Design proposal of a personalized Dashboard to optimize teaching-learning in Virtual Learning Environments

Benjamin Maraza Quispe, Jhon Edwar Ninasivincha Apfata, Ricardo Carlos Qusipe Figueroa, Manuel Alejandro Valderrama Solis

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The objective of the research is to develop a methodology to analyze a set of data extracted from a Learning Management System (LMS), in order to implement a Dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of the analysis of 9,257 records extracted through simple random sampling from a population of 100,000 records. The indicators analyzed were: number of accesses, course grades, time spent, number of courses enrolled and number of activities developed. The results show the data analysis in the KNIME data mining analysis platform, the model was implemented in five phases: Requirements definition, model design, development, implementation and evaluation of results. The results are taken as a recommendation to design and implement a customized Dashboard for teachers to identify observable behavioral patterns that allow them to make decisions to improve the teaching-learning processes of students.

Idioma originalInglés
Título de la publicación alojadaProceedings of 2021 13th International Conference on Education Technology and Computers, ICETC 2021
EditorialAssociation for Computing Machinery
Páginas77-84
Número de páginas8
ISBN (versión digital)9781450385114
DOI
EstadoPublicada - 22 oct. 2021
Evento13th International Conference on Education Technology and Computers, ICETC 2021 - Virtual, Online, China
Duración: 22 oct. 202125 oct. 2021

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia13th International Conference on Education Technology and Computers, ICETC 2021
País/TerritorioChina
CiudadVirtual, Online
Período22/10/2125/10/21

Nota bibliográfica

Publisher Copyright:
© 2021 ACM.

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