Towards a Learning Analytics Model in Higher Education Applied to a LMS in Virtual Education Based on Motivation Indicators for Permanence

In recent years, the impact of Learning Analytics applied to higher education through HEIs has been identified in order to understand the academic performance of students, based on the interaction that students have in an LMS, using descriptive analytics, for example. However, there are few works that have focused on the integration of information from various sources, in addition to considering motivation as a fundamental part of student permanence in an academic course implemented in an LMS. This paper presents a proposed model of learning analytics in higher education applied to an LMS in virtual education based on motivation indicators for permanence. A review is presented of the way in which motivation has been measured in previous works and the model for carrying out said measurement in the future is proposed, by extracting the data generated through the use of an LMS. An analysis of the traditional measurement of motivation is presented, where two specific instruments are implemented such as AMS (Academic Motivation Scale) and IMI (Intrinsic Motivation Inventory), suggested by the reviewed literature, in addition to identifying the indicators that will be considered in the measurement proposal. The data of the Instituto Tecnológlco Superior de Perote is taken as a case study. It is a first version of the proposal and work is still being done on its development and implementation. As results, a first analysis of the data is presented applying unsupervised machine learning techniques used for predictive analytics.