Evaluation of the Main Components for Learning with Materials in Educational Platforms
Miguel Ysrrael Ramirez-Sanchez (),
Enoc Gutierrez-Pallares (),
Vilmar Alves Pereira () and
Rodrigo Florencio da Silva ()
International Journal of Education and Practice, 2022, vol. 10, issue 2, 96-106
Abstract:
Distance Education Learning for higher levels depends on multiple factors which entail pedagogical and technical dimensions. This research focused on an assessment study of materials contained in an educational platform, showing results on the factors causing significant intervention in the ways of learning in Virtual Learning Environments. The study contemplates a sampling for the educational platform operating at the Autonomous University of the State of Mexico. It was conducted following a transversal descriptive methodology, assessment of 19 independent study guides, and analyses of 13 fundamental indicators for each of them. For the research design, descriptive and correlational statistical techniques were used to analyze the foundation of the model. T tests were conducted to understand the discrepancy of those factors that should be showing a convergence. Results showed that there were areas of opportunity in terms of contents, learning activities, activity evaluation with feedback and materials content. The main inference found was that, in order to be able to build a distance educational model, the main components for learning should score a minimum of 7 out of the 10 possible points to be able to guarantee quality education materials in educational platforms. The recommendations include the prioritization of not replicating a traditional educational model deposited in virtual form, implying the support of the integration of educational materials with the Virtual Learning Environments.
Keywords: Computer assisted learning; Distance education; Educational model; Educational platforms; Learning; Virtual learning environments. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:pkp:ijoeap:v:10:y:2022:i:2:p:96-106:id:2954
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