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1. 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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2. Utilizing a computational thinking engagement inventory to support inclusive computational thinking pathways

   https://doi.org/10.1080/15391523.2024.2398520  

   Coenraad, Merijke; Rangel, Alessandra; Dunbar, Kyle (September 2024, Journal of Research on Technology in Education)

   Based in a research-practice partnership around district-wide computational thinking (CT) Pathways, this paper explores how six districts utilized the CT Engagement Inventory to examine if and how students are engaged in computing learning opportunities and write inclusive CT pathway goals. We found the CT Engagement Inventory supported districts in articulating inclusive pathway goals that moved beyond focusing only on access and participation. Instead, goals focused on building capacity to make broader access and participation possible and examining the nature of student participation. This paper demonstrates a tool to support districts in ensuring inclusive computing learning opportunities reach all students. 

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3. Computational Thinking and Literacy

   https://doi.org/10.26716/jcsi.2018.01.1.1  

   Jacob, Sharin Rawhiya; Warschauer, Mark (January 2018, Journal of Computer Science Integration)
4. 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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5. Computational Thinking Frameworks used in Computational Thinking Assessment in Higher Education. A Systematized Literature Review.

   https://doi.org/10.18260/1-2--36824  

   Cruz Castro, Laura; Shoaib, Huma; Douglas, Kerrie (January 2021, ASEE Annual Conference)

   null (Ed.)

   This research paper presents a literature review of Computational Thinking (CT) frameworks and assessment practices. CT is a 21st century way of solving a problem. It refers specifically to the methods that are effective when trying to solve a problem with a machine or other computational tools. In the past few years, CT researchers and educationists' significant movement started to look for a formal definition and composition of CT in K-12 and higher education. From this effort, over 20 different definitions and frameworks for CT have emerged. Although the availability of literature on CT has been increasing over the last decade, there is limited research synthesis available on how to assess CT better. Besides, it is known that in higher education designing assessments for CT is challenging and one of the primary reasons is that the precise meaning of CT is still unknown. This research paper, therefore, presents a systematized literature review on CT frameworks and assessment practice. We search three different databases and review 19 journal articles that address the assessment of CT in higher education to answer the following two research questions: 1) What does the literature inform us about practices and types of assessments used to evaluate CT in higher education? 2) Which frameworks of CT are present in literature to support CT assessment in higher education? The critical components of this review focus on frameworks and assessment practices based on CT. We develop a synthesis of suggestions and explanations to answer the proposed questions based on literature from recent research in CT. Based on our initial synthesis, we found a disconnect between theory and practice. Specifically, neither the ideas within CT frameworks nor those from CT assessment research are being utilized by the other. Therefore, there is a dire need to connect the two for practical implementation and further research in CT in higher education. 

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