Utilizing open-source programming environments and student clustering to foster K-12 STEAM learning outcomes. Modelling processes via simulation scenarios.

This study investigates the impact of open-source programming environments and student clustering on K-12 STEAM learning outcomes. The research addresses the gap in understanding how knowledge acquisition is influenced by collaborative expert groups and digital instructional tools. A quasi-experimental design is implemented, assessing student performance through formative assessments and statistical analysis. Results indicate that clustering students into expert groups significantly enhances declarative, conceptual, procedural, and evaluative knowledge. The study also explores the effectiveness of modeling processes via simulation scenarios. Findings suggest that optimized student grouping and technology-enhanced learning contribute to improved learning efficiency. The implications note the importance of innovative instructional strategies in STEAM education.