Authors:
Eva Durall
1
and
Begoña Gros
2
Affiliations:
1
Aalto university, Finland
;
2
University of Barcelona, Spain
Keyword(s):
Learning Analytics, Educational Data Mining, Self-directed Learning, Self-Regulated Learning.
Related
Ontology
Subjects/Areas/Topics:
Computer-Supported Education
;
Higher Order Thinking Skills
;
Information Technologies Supporting Learning
;
Learning Analytics
;
Learning/Teaching Methodologies and Assessment
Abstract:
The use of learning analytics is entering in the field of research in education as a promising way to support learning. However, in many cases data are not transparent for the learner. In this regard, Educational institutions shouldn’t escape the need of making transparent for the learners how their personal data is being tracked and used in order to build inferences, as well as how its use is going to affect in their learning. In this contribution, we sustain that learning analytics offers opportunities to the students to reflect about learning and develop metacognitive skills. Student-centered analytics are highlighted as a useful approach for reframing learning analytics as a tool for supporting self-directed and self-regulated learning. The article also provides insights about the design of learning analytics and examples of experiences that challenge traditional implementations of learning analytics.