Architectural Design for the Implementation of Learning Analytics: Case Study at Salesian Polytechnic University

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3 Scopus citations

Abstract

Learning analytics consist of measuring, capturing, and analyzing student data. Currently, the use of learning analytics in Universities constitutes a world trend that helps to make better academic decisions in the Salesian Polytechnic University with the purpose of decrease the dropout rates of the career. The institution developed tutoring processes in which help is provided to students in the teaching-learning process. The problem is that attendance at these tutorials is optional. There is a proliferation of concern about whether the students who most need it the most are the ones who attend these tutorials. Consequently, the University tries to identify the students that are most likely to drop out of their careers before it happens and offer them the help they need through these tutorials. Today, student’s data are growing and are indifferent and scattered databases. This article proposes an architectural design for the implementation of learning analytics that seeks to strengthen students to achieve their personal and academic goals. The evaluation of the architecture was based on the LWPM operator and shows a high evaluation, according to the experts, highlighting the maintainability and reliability of this architecture.

Original languageEnglish
Title of host publicationAdvances in Human Factors in Training, Education, and Learning Sciences - Proceedings of the AHFE 2021
EditorsSalman Nazir, Tareq Z. Ahram, Waldemar Karwowski
PublisherSpringer Science and Business Media Deutschland GmbH
Pages260-268
Number of pages9
ISBN (Print)9783030799991
DOIs
StatePublished - 2021
EventAHFE Conference on Human Factors in Training, Education, and Learning Sciences, 2021 - Virtual, Online
Duration: 25 Jul 202129 Jul 2021

Publication series

NameLecture Notes in Networks and Systems
Volume269

Conference

ConferenceAHFE Conference on Human Factors in Training, Education, and Learning Sciences, 2021
CityVirtual, Online
Period25/07/2129/07/21

Bibliographical note

Funding Information:
This work has been supported by the GIIAR research group and of the Academic Vice-Rector?s Office in the Universidad Polit?cnica Salesiana.

Funding Information:
Acknowledgments. This work has been supported by the GIIAR research group and of the Academic Vice-Rector’s Office in the Universidad Politécnica Salesiana.

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Education data
  • Efficient data processing
  • Learning analytics infrastructure
  • LWPM

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