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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Lourdes Quevedo-Sánchez
Universidad César Vallejo

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Functionality of the learning platform and its effect on the satisfaction of students in the online teaching environment Omar Chamorro-Atalaya; Guillermo Morales-Romero; César León-Velarde; Lourdes Quevedo-Sánchez; Yurfa Medina-Bedón; Abel Tasayco-Jala; Maritte Fierro-Bravo
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1073-1081

Abstract

The objective of this article is to identify the results of the functionality of the learning platform and its effect on the satisfaction of mechanical and electrical engineering students, the results will serve as a basis for the continuous improvement of teaching-learning online from the higher institution. The research findings indicate that the indicators that present a better perception regarding the functionality of the learning platform are related to the design and ease of navigation. However, 21.4% of the students are not entirely satisfied with its functionality due to the technical problems presented when downloading the study material. According to the results, we can point out that the functionality of the learning platform generates an effect of 70.87% on student satisfaction, the relationship was validated through the Chi-square test, in which it is determined that the indicators that generate a Greater satisfaction in students refers to the design, availability (connectivity) and the ease of communication and interaction with the teacher and classmates.
Vector support machine algorithm applied to the improvement of satisfaction levels in the acquisition of professional skills Omar Chamorro-Atalaya; Orlando Ortega-Galicio; Guillermo Morales-Romero; Darío Villar-Valenzuela; Yeferzon Meza-Chaupis; César León-Velarde; Lourdes Quevedo-Sánchez
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp597-604

Abstract

The study carried out identifies the metricss of the predictive model obtained through the support vector machine (VSM) algorithm, which will be applied in the satisfaction of the acquisition of professional skills of the students of the Professional Engineering Career. As part of the development, the statistical classification tool is used, during the development of the research, it was identified that the predictive model presents as general metrics an accuracy of 82.1%, a precision of 70.72%, a sensitivity of 91.06% and a specificity of 87.60%. Through this model, it contributes significantly to decision-making in relation to improving satisfaction related to the acquisition of professional skills in engineering students, since decision-making by university authorities will have a scientific basis, to take early and timely actions in relation to the predictive elements.
Co-Authors Abel Tasayco-Jala César León-Velarde Darío Villar-Valenzuela Guillermo Morales-Romero Maritte Fierro-Bravo Omar Chamorro-Atalaya Orlando Ortega-Galicio Yeferzon Meza-Chaupis Yurfa Medina-Bedón