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

Autor: Higinio Mora, Antonio Ferrández, David Gil, Jesús Peral
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: International Review of Research in Open and Distributed Learning, Vol 18, Iss 1 (2017)
Druh dokumentu: article
ISSN: 1492-3831
DOI: 10.19173/irrodl.v18i1.2637
Popis: 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.
Databáze: Directory of Open Access Journals