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Application of Learning Analytics to Improve Higher Education
Author(s) -
Carlos Llopis-Albert,
Francisco Rubio
Publication year - 2021
Publication title -
multidisciplinary journal for education, social and technological sciences
Language(s) - English
Resource type - Journals
ISSN - 2341-2593
DOI - 10.4995/muse.2021.16287
Subject(s) - bachelor , typology , learning analytics , analytics , subject (documents) , quality (philosophy) , mathematics education , big data , computer science , knowledge management , data science , psychology , sociology , world wide web , political science , philosophy , epistemology , anthropology , law , operating system
In the digital era, the teacher assumes very diverse roles among which are to be an adviser, a generator of multimedia content, and more recently a data analyst. Big data analytics may play a major role in Higher Education for all the agents involved, the teachers and educators, the students themselves and the managers or heads of university centers. This paper applies learning analytics to the subject of Theory of Machines and Strength of Materials of the bachelor's degree in Chemical Engineering at Universitat Politècnica de València (Spain). The aim of analyzing the available information is to improve teachers’ actions and communication, to enhance resource efficiency, to assess classroom procedures, the achievement of transversal competences, the student typology and their results, or the attitudes and commitment they acquire with the subject taught. Results show the existence of niches with competitive advantages, improvements in the quality and performance of the teaching-learning experience.

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