IMASHEDU: Intelligent MAshups for EDUcation - Towards a Data Mining Approach

Priscila Cedillo, Pablo Martínez León, Marcos Orellana

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Nowadays, technological tools greatly support the work of teaching-learning tasks. In this sense, there are various sources of information from which teachers and students rely on to complement their academic activities. Content is sought on the web, significantly updated and easy to understand, generally in the form of videos. As people progress in their learning, they face terms, concepts, and topics that they are not familiar with them. However, those topics are included in the video. In this context, a complex process is generated of alternating sections of the video with other sources of information that explain the related topics and contribute to the understanding of the topic discussed. In this regard, and considering the possibility of systematically consuming information from various sources, it is necessary to build a method and an application that orchestrates the contents of these sources in a convenient, fast and automatic way, according to the person's learning. This proposal contemplates the development of a Mashup. This mashup integrates different data sources in a single graphical interface. Also, it is considered the construction of a core software solution based on text mining techniques. This solution allows extracting the textual content from videos and identifying the terms that could support the knowledge of the topic. It would significantly contribute to the fact that related topics are presented unified in the same interface. At the same time, the learning experience is greatly improved, avoiding losing the common thread of the observed video. Therefore, this article presents a process of orchestrating various data sources in a Web Mashup application. It includes videos available on YouTube channels, with other sources (e.g., Wikipedia, Pinterest) that help understand the topic better, generating hypertext references based on the generation of terms through text mining techniques. A Mathematics Learning mashup has been built to show the proposal’s feasibility.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 14th International Conference on Computer Supported Education - Volume 1, CSEDU 2022
EditoresMutlu Cukurova, Nikol Rummel, Denis Gillet, Bruce McLaren, James Uhomoibhi
EditorialScience and Technology Publications, Lda
Páginas383-388
Número de páginas6
ISBN (versión digital)9789897585623
DOI
EstadoPublicada - 2022
Evento14th International Conference on Computer Supported Education, CSEDU 2022 - Virtual, Online
Duración: 22 abr. 202224 abr. 2022

Serie de la publicación

NombreInternational Conference on Computer Supported Education, CSEDU - Proceedings
Volumen1
ISSN (versión digital)2184-5026

Conferencia

Conferencia14th International Conference on Computer Supported Education, CSEDU 2022
CiudadVirtual, Online
Período22/04/2224/04/22

Huella

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