Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries

Incorporating technology into virtual education encourages educational institutions to demand a migration from the current learning management system towards an intelligent virtual educational system, seeking greater benefit by exploiting the data generated by students in their day-to-day activities...

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Main Authors: Vidal Alonso-Secades, Alfonso-José López-Rivero, Manuel Martín-Merino-Acera, Manuel-José Ruiz-García, Olga Arranz-García
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Electronics
Subjects:
Online Access:https://www.mdpi.com/2079-9292/11/9/1487
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author Vidal Alonso-Secades
Alfonso-José López-Rivero
Manuel Martín-Merino-Acera
Manuel-José Ruiz-García
Olga Arranz-García
author_facet Vidal Alonso-Secades
Alfonso-José López-Rivero
Manuel Martín-Merino-Acera
Manuel-José Ruiz-García
Olga Arranz-García
author_sort Vidal Alonso-Secades
collection DOAJ
description Incorporating technology into virtual education encourages educational institutions to demand a migration from the current learning management system towards an intelligent virtual educational system, seeking greater benefit by exploiting the data generated by students in their day-to-day activities. Therefore, the design of these intelligent systems must be performed from a new perspective, which will take advantage of the new analytical functions provided by technologies such as artificial intelligence, big data, educational data mining techniques, and web analytics. This paper focuses on primary education in developing countries, showing the design of an intelligent virtual educational system to improve the efficiency of primary education through recommendations based on reliable data. The intelligent system is formed of four subsystems: data warehousing, analytical data processing, monitoring process and recommender system for educational agents. To illustrate this, the paper contains two dashboards that analyze, respectively, the digital resources usage time and an aggregate profile of teachers’ digital skills, in order to infer new activities that improve efficiency. These intelligent virtual educational systems focus the teaching–learning process on new forms of interaction on an educational future oriented to personalized teaching for the students, and new evaluation and teaching processes for each professor.
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spelling doaj.art-8427bc5f4fa241428e78c15fa920b3452023-11-23T08:04:17ZengMDPI AGElectronics2079-92922022-05-01119148710.3390/electronics11091487Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing CountriesVidal Alonso-Secades0Alfonso-José López-Rivero1Manuel Martín-Merino-Acera2Manuel-José Ruiz-García3Olga Arranz-García4Computer Science Faculty, Pontifical University of Salamanca, C/Compañia, 5, 37002 Salamanca, SpainComputer Science Faculty, Pontifical University of Salamanca, C/Compañia, 5, 37002 Salamanca, SpainComputer Science Faculty, Pontifical University of Salamanca, C/Compañia, 5, 37002 Salamanca, SpainProFuturo Foundation, C/Gran Vía 28, 28013 Madrid, SpainEducation Faculty, Pontifical University of Salamanca, C/Compañia, 5, 37002 Salamanca, SpainIncorporating technology into virtual education encourages educational institutions to demand a migration from the current learning management system towards an intelligent virtual educational system, seeking greater benefit by exploiting the data generated by students in their day-to-day activities. Therefore, the design of these intelligent systems must be performed from a new perspective, which will take advantage of the new analytical functions provided by technologies such as artificial intelligence, big data, educational data mining techniques, and web analytics. This paper focuses on primary education in developing countries, showing the design of an intelligent virtual educational system to improve the efficiency of primary education through recommendations based on reliable data. The intelligent system is formed of four subsystems: data warehousing, analytical data processing, monitoring process and recommender system for educational agents. To illustrate this, the paper contains two dashboards that analyze, respectively, the digital resources usage time and an aggregate profile of teachers’ digital skills, in order to infer new activities that improve efficiency. These intelligent virtual educational systems focus the teaching–learning process on new forms of interaction on an educational future oriented to personalized teaching for the students, and new evaluation and teaching processes for each professor.https://www.mdpi.com/2079-9292/11/9/1487intelligent systemsvirtual educationeducational data miningdata cleaningmachine learninglearning analytics
spellingShingle Vidal Alonso-Secades
Alfonso-José López-Rivero
Manuel Martín-Merino-Acera
Manuel-José Ruiz-García
Olga Arranz-García
Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
Electronics
intelligent systems
virtual education
educational data mining
data cleaning
machine learning
learning analytics
title Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
title_full Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
title_fullStr Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
title_full_unstemmed Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
title_short Designing an Intelligent Virtual Educational System to Improve the Efficiency of Primary Education in Developing Countries
title_sort designing an intelligent virtual educational system to improve the efficiency of primary education in developing countries
topic intelligent systems
virtual education
educational data mining
data cleaning
machine learning
learning analytics
url https://www.mdpi.com/2079-9292/11/9/1487
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