in face-to-face lessons, teaching evaluation is a relevant task in this context, which requires many time and human resources for classroom observation. In this work we propose automatic tools for the analysis of teaching practices, taking advantage of the lessons recordings provided by the videoconference system. We show that it is possible to detect with a high level of accuracy, relevant lessons metrics for the analysis, such as the teacher talking time or the language usage in English lessons.
| 2023 | |
| Esta investigación fue financiada por la Agencia Nacional de Investigación e Innovación (ANII) Uruguay, Número de subvención FMV_1_2021_1_166660 | |
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Teaching analysis Classroom activity detection Diarization Education Audio signal processing |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/39852 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
