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.
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This work has been supported by the GIIAR research group and of the Academic Vice-Rector’s Office in the Universidad Politécnica Salesiana.
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Castro Arias, S.T., Quiroz Martinez, M.A., Leyva Vazquez, M.Y., Flores Ortiz, A.C. (2021). Architectural Design for the Implementation of Learning Analytics: Case Study at Salesian Polytechnic University. In: Nazir, S., Ahram, T.Z., Karwowski, W. (eds) Advances in Human Factors in Training, Education, and Learning Sciences. AHFE 2021. Lecture Notes in Networks and Systems, vol 269. Springer, Cham. https://doi.org/10.1007/978-3-030-80000-0_31
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DOI: https://doi.org/10.1007/978-3-030-80000-0_31
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