Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Learning Analytics and Interactions in Virtual Learning Environments. A Comparative Study of Typologies and their Relationship with Academic Performance
Year:2012
Research Areas
  • Humanities
Information
Abstract
Analysis of learning data (learning analytics) is a new research field with high growth potential. The main objective of Learning analytics is the analysis of data (interactions being the basic data unit) generated in virtual learning environments, in order to maximize the outcomes of the learning process; however, a consensus has not been reached yet on which interactions must be measured and what is their influence on learning outcomes. This research is grounded on the study of e-learning interaction typologies and their relationship with students? academic performance, by means of a comparative study between different interaction typologies (based on the agents involved, frequency of use and participation mode). The main conclusions are a) that classifications based on agents offer a better explanation of academic performance; and b) that each of the three typologies are able to explain academic performance in terms of some of their components (student-teacher and student-student interactions, evaluating students interactions and active interactions, respectively), with the other components being nonrelevant.
International
Si
Congress
XIV Simposio Internacional de Informática Educativa
960
Place
Andorra La Vella (Andorra)
Reviewers
Si
ISBN/ISSN
978-84-939814-6-4
Start Date
29/10/2012
End Date
31/10/2012
From page
203
To page
208
XIV Simposio Internacional de Informática Educativa
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
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
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