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1. A Principled Approach to Designing Assessments That Integrate Science and Computational Thinking

   https://doi.org/10.22318/cscl2018.384  

   Basu, S.; McElhaney, K. W.; Grover, S.; Harris, C. J.; Biswas, G. (July 2018, 13th International Conference of the Learning Sciences (ICLS))

   There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks as part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts. 

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2. Teacher Practices for Formatively Assessing Computational Thinking with Early Elementary Learners

   https://doi.org/10.3390/educsci14111250  

   Sherwood, Heather; Culp, Katherine McMillan; Ferguson, Camille; Kaiser, Alice; Henry, Meagan; Negron, Anthony (November 2024, Education Sciences)

   Few studies of computational thinking (CT) integration in elementary curricula have yet focused on supporting early elementary educators with implementing and assessing their young students’ application of these practices to content area work. This paper summarizes a collaborative research project that engaged researchers, K-second grade teachers, and professional development (PD) providers in implementing a hybrid PD model to answer the following research questions: (1) What kind of PD and guidance do teachers need to identify and support emergent computational thinking development in young students’ language and work process? (2) What kind of PD and guidance do teachers need to identify emergent computational thinking development in young students’ work products? This project employed a mixed-methods research design that included pre- and post-surveys and interviews with teachers to measure and understand how growth in teachers’ confidence, knowledge, and self-efficacy with CT prepared them to identify and support these concepts with young learners. Additionally, analysis was able to identify the key formative assessment strategies these teachers employed to generate insight into students’ understanding and application of CT during problem-solving. 

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3. Developing an Introductory Computer Science Course for Pre-service Teachers

   Adler, Rachel F; Beck, Kristan (January 2020, Journal of technology and teacher education)

   Computational thinking (CT) involves breaking a problem into smaller components and solving it using algorithmic thinking and abstraction. CT is no longer exclusively for computer scientists but for everyone. While CT does not necessarily require programming, learning programming to enhance CT skills at a young age can help shape the next generation of children with knowledge that can help them succeed in our technological world. In order to produce teachers who are able to incorporate programming and CT into their future classrooms, we created an introductory Computer Science course (CS0) targeting future K-8 STEM teachers yet open to any student to enroll and learn computer science. We used a mixed-methods approach, examining both quantitative and qualitative data based on self-reported surveys, classroom artifacts, and focus groups from four semesters of data. We found that after taking the course, students’ self-efficacy in CT increased and while education students initially had lower confidence in their computing abilities than computer science students in the course, by the end of the semester there were no differences in their perceived and actual coding abilities when compared with computer science students. Furthermore, education students had many ideas on how to incorporate similar projects into their own future classrooms. 

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4. Studying Interdisciplinary Thinking about Complex Real-World Data at DataFest

   Higgins, Traci; Karch, Jessica M.; Hammerman, James K.L. (July 2023, IASE 2023 Satellite Conference Proceedings: Fostering Learning in Statistics and Data Science)

   In the 21st century with the rise of computing power, it has become increasingly important to create opportunities for students to learn to work with large, authentic, complex (LAC) data across multiple disciplines. DataFest, a hackathon style undergraduate event, creates a space for such inquiry due to the collaborative, data-driven, open-problem, real-world relevant nature of the challenge it presents. We present preliminary findings from research that explores how teams at DataFest leverage and integrate multidisciplinary tools and domain knowledge to engage productively with the data investigation process. Implications for statistics and data science education are discussed. 

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5. Consider “HACKS” when designing hackathon challenges: Hook, action, collaborative knowledge sharing

   https://doi.org/10.3389/feduc.2022.954044  

   Wallwey, Cassie; Longmeier, Meris M.; Hayde, Donnelley; Armstrong, Julia; Kajfez, Rachel; Pelan, Renee (September 2022, Frontiers in Education)

   Our world’s complex challenges increase the need for those entering STEAM (Science, Technology, Engineering, Arts, and Math) disciplines to be able to creatively approach and collaboratively address wicked problems – complex problems with no “right” answer that span disciplines. Hackathons are environments that leverage problem-based learning practices so student teams can solve problems creatively and collaboratively by developing a solution to given challenges using engineering and computer science knowledge, skills, and abilities. The purpose of this paper is to offer a framework for interdisciplinary hackathon challenge development, as well as provide resources to aid interdisciplinary teams in better understanding the context and needs of a hackathon to evaluate and refine hackathon challenges. Three cohorts of interdisciplinary STEAM researchers were observed and interviewed as they collaboratively created a hackathon challenge incorporating all cohort-member disciplines for an online high school hackathon. The observation data and interview transcripts were analyzed using thematic analysis to distill the processes cohorts underwent and resources that were necessary for successfully creating a hackathon challenge. Through this research we found that the cohorts worked through four sequential stages as they collaborated to create a hackathon challenge. We detail the stages and offer them as a framework for future teams who seek to develop an interdisciplinary hackathon challenge. Additionally, we found that all cohorts lacked the knowledge and experience with hackathons to make fully informed decisions related to the challenge’s topic, scope, outcomes, etc. In response, this manuscript offers five hackathon quality considerations and three guiding principles for challenge developers to best meet the needs and goals of hackathon sponsors and participants. 

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