More Like this

1. Determinants of Systems Thinking in College Engineering Students: Research Initiation

   Stirgus, E ; Nagahi, M ; Ma, J ; Jaradat, R ; Strawderman, L ; Eakin, D ( June 2019 , Determinants of Systems Thinking in College Engineering Students: Research Initiation)

   As the world becomes increasingly complicated, systems thinking continues to gain recognition as an important and necessary skill for future engineers. Systems thinking does not replace traditional technical skills required of engineers; rather, it provides a complementary skillset to help better navigate complex systems and their corresponding problems. The increasing complexity of U.S. industries demands that universities train and educate future engineers with systems-thinking skills to solve the range of interconnected problems companies may face. Many factors have the potentials to impact systems-thinking skills. This paper aims to identify the effects of potential impacting factors on the systems-thinking skillset. Current college engineering students were the target population of the study. Structural Equation Modeling was performed to quantify the relationship between systems-thinking skills and potential impacting factors. The results of this study indicated that employment status would affect the overall systems-thinking skills of the engineering students and the engineering students with outside job experience will score higher than students without outside job experience in the systems-thinking skills. 

   more » « less
2. Promoting Computational Thinking through Project-Based Learning

   https://doi.org/doi.org/10.1186/s43031-021-00033-y  

   Shin, N. ; Bowers, J. ; Krajcik, J. ; Damelin, D. ( August 2021 , Disciplinary and Interdisciplinary Science Education Research)

   null (Ed.)

   This paper introduces project-based learning (PBL) features for developing technological, curricular, and pedagogical supports to engage students in computational thinking (CT) through modeling. CT is recognized as the collection of approaches that involve people in computational problem solving. CT supports students in deconstructing and reformulating a phenomenon such that it can be resolved using an information-processing agent (human or machine) to reach a scientifically appropriate explanation of a phenomenon. PBL allows students to learn by doing, to apply ideas, figure out how phenomena occur and solve challenging, compelling and complex problems. In doing so, students take part in authentic science practices similar to those of professionals in science or engineering, such as computational thinking. This paper includes 1) CT and its associated aspects, 2) The foundation of PBL, 3) PBL design features to support CT through modeling, and 4) a curriculum example and associated student models to illustrate how particular design features can be used for developing high school physical science materials, such as an evaporative cooling unit to promote the teaching and learning of CT. 

   more » « less
3. Promoting computational thinking through project-based learning

   https://doi.org/10.1186/s43031-021-00033-y  

   Shin, Namsoo ; Bowers, Jonathan ; Krajcik, Joseph ; Damelin, Daniel ( August 2021 , Disciplinary and Interdisciplinary Science Education Research)

   This paper introduces project-based learning (PBL) features for developing technological, curricular, and pedagogical supports to engage students in computational thinking (CT) through modeling. CT is recognized as the collection of approaches that  involve people in computational problem solving. CT supports students in deconstructing and reformulating a phenomenon such that it can be resolved using an information-processing agent (human or machine) to reach a scientifically appropriate explanation of a phenomenon. PBL allows students to learn by doing, to apply ideas, figure out how phenomena occur and solve challenging, compelling and complex problems. In doing so, students  take part in authentic science practices similar to those of professionals in science or engineering, such as computational thinking. This paper includes 1) CT and its associated aspects, 2) The foundation of PBL, 3) PBL design features to support CT through modeling, and 4) a curriculum example and associated student models to illustrate how particular design features can be used for developing high school physical science materials, such as an evaporative cooling unit to promote the teaching and learning of CT.

    

   more » « less
4. The effect of using different computational system modeling approaches on applying systems thinking

   https://doi.org/10.3389/feduc.2023.1173792  

   Eidin, Emil ; Bowers, Jonathan ; Damelin, Dan ; Krajcik, Joe ( June 2023 , Frontiers in Education)

   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. 

   more » « less
5. Characterizing Advantages and Challenges for Students Engaging in Computational Thinking and Systems Thinking Through Model Construction

   https://doi.org/10.22318/icls2020.183  

   Eidin, E. ; Bielik, T. ; Touitou, I. ; Bowers, J. ; McIntyre, C. ; Damelin, D. ( June 2020 , The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020)

   Gresalfi, M. ; Horn, I. S. (Ed.)

   As human society advances, new scientific challenges are constantly emerging. The use of systems thinking (ST) and computational thinking (CT) can help elucidate these problems and bring us closer to a possible solution. The construction and use of models is one of the most widely used tools when trying to understand systems. In this paper, we examine four case studies of student pairs who were engaged in building and using system models in an NGSS-aligned project-based learning unit on chemical kinetics. Using a theoretical framework that describes how CT and ST practices are manifested in the modeling process we examine the progression of students’ models during their model revisions and explore strategies they employ to overcome modeling challenges they face. We discuss some suggestions to scaffold students’ progression in constructing computational system models and prepare teachers to support their students in engaging in CT and ST practices. 

   more » « less