Learning analytics for the study of self -regulated learning strategies in a context of hybrid learning

Today higher education institutions are investing their efforts to offer students learning scenarios on a scale, both virtually and semi-resident or blended (blunded learning in English, mix the face-to-face with the virtual). However, the implementation of these scenarios on scale has given as a result that the vast majority of students have problems to successfully overcome courses. Recent research suggests that there are 2 reasons why students have difficulty overcoming courses. On the one hand, students experience difficulties in planning, executing and monitoring their learning process autonomously; That is to say; They do not know their learning process as self -regular. On the other hand, current technological platforms through which the courses are offered do not offer the necessary technological support to help students improve the efficient use of learning self -regulation strategies (SRL - Self -Regulated Learning in English), which allows them to make the most of the courses and overcome them. The general objective of this research project is to explore how learning analytics can be used for the study of self -regulated learning strategies that students use in a context of hybrid learning (virtual and presiding). To achieve this, using mixed methodologies for data analysis and design -based Research for the adaptation of a tool, it will be sought to define methods, techniques, methodologies and software tools of the (the - Learning Analytics in English) that allow studying the self -regulation strategies that students use in hybrid scenarios. As results, beyond the definition of methods, techniques, methodologies and tools, it is expected to provide empirical data on SRL strategies used by students: (1) inside and outside a virtual course; And (2) in a Bl scheneario supported by a tool of the. Additionally, the results This project will create new alliances with European and Latin American research groups, and through the LALA Learning Analytical Network, visibility is expected to give visibility to the scientific and technological contributions of the Department of Computer Sciences of the University of Cuenca. In addition, locally, the results of this project are expected to install capacities for the production of digital educational materials and exploit them in virtual and hybrid learning scenarios on scale at the University of Cuenca and other interested institutions.

XVIII UNIVERSITY COMPETITION FOR RESEARCH PROJECTS