Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning
Year:2014
Research Areas
  • Educational sciences
Information
Abstract
Learning analytics is the analysis of electronic learning data which allows teachers, course designers and administrators of virtual learning environments to search for unobserved patterns and underlying information in learning processes. The main aim of learning analytics is to improve learning outcomes and the overall learning process in electronic learning virtual classrooms and computer-supported education. The most basic unit of learning data in virtual learning environments for learning analytics is the interaction, but there is no consensus yet on which interactions are relevant for effective learning. Drawing upon extant literature, this research defines three system-independent classifications of interactions and evaluates the relation of their components with academic performance across two different learning modalities: virtual learning environment (VLE) supported face-to-face (F2F) and online learning. In order to do so, we performed an empirical study with data from six online and two VLE-supported F2F courses. Data extraction and analysis required the development of an ad hoc tool based on the proposed interaction classification. The main finding from this research is that, for each classification, there is a relation between some type of interactions and academic performance in online courses, whereas this relation is non-significant in the case of VLE-supported F2F courses. Implications for theory and practice are discussed next.
International
Si
JCR
Si
Title
Computers in Human Behavior
ISBN
0747-5632
Impact factor JCR
2,273
Impact info
Datos JCR del año 2013
Volume
31
10.1016/j.chb.2013.05.031
Journal number
From page
542
To page
550
Month
FEBRERO
Ranking
Participants
  • Autor: Angel Francisco Agudo Peregrina (UPM)
  • Autor: Santiago Iglesias Pradas (UPM)
  • Autor: Miguel Ángel Conde-González (Universidad de León)
  • Autor: Angel Hernandez Garcia (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
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)