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Comprehensive learning system based on the analysis of data and the recommendation of activities in a distance education environment

  • Autores: William Eduardo Villegas Chiliquinga Árbol académico, Xavier Palacios Pacheco, Diego Buenaño Fernández, Sergio Luján Mora Árbol académico
  • Localización: The International journal of engineering education, ISSN-e 0949-149X, Vol. 35, no. Extra 5, 2019, págs. 1316-1325
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen

    • Traditional teaching, based on techniques in which students develop a passive function, has proven to be an inefficient method inthe engineering learning process. Universities have been forced to improve their teaching methods and have found a partial solutionin open source platforms; these platforms have allowed a greater collaboration between institutions that improve the contributionof technology to education. There are cases of collaboration between universities where their sole objective is to promote studentlearning and the automation of educational processes. The massification of this type of technological tools allows the use ofsystems and platforms commonly used in the business world. This adoption of open source tools has proven to be very effective ineducational environments and has offered several benefits such as the reduction of costs and the constant updating of informationsystems. One of the frequent cases in which there are collaborative projects based on learning is the analysis of educational datathat seek to detect students’ deficiencies and to take actions before they abandon their studies. In this work, we propose the designof an integral learning system in which business intelligence, expert systems, learning management systems and different learningtechniques converge. This integration seeks to create a system capable of recommending different activities that focus on the needsof students.

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