Modeling STEM learning design competence through discourse analysis

Modeling STEM learning design competence is critical in support of STEM teacher professional development. This study collected 9686 utterances of 33 pre-service STEM teachers from an online STEM learning design environment and modeled STEM learning design competence using epistemic network analysis (ENA) approach. Moreover, this study investigated the relations between collaborative design process and design outcome. We categorized high and low-performing groups based on their STEM lesson plans and then compared their STEM learning competence networks drawn from conversation. The findings revealed that there are significant differences in the networks between high and low-performing groups, which may contribute to the quality of their lesson plans. To further explore the developmental trajectory of STEM learning design competence, we modeled the competence 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.