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Research on socio-scientific issues (SSI) has revealed that it is critical for learners to develop a systematic understanding of the underlying issue. In this paper, we explore how modeling can facilitate students’ systems thinking in the context of SSI. Building on evidence from prior research in promoting systems thinking skills through modeling in scientific contexts, we hypothesize that a similar modeling approach could effectively foster students’ systematic understanding of complex societal issues. In particular, we investigate the affordances of socio-scientific models in promoting students’ systems thinking in the context of COVID-19. We examine learners’ experiences and reflections concerning three unique epistemic features of socio-scientific models, (1) knowledge representation, (2) knowledge justification, and (3) systems thinking. The findings of this study demonstrate that, due to the epistemic differences from traditional scientific modeling approach, engaging learners in developing socio-scientific models presents unique opportunities and challenges for SSI teaching and learning. It provides evidence that, socio-scientific models can serve as not only an effective but also an equitable tool for addressing this issue.
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The Lake Urmia vignette: a tool to assess understanding of complexity in socio‐environmental systems
Abstract We introduce the Lake Urmia Vignette (LUV) as a tool to assess individuals' understanding of complexity in socio‐environmental systems. LUV is based on a real‐world case and includes a short vignette describing an environmental catastrophe involving a lake. Over a few decades, significant issues have manifested themselves at the lake because of various social, political, economic, and environmental factors. We design a rubric for assessing responses to a prompt. A pilot test with a sample of 30 engineering graduate students is conducted. We compare responses to LUV with other measures. Our findings suggest that students' understanding of complexity is positively associated with their understanding of systems concepts such as feedback loops but not with other possible variables such as self‐reported systems thinking skills or systems‐related coursework. Based on the provided instructions, researchers can use LUV as a novel assessment tool to examine understanding of complexity in socio‐environmental systems. © 2020 System Dynamics Society
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- Award ID(s):
- 1824594
- PAR ID:
- 10457052
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- System Dynamics Review
- Volume:
- 36
- Issue:
- 2
- ISSN:
- 0883-7066
- Format(s):
- Medium: X Size: p. 191-222
- Size(s):
- p. 191-222
- Sponsoring Org:
- National Science Foundation
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