Evaluation of a Learning Analytics Application for Open edX Platform

José A. Ruipérez-Valiente1,2, Pedro J. Muñoz-Merino1, Héctor J. Pijeira Díaz1, Javier Santofimia Ruiz1 and Carlos Delgado Kloos1

  1. Universidad Carlos III de Madrid
    Avenida Universidad 30, 28911 Leganés (Madrid) Spain
    {jruipere@it, pedmume@it, 100075697@alumnos, 100060449@alumnos, cdk@it}.uc3m.es
  2. IMDEA Networks Institute
    Av. del Mar Mediterráneo 22, 28918 Leganés (Madrid) Spain


Massive open online courses (MOOCs) have recently emerged as a revolution in education. Due to the huge amount of users, it is difficult for teachers to provide personalized instruction. Learning analytics computer applications have emerged as a solution. At present, MOOC platforms provide low support for learning analytics visualizations, and a challenge is to provide useful and effective visualization applications about the learning process. At this paper we review the learning analytics functionality of Open edX and make an overview of our learning analytics application ANALYSE. We present a usability and effectiveness evaluation of ANALYSE tool with 40 students taking a Design of Telematics Applications course. The survey obtained very positive results in a system usability scale (SUS) questionnaire (78.44/100) in terms of the usefulness of visualizations (3.68/5) and the effectiveness ratio (92/100) of the actions required for the respondents. Therefore, we can conclude that the implemented learning analytics application is usable and effective.

Key words

learning analytics, human machine system, open edx, MOOCs, information visualization

Digital Object Identifier (DOI)


Publication information

Volume 14, Issue 1 (January 2017)
Year of Publication: 2017
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Ruipérez-Valiente, J. A., Muñoz-Merino, P. J., Díaz, H. J. P., Ruiz, J. S., Kloos, C. D.: Evaluation of a Learning Analytics Application for Open edX Platform. Computer Science and Information Systems, Vol. 14, No. 1, 51–73. (2017), https://doi.org/10.2298/CSIS160331043R