Emil Eidin, Tom Bielik, Israel Touitou, Jonathan Bowers, Cynthia McIntyre, Dan Damelin, Joeseph Krajcik
{"title":"Thinking in Terms of Change over Time: Opportunities and Challenges of Using System Dynamics Models.","authors":"Emil Eidin, Tom Bielik, Israel Touitou, Jonathan Bowers, Cynthia McIntyre, Dan Damelin, Joeseph Krajcik","doi":"10.1007/s10956-023-10047-y","DOIUrl":null,"url":null,"abstract":"<p><p>Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that should be integrated across educational science disciplines. However, studies show that engaging students in ST is challenging, especially concerning aspects like change over time and feedback. Using computational system models and a system dynamics approach can support students in overcoming these challenges when making sense of complex phenomena. In this paper, we describe an empirical study that examines how 10th grade students engage in aspects of ST through computational system modeling as part of a Next Generation Science Standards-aligned project-based learning unit on chemical kinetics. We show students' increased capacity to explain the underlying mechanism of the phenomenon in terms of change over time that goes beyond linear causal relationships. However, student models and their accompanying explanations were limited in scope as students did not address feedback mechanisms as part of their modeling and explanations. In addition, we describe specific challenges students encountered when evaluating and revising models. In particular, we show epistemological barriers to fruitful use of real-world data for model revision. Our findings provide insights into the opportunities of a system dynamics approach and the challenges that remain in supporting students to make sense of complex phenomena and nonlinear mechanisms.</p>","PeriodicalId":50057,"journal":{"name":"Journal of Science Education and Technology","volume":" ","pages":"1-28"},"PeriodicalIF":3.3000,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260385/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science Education and Technology","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1007/s10956-023-10047-y","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 1
Abstract
Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that should be integrated across educational science disciplines. However, studies show that engaging students in ST is challenging, especially concerning aspects like change over time and feedback. Using computational system models and a system dynamics approach can support students in overcoming these challenges when making sense of complex phenomena. In this paper, we describe an empirical study that examines how 10th grade students engage in aspects of ST through computational system modeling as part of a Next Generation Science Standards-aligned project-based learning unit on chemical kinetics. We show students' increased capacity to explain the underlying mechanism of the phenomenon in terms of change over time that goes beyond linear causal relationships. However, student models and their accompanying explanations were limited in scope as students did not address feedback mechanisms as part of their modeling and explanations. In addition, we describe specific challenges students encountered when evaluating and revising models. In particular, we show epistemological barriers to fruitful use of real-world data for model revision. Our findings provide insights into the opportunities of a system dynamics approach and the challenges that remain in supporting students to make sense of complex phenomena and nonlinear mechanisms.
期刊介绍:
Journal of Science Education and Technology is an interdisciplinary forum for the publication of original peer-reviewed, contributed and invited research articles of the highest quality that address the intersection of science education and technology with implications for improving and enhancing science education at all levels across the world. Topics covered can be categorized as disciplinary (biology, chemistry, physics, as well as some applications of computer science and engineering, including the processes of learning, teaching and teacher development), technological (hardware, software, deigned and situated environments involving applications characterized as with, through and in), and organizational (legislation, administration, implementation and teacher enhancement). Insofar as technology plays an ever-increasing role in our understanding and development of science disciplines, in the social relationships among people, information and institutions, the journal includes it as a component of science education. The journal provides a stimulating and informative variety of research papers that expand and deepen our theoretical understanding while providing practice and policy based implications in the anticipation that such high-quality work shared among a broad coalition of individuals and groups will facilitate future efforts.