Educational Sciences: Theory & Practice

ISSN: 2630-5984

Topic Interaction Model Based on Local Community Detection in MOOC Discussion Forums and its Teaching

Gengxin Sun
School of Data Science and Software Engineering, Qingdao University, Qingdao 266071, China.
Sheng Bin
School of Data Science and Software Engineering, Qingdao University, Qingdao 266071, China.

Abstract

Discussion forums is a major component of MOOC platform. The teaching interaction in MOOC learning process mainly occurs in discussion forums by topic. Aiming at the problem of students’ ability difference in the course of MOOC teaching, in this paper a topic interaction model based on local community detection is proposed. Through topic modeling for students’ interaction ability in discussion forums, local community detection algorithm is used to classify students’ various abilities reasonably. Through tracking and analyzing student behavior information on a highly interactive MOOC platform, the accuracy rate of the proposed model is obviously higher than that of the traditional assessment methods. The teaching practice using the model shows that students’ abilities in all aspects are improved by means of pertinence classroom communication and training.

Keywords
Topic Interaction, MOOCs, Topic Model, Community Detection.