Model to personalize the teaching-learning process in virtual environments using case-based reasoning

Benjamin Maraza-Quispe, Olga Alejandro-Oviedo, Betsy Cisneros-Chavez, Maryluz Cuentas-Toledo, Luis Cuadros-Paz, Walter Fernandez-Gambarini, Lita Quispe-Flores, Nicolas Caytuiro-Silva

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

Abstract

In recent years, new research has appeared in the area of education, which has focused on the use of information technology and the Internet to promote online learning, breaking many barriers of traditional education such as space, time, quantity and coverage. However, we have found that these new proposals present problems such as linear access to content, patronized teaching structures, and non-flexible methods in the style of user learning. Therefore, we have proposed the use of an intelligent model of personalized learning management in a virtual simulation environment based on instances of learning objects, using a similarity function through the weighted multidimensional Euclidean distance. The results obtained by the proposed model show an efficiency of 99.5%; which is superior to other models such as Simple Logistic with 98.99% efficiency, Naive Bayes with 97.98% efficiency, Tree J48 with 96.98% efficiency, and Neural Networks with 94.97% efficiency. For which we have designed and implemented the experimental platform MIGAP (Intelligent Model of Personalized Learning Management), which focuses on the assembly of mastery courses in Newtonian Mechanics. Additionally, the application of this model in other areas of knowledge will allow better identification of the best learning style of each student; with the objective of providing resources, activities and educational services that are flexible to the learning style of each student, improving the quality of current educational services.

Original languageEnglish
Title of host publicationProceedings of the 2019 11th International Conference on Education Technology and Computers, ICETC 2019
PublisherAssociation for Computing Machinery
Pages105-110
Number of pages6
ISBN (Electronic)9781450372541
DOIs
StatePublished - 28 Oct 2019
Event11th International Conference on Education Technology and Computers, ICETC 2019 - Amsterdam, Netherlands
Duration: 28 Oct 201931 Oct 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Education Technology and Computers, ICETC 2019
Country/TerritoryNetherlands
CityAmsterdam
Period28/10/1931/10/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

  • Artificial intelligence
  • Case-based reasoning
  • Learning management
  • Learning styles

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