The effect of using different computational system modeling approaches on applying systems thinking

Abstract

This paper discusses the potential of two computational modeling approaches in moving students from simple linear causal reasoning to applying more complex aspects of systems thinking (ST) in explanations of scientific phenomena. While linear causal reasoning can help students understand some natural phenomena, it may not be sufficient for understanding more complex issues such as global warming and pandemics, which involve feedback, cyclic patterns, and equilibrium. In contrast, ST has shown promise as an approach for making sense of complex problems. To facilitate ST, computational modeling tools have been developed, but it is not clear to what extent different approaches promote specific aspects of ST and whether scaffolding such thinking should start with supporting students first in linear causal reasoning before moving to more complex causal dimensions. This study compares two computational modeling approaches, static equilibrium and system dynamics modeling, and their potential to engage students in applying ST aspects in their explanations of the evaporative cooling phenomenon. To make such a comparison we analyzed 10th grade chemistry students’ explanations of the phenomenon as they constructed and used both modeling approaches. The findings suggest that using a system dynamics approach prompts more complex reasoning aligning with ST aspects. However, some students remain resistant to the application of ST and continue to favor linear causal explanations with both modeling approaches. This study provides evidence for the potential of using system dynamics models in applying ST. In addition, the results raise questions about whether linear causal reasoning may serve as a scaffold for engaging students in more sophisticated types of reasoning.

Leveraging Systems Thinking, Engagement, and Digital Competencies to Enhance First-Year Architecture Students’ Achievement in Design-Based Learning

“…Even though prior research has shown that the perceived usefulness of ICT positively affects all types of student engagement, we provide evidence that only the targeted use of ICT (problem solving and creative work) enhances higher-order thinking and students' cognitive-motivational strength when engaged in design tasks, which confirms the findings of Avsec [75]. It seems that advance organizers, because they build information modeling, 3D modeling, and various simulations used in the course along with functional analysis diagrams and flowcharts, might enhance meaningful learning when students are cognitively and behaviorally engaged at higher levels, which is consistent with the findings of Eidin et al [72] and Green at al. [23].…”

“…Systems thinking has a long tradition in computing education and greatly relates to computational thinking [72]. Thus, it is expected that systems thinking may affect engagement in learning using ICT [73] and ICT self-concept might moderate the relationship between systems thinking and design course achievement [74].…”