A Review of the Analytics Techniques for an Efficient Management of Online Forums: An Architecture Proposal

E-learning is a response to the new educational needs of society and an important development in information and communication technologies because it represents the future of the teaching and learning processes. However, this trend presents many challenges, such as the processing of online forums which generate a huge number of messages with an unordered structure and a great variety of topics. These forums provide an excellent platform for learning and connecting students of a subject but the difficulty of following and searching the vast volume of information that they generate may be counterproductive. The main goal of this paper is to review the approaches and techniques related to online courses in order to present a set of learning analytics techniques and a general architecture that solve the main challenges found in the state of the art by managing them in a more efficient way: 1) efficient tracking and monitoring of forums generated; 2) design of effective search mechanisms for questions and answers in the forums; and 3) extraction of relevant key performance indicators with the objective of carrying out an efficient management of online forums. In our proposal, natural language processing, clustering, information retrieval, question answering, and data mining techniques will be used.This work was supported in part by the Spanish Ministry of Economy and Competitiveness through the Project SEQUOIA-UA under Grant TIN2015-63502-C3-3-R, the Project RESCATA under Grant TIN2015-65100-R, and the Project PROMETEO/2018/089, and in part by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) through the Project CloudDriver4Industry under Grant TIN2017-89266-R