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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of 2021 13th International Conference on Education Technology and Computers, ICETC 2021
PublisherAssociation for Computing Machinery
Pages77-84
Number of pages8
ISBN (Electronic)9781450385114
DOIs
StatePublished - 22 Oct 2021
Event13th International Conference on Education Technology and Computers, ICETC 2021 - Virtual, Online, China
Duration: 22 Oct 202125 Oct 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference13th International Conference on Education Technology and Computers, ICETC 2021
Country/TerritoryChina
CityVirtual, Online
Period22/10/2125/10/21

Bibliographical note

Publisher Copyright:
© 2021 ACM.

Keywords

  • Dashboard
  • EVE
  • learning
  • LMS
  • personalized
  • teaching

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