Abstract:

Currently one of the trends that has shown great interest in society is related to Big Data or Data Mining, in such a way that organizations of different nature or disciplinary field have been interested in knowing its functioning by the utility it generates in identifying problems and offering the best alternatives and solutions (Mosquera, 2018; Peñaloza, 2017; Romero and Rojas, 2014).

The Horizon Report (2019) and Tsai and Gasevic (2017), point out that within the main guidelines for the field of higher education is for institutions to take advantage of the mass data set generated by students and their contexts, derived from a Big Data known as the Learning Analytics defined as: "the measurement, collection, analysis and reporting of data on students" (Ifenthaler, 2017; Bollenback, 2015); which serves to improve the learning processes of students as well as for management and quality in higher education (Whitelock-Wainwright, Gasevic, and Tejeiro, 2019; Siemens and Baker, 2012; Ellis, 2011).

Learning analytics includes the application of big data to the training and development of student education data obtained by universities for use as support services, such as determining whether a student is below the average level of performance in the course, or whether he or she is at risk of failing or dropping out of the professional career (Avolio, Benzaquen and Pretel 2019; Ifenthaler and Schumacher, 2016). The learning analytics service provides timely information so that the institution can contact the learner and identify any problems before they jeopardize their academic learning.

The importance of collecting and understanding students' expectations of learning analytics is of vital importance to the success of the service (Sabulski, 2019; Ifenthaler 2017) this research aims to contribute to addressing the field of learning analytics and their benefit in the learning processes of students and in applying a questionnaire to master’s students a public University in Mexico in order to know what students expect from the services of learning analytics.

The objectives of this paper are to provide critical information on the expectations of ethics and privacy as well as the characteristics of the learning analytics service for students and to test the hypothesis: Do men or women perceive the learning analytics service differently in the educational institution? For the analysis of the data, the descriptive part of them will be shown; as well as the application of parametric tests with the estimation of the Student t test for independent samples (Canavos, 1986) and the Levene test for equal variances and means; with a level of significance (alpha) 5% =0.05, for the verification of the main hypothesis of the study.

The findings will help higher education institutions and even other levels of education, take as a reference and see which aspects should be included in the design and implementation of the Learning Analytics policy in their educational institution. As well as universities may know that it is more important for students whether the expectations of ethics and privacy or those related to the features of the learning analytics service.

Keywords:

Learning Analytics, Educational Technology, Educational Data Mining, University Students.