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  • 标题:Assessing the Language of Chat for Teamwork Dialogue
  • 本地全文:下载
  • 作者:Antonette Shibani ; Elizabeth Koh ; Vivian Lai
  • 期刊名称:Educational Technology and Society
  • 印刷版ISSN:1176-3647
  • 电子版ISSN:1436-4522
  • 出版年度:2017
  • 卷号:20
  • 期号:2
  • 页码:224-237
  • 出版社:IFETS - Attn Kinshuck
  • 摘要:In technology enhanced language learning, many pedagogical activities involve students in online discussion such as synchronous chat, in order to help them practice their language skills. Besides developing the language competency of students, it is also crucial to nurture their teamwork competencies for today’s global and complex environment. Language communication is an important glue of teamwork. In order to assess the language of chat for teamwork dimensions, several text mining methods are possible. However, difficulties arise such as pre-processing being a black box and classification approaches and algorithms being dependent on the context. To address these issues, the study will evaluate and explain pre-processing and classification methods used to analyze teamwork dialogue from a dataset of chat data. Analytics methods evaluated in this study provide a direction for assessing the language of chat for teamwork dialogue and can help extend the work of technology enhanced language learning to not only focus on academic competency, but on the communication aspect too.
  • 关键词:Teamwork; Pre-processing; Supervised machine learning; Text mining; Learning analytics
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