  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.
