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.
Systems thinking and modeling are two critical 21st-century skills that teachers and educators are expected to impart to students, and students are expected to acquire and master them as part of their preparation to become literate citizens of a society and environment that is becoming ever more complex. Systems thinking is a thought process in which assumptions about interactions among interconnected elements of a system or a phenomenon can help predict the system’s behavior, outcomes, and in the case of human-made artifacts, the value to its beneficiaries. Conceptual modeling involves the simultaneous visual and textual representation of one’s ideas about a phenomenon or system in science or engineering. The qualitative study described here aimed to examine the effect of an online interdisciplinary asynchronous course on the development of systems thinking and conceptual modeling skills among pre- and in-service science and engineering teachers. Engaging in a qualitative case study with an exploratory orientation, we investigated how science and engineering teachers and teacher educators coped with (a) online learning of conceptual modeling and systems thinking using Object-Process Methodology in a food and sustainability context, and (b) developing an online assignment for teaching those skills to their students and assessing them. Research tools included the online assignment that the participants developed, a dedicated rubric for analyzing their assignments, accounting for use of modeling and systems concepts and the integration of sustainability and COVID-19 issues, a variety of thinking skills, visualizations and disciplines, and a mix of closed- and open-ended questions. Additionally, the participants’ reflections were analyzed to characterize their sense of self-efficacy and academic progression. We characterize five teacher-developed assignment cases along with the related teachers’ reflections, which exposed the benefits they had gained from the online course, as well as the systems thinking and modeling challenges they had faced. Analysis of the effect of the course with emphasis on the final task reveals that this approach is effective for developing the systems thinking and modeling skills of the teachers and serves as a catalyst for their professional development. The study offers a methodological contribution by providing a basis for evaluating teachers’ assessment knowledge and skills using a six attributes rubric.