A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities

Authors

  • Higinio Mora University of Alicante
  • Antonio Ferrández University of Alicante
  • David Gil University of Alicante
  • Jesús Peral University of Alicante

DOI:

https://doi.org/10.19173/irrodl.v18i1.2637

Keywords:

natural language processing, topic detection, distance learning, online forum, mooc managing, e-learning, applications for open and distance learning

Abstract

Massive Open Online Courses and e-learning represent the future of the teaching-learning processes through the development of Information and Communication Technologies. They are the response to the new education needs of society. However, this future also presents many challenges such as the processing of online forums when a huge number of messages are generated. These forums provide an excellent platform for learning and connecting students of the subject, but the difficulties in following and searching the vast volume of information that they generate may produce the opposite effect. In this paper, we propose a computational method for enabling the educational process in huge online learning communities. This method analyses the forum information through Natural Language Processing techniques and extract the main topics discussed. The results generated improves the management of the forums, increases the effectiveness of the teachers’ explanations and reduces the time spent by students to follow the course. The proposal has been complemented with a real case study that shows promising results.

Author Biographies

Higinio Mora, University of Alicante

Department of Computer Technology

Antonio Ferrández, University of Alicante

Dept. Language and Information Systems

David Gil, University of Alicante

Department of Computer Technology

Jesús Peral, University of Alicante

Dept. Language and Information Systems

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Published

2017-02-28

How to Cite

Mora, H., Ferrández, A., Gil, D., & Peral, J. (2017). A Computational Method for Enabling Teaching-Learning Process in Huge Online Courses and Communities. The International Review of Research in Open and Distributed Learning, 18(1). https://doi.org/10.19173/irrodl.v18i1.2637

Issue

Vol. 18 No. 1 (2017): Special Issue: Advances in Research on Social Networking in Open and Distributed Learning

Section

Research Articles

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