¿El contenido que compartes en los foros eLearning podría revelar qué tipo de estudiante eres?
Trending topics on forums or social networks are now being analysed to know our preferences and needs. This line of thought can be applied to the educational context. In this study we want to analyze what information on the profile of students can be inferred by analyzing their performance in educat...
| Autores: | , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Universidad de La Laguna (ULL) |
| Repositorio: | RIULL. Repositorio Institucional de la Universidad de La Laguna |
| OAI Identifier: | oai:riull.ull.es:915/40155 |
| Acesso em linha: | http://riull.ull.es/xmlui/handle/915/40155 |
| Access Level: | acceso abierto |
| Palavra-chave: | applied computing learning management systems e-learning Learning Analytics social interaction learnings forums |
| Resumo: | Trending topics on forums or social networks are now being analysed to know our preferences and needs. This line of thought can be applied to the educational context. In this study we want to analyze what information on the profile of students can be inferred by analyzing their performance in educational forums and if it is possible to classify them by applying a taxonomy with a quantitative and qualitative perspective of their social interaction. To achieve this, our methodology will be divided into two stages. The first stage consists of preprocessing, classifying and analyzing the messages of the educational forum. In the second stage, the analysis of the messages in the forums is combined with a taxonomy of five different student profiles. These profiles were built according to two types of interactions (social interaction and interaction with content) with the online platform from a quantitative perspective. However, this article proposes to analyze the social interactions of the five proposed profiles from a qualitative perspective. Our results validate the application of the Extended Taxonomy when qualitative and quantitative approaches are applied. |
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