Teamwork Dimensions Classification Using BERT
December 09, 2023 ยท Declared Dead ยท ๐ International Conference on Artificial Intelligence in Education
"No code URL or promise found in abstract"
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Authors
Junyoung Lee, Elizabeth Koh
arXiv ID
2312.05483
Category
cs.CL: Computation & Language
Citations
2
Venue
International Conference on Artificial Intelligence in Education
Last Checked
5 months ago
Abstract
Teamwork is a necessary competency for students that is often inadequately assessed. Towards providing a formative assessment of student teamwork, an automated natural language processing approach was developed to identify teamwork dimensions of students' online team chat. Developments in the field of natural language processing and artificial intelligence have resulted in advanced deep transfer learning approaches namely the Bidirectional Encoder Representations from Transformers (BERT) model that allow for more in-depth understanding of the context of the text. While traditional machine learning algorithms were used in the previous work for the automatic classification of chat messages into the different teamwork dimensions, our findings have shown that classifiers based on the pre-trained language model BERT provides improved classification performance, as well as much potential for generalizability in the language use of varying team chat contexts and team member demographics. This model will contribute towards an enhanced learning analytics tool for teamwork assessment and feedback.
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