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Memorias de investigación
Communications at congresses:
Predicting academic performance with learning analytics in virtual learning environments: A comparative study of three interaction classifications
Year:2012
Research Areas
  • Humanities
Information
Abstract
Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.
International
Si
Congress
International Symposium on Computers in Education (SIIE), 2012
960
Place
Andorra La Vella (Andorra)
Reviewers
Si
ISBN/ISSN
978-1-4673-4743-3
Start Date
29/10/2012
End Date
31/10/2012
From page
1
To page
6
International Symposium on Computers in Education
Participants
  • Autor: Angel Francisco Agudo Peregrina (UPM)
  • Autor: Angel Hernandez Garcia (UPM)
  • Autor: Santiago Iglesias Pradas (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Innovación, Propiedad industrial y Política tecnológica (INNOPRO)
  • Centro o Instituto I+D+i: Centro de Domótica Integral, CEDINT
  • Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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