Using text mining to evaluate student interaction in virtual learning environments

The field of education has been affected by globalization and the constant increase of online courses. The high number of students enrolled in these learning environments and their constant interaction with platforms generate a large amount of data that is difficult to handle with traditional method...

Full description

Saved in:
Bibliographic Details
Published in2018 IEEE World Engineering Education Conference (EDUNINE) pp. 1 - 6
Main Authors Buenano-Fernandez, Diego, Villegas-Ch, W., Lujan-Mora, Sergio
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2018
Subjects
Education
Electronic mail
Massive Open Online Course
MOOC
Opinion mining
Supervised learning
Text mining
Twitter
Online AccessGet full text

Cover

More Information
Summary:The field of education has been affected by globalization and the constant increase of online courses. The high number of students enrolled in these learning environments and their constant interaction with platforms generate a large amount of data that is difficult to handle with traditional methods of data analysis. The permanence of students in these courses poses challenges aimed at raising their level of commitment and motivation. Several articles with this approach have been identified in the literature analyzed in this work. Some of them are related to the application of text mining techniques aimed at analyzing the interaction of students in these environments. This interaction is based on entries included in discussion forums, emails or interaction in social networks. In this article, we explore the interaction of students through text mining techniques in different student interaction environments in a massive open online course (MOOC). The research focuses on the calculation and analysis of the frequency of terms, the analysis of concordances and groupings in n-grams.
DOI:10.1109/EDUNINE.2018.8450969