Using Epistemic Network Analysis to Explore STEM Learning Design Competence in Online Collaborative Discourse

Involvement in well-scaffolded collaborative curriculum design contributes to teachers design high-quality STEM learning plans. It remains unclear how we can evaluate STEM learning competence effectively and then stimulate a productive design process. This study utilized 12 STEM learning design activities in an online collaborative learning environment, and collected 9686 utterances of 33 pre-service teachers during the design process. The present study aimed to: (1)uncover links between elements of STEM learning design competence and the differences between high and low-performing pre-service teachers; (2) explore how pre-service teachers' STEM learning design competence changed over time during activities. We aligned Epistemic Network Analysis method to analyze discourse data. The findings revealed that there are significant differences in the networks between high and low-performing groups. By analyzing the discourse that contributed to each of the connections in the network representation, we can see that this difference leads to the quality of their lesson plans. To further explore the competence development trajectory, we modeled the networks of the two groups at different design stages. The findings show that these two groups represent two learning design patterns, similar to traditional learning design and backward learning design.