Predictive discursive features for learning outcome in online cooperative learning

ID: 32216 Type: Brief Paper
  1. Eiji Tomida, Ehime University, Japan
  2. Yohei Okibayashi, Yamaguchi University, Japan
  3. Yasuhisa Tamura, Sophia University, Japan

Tuesday, March 8 3:05-3:25 PM Location: Kingsley

No presider for this session.

The purpose of the present study was to discover the discursive characteristics which led to the learning outcome in online cooperative learning. Sixty-one students who took an undergraduate course at a university were the participants of this study. They were divided into small groups and discussed on the BBS of the LMS over the understanding on the theories of Piaget and Vygotsky. Using text data mining techniques, simple counting of used words on the BBS showed that more frequent exemplification of academic concepts would lead to higher test scores. In addition, the analysis using ontologically categorized word frequency showed that more frequent use of abstract words was also related to higher scores. The overall tendency of the results implicates that the phase in which students were mutually asking and answering questions about basic understanding might improve shallow understanding of the learning topics. Meanwhile, thematically free discussion might facilitate deeper understanding.

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