Undergraduate Engineering Students’ Types and Quality of Knowledge Used in Synthetic Modeling

Abstract

Modeling is an important element of discovery and design processes because it can help individuals to comprehend and facilitate solutions to problems, mediate among mental and external representations, and off-load cognitive demands. However, engaging in model generation, comprehension, and transformation requires the orchestration of domain knowledge, meta-representational cknowledge, and various reasoning processes. This study aims to understand the interplay between domain knowledge, meta-representational knowledge, and students’ reasoning processes while engaging in modeling activity. Specifically, our goal is to investigate: (a) the types and quality of knowledge students used when performing modeling activities, and (b) the differences in types of knowledge used by students regarding their performance in a modeling and simulation challenge. Our qualitative analysis focused on verbal descriptions via a retrospective semi-structured interview and artifacts created by seventeen students after engaging in synthetic modeling activity. The resulting analysis reports overall quality for the types of domain and meta-representational knowledge that students used along with reasoning processes during synthetic modeling activity. The analysis also compared and contrasted the patterns of conceptual understanding and problem-solving skills between three groups, which differed in terms of modeling performance.