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

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.This paper has been partially supported by the MESOLAP (TIN2010-14860), GEODAS-BI (TIN2012-37493-C03-03), DIIM2.0 (PROMETEOII/2014/001) and RESCATA (TIN2015-65100-R) projects from the Spanish Ministry of Education and Competitiveness