The Reflective Modeling Practitioner: Promoting Self-regulation and Self-confidence in Computational Modeling and Simulation Practices

This study investigated the effects of a team -based modeling intervention that implemented reflective practices to support students' self -regulated learning in the context of modeling assignments. We used a mixed method design to answer the three research questions: (1) What metacognitive strategies do students, organized in teams, implement when solving computational modeling assignments? (2) What are students' levels of performance in solving computational modeling assignments in teams? (3) What are the relationships between teams' level of confidence and their implemented metacognitive strategies and level of performance in the computational modeling assignment? The learning intervention was guided by a reflective modeling practitioner model, bringing together modeling practices with elements of selfregulated learning. The results illustrate students' levels of self -reported confidence in three levels, showing that from the twelve teams studied, seven reported an increase in confidence as the project progressed, three reported a decrease in their confidence, and two reported an initial struggle, but their confidence increased as they completed the assignment. The implications relate to the learning interventions in the team modeling activity that can influence the teams' reported selfconfidence, which can impact the skills students acquire and the strategies they use when faced with challenges.