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1. Thinking about Thinking as Rational Computation

   Berke, Marlene; Tenenbaum, Abigail; Sterling, Benjamin; Jara-Ettinger, Julian (July 2023, Proceedings of the Annual Conference of the Cognitive Science Society)
2. Developing the systems thinking and computational thinking identification tool

   Bowers, J.; Shin, N.; Brennan, L.; Eidin, E. E.; Stephens, L.; Roderick, S. (January 2022, Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022)

   Chinn, C.; Tan, E.; Chan, C.; Kali, Y. (Ed.)

   We developed the Systems Thinking (ST) and Computational Thinking (CT) Identification Tool (ID Tool) to identify student involvement in ST and CT as they construct and revise computational models. Our ID Tool builds off the ST and CT Through Modeling Framework, emphasizing the synergistic relationship between ST and CT and demonstrating how both can be supported through computational modeling. This paper describes the process of designing and validating the ID Tool with special emphasis on the observable indicators of testing and debugging computational models. We collected 75 hours of students’ interactions with a computational modeling tool and analyzed them using the ID Tool to characterize students’ use of ST and CT when involved in modeling. The results suggest that the ID Tool has the potential to allow researchers and practitioners to identify student involvement in various aspects of ST and CT as they construct and revise computational models. 

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3. Systems Thinking Assessments: Approaches That Examine Engagement in Systems Thinking

   Dugan. K. E., Mosyjowski (January 2021, Proceedings of the 2021 American Society for Engineering Education Annual Conference & Exposition)

   null (Ed.)

   While systems engineers rely on systems thinking skills in their work, given the increasing complexity of modern engineering problems, engineers across disciplines need to be able to engage in systems thinking, including what we term comprehensive systems thinking. Due to the inherent complexity of systems thinking, and more specifically comprehensive systems thinking, it is not easy to know how well students (and practitioners) are learning and leveraging systems thinking approaches. Thus, engineering managers and educators can benefit from systems thinking assessments. A variety of systems thinking assessments exist that are relevant to engineers, including some focused on the demonstration of systems thinking knowledge or skills and others measuring attitudes, interests, or values related to systems thinking. Starting with a collection of systems thinking assessments from a systematic literature review conducted by our team, we analyzed in-depth those behavior-based assessments that included the creation of a visual representation and were open-ended, i.e., it did not presuppose or provide answers. The findings from this in-depth analysis of systems thinking behavior-based assessments identified 1) six visualization types that were leveraged, 2) dimensions of systems thinking that were assessed and 3) tensions between the affordances of different assessments. In addition, we consider the ways assessments can be used. For example, using assessments to provide feedback to students or using assessments to determine which students are meeting defined learning goals. We draw on our findings to highlight opportunities for future comprehensive systems thinking behavior-based assessment development. 

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4. Demystifying computational thinking

   https://doi.org/10.1016/j_edurev.2017.09.003  

   Shute, V. J.; Sun, C.; Asbell-Clarke, J. (January 2017, Educational research review)

   This paper examines the growing field of computational thinking (CT) in education. A review of the relevant literature shows a diversity in definitions, interventions, assessments, and models. After synthesizing various approaches used to develop the construct in K-16 settings, we have created the following working definition of CT: The conceptual foundation required to solve problems effectively and efficiently (i.e., algorithmically, with or without the assistance of computers) with solutions that are reusable in different contexts. This definition highlights that CT is primarily a way of thinking and acting, which can be exhibited through the use particular skills, which then can become the basis for performance-based assessments of CT skills. Based on the literature, we categorized CT into six main facets: decomposition, abstraction, algorithm design, debugging, iteration, and generalization. This paper shows examples of CT definitions, interventions, assessments, and models across a variety of disciplines, with a call for more extensive research in this area. 

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5. Measuring systems thinking.

   Gray, S. (January 2018, Nature sustainability)