Publication Type

Journal Article

Publication Date

4-2017

Abstract

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 pos sible. 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 preprocessing 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 n ot only focus on academic competency, but on the communication aspect too.

Keywords

Teamwork, Pre-processing, Supervised machine learning, Text mining, Learning analytics

Discipline

Databases and Information Systems | Data Storage Systems

Research Areas

Data Management and Analytics

Publication

Educational Technology and Society

Volume

20

Issue

2

First Page

224

Last Page

237

ISSN

1176-3647

Publisher

International Forum of Educational Technology and Society / International Forum of Educational Technology & Society

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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