Monday, June 22
11:55 AM-12:15 PM
EDT
Salon B

Automated Content Analysis of Students’ Cognitive Presence In Asynchronous Online Discussion

Brief Paper: Other ID: 46129
  1. aaa
    Ye Chen
    Syracuse University

Abstract: This study investigated the use of text mining techniques in qualitatively analyzing online students’ cognitive presence in their discussion. Multinomial Naïve Bayes and Support Vector Machines were adopted as the text classification algorithms to automate content analysis of students’ discussion transcription. The results demonstrated the potential of text mining in exploring students’ online discourse and learning process. To develop the optimal classification model, the effectiveness of the two algorithms were compared, different classifiers were examined, and the use of different lexical/vectorization features were also discussed.

No presider for this session.

Topics

Conference attendees are able to comment on papers, view the full text and slides, and attend live presentations. If you are an attendee, please login to get full access.
x