Research Area:  Machine Learning

Abstract:

This research presents a comprehensive methodological approach to detect and analyze student engagement within the context of online education. It is supported by e-learning systems, and is based on a combination of semantic analysis, applied to the students’ posts and comments, with a machine learning-based classification, performed upon a range of data derived from the students’ usage of the online courses themselves. This is meant to provide teachers and students with information related to the relevant aspects making up the students’ engagement, such as sentiment, urgency, confusion within a given course as well as the probability for students to keep their involvement in or to drop out from the courses altogether.

Keywords:  

Author(s) Name:  Daniele Toti, Nicola Capuano, Fernanda Campos, Mario Dantas, Felipe Neves & Santi Caballé

Publisher name:  Springer

DOI:  10.1007/978-3-030-61105-7_21

Volume Information:  

Paper Link:   https://link.springer.com/chapter/10.1007/978-3-030-61105-7_21