Concepts before coding: non-programming interactives to advance learning of introductory programming concepts in middle school

Grover, Shuchi; Jackiw, Nicholas; Lundh, Patrik

doi:10.1080/08993408.2019.1568955

Cited by 37 publications

(18 citation statements)

References 26 publications

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“…Design-based research through iteration draws upon educational theories to design classroom interventions in highly specified contexts to develop design principles [6,49]. Design-based research has been used previously to look into computer science and computational thinking curriculum [13,15]. This affords the researcher to develop highly specific theories within undergraduate populations around the use of computational thinking in the classroom.…”

Section: Implications For Educational Researchmentioning

confidence: 99%

Computational thinking in higher education: A review of the literature

Lyon

Magana

2020

Comp Applic In Engineering

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Computational thinking is of growing interest to the science, technology, engineering, and mathematics (STEM) education research community. Calls from national agencies look to increase computation in STEM education. This review identifies key areas for future study by reviewing recent empirical studies that investigate computational thinking in teaching and learning contexts within higher education. Using a systematic process, this review identified four different databases for peer‐reviewed research articles using keywords. Results were evaluated against inclusion and exclusion criteria. Studies were analyzed for types of methods, target population, the role of computational thinking, pedagogical designs used, and significant findings of the study. This process resulted in a final set of 13 studies. The results indicate that computational thinking research in higher education is growing, yet there are opportunities for more research. The findings of this study highlight the need for more concrete definitions and implementations of computational thinking within higher education spaces.

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Section: Implications For Educational Researchmentioning

confidence: 99%

Computational thinking in higher education: A review of the literature

Lyon

Magana

2020

Comp Applic In Engineering

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“…Programming is considered a fundamental component of CT, as it provides a context for students to develop CT-related skill sets (Brennan & Resnick, 2012; Grover, Jackiw, & Lundh, 2019; Grover & Pea, 2013; Guzdial, 2004). Traditionally, learning to program focused primarily on coding skills, an effort that has been criticized because it fails to demonstrate what students learn and how such learning can be transferred in other subjects (Kafai & Burke, 2013).…”

Section: Theoretical Perspectivesmentioning

confidence: 99%

“…Specifically, identified CT concepts and competencies include problem decomposition, algorithmic thinking, abstraction, data, automation, parallelization, and simulation (Computer Science Teachers Association & International Society for Technology in Education, 2011). Programming is considered a fundamental component of CT, as it provides a context for students to develop CT-related skill sets (Brennan & Resnick, 2012;Grover, Jackiw, & Lundh, 2019;Grover & Pea, 2013;Guzdial, 2004). Traditionally, learning to program focused primarily on coding skills, an effort that has been criticized because it fails to demonstrate what students learn and how such learning can be transferred in other subjects (Kafai & Burke, 2013).…”

Section: Definition Of Computational Thinkingmentioning

confidence: 99%

A Multiyear Investigation of Student Computational Thinking Concepts, Practices, and Perspectives in an After-School Computing Program

Mouza

Pan

Huí

et al. 2020

Journal of Educational Computing Research

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In this work, we examine whether repeated participation in an after-school computing program influenced student learning of computational thinking concepts, practices, and perspectives. We also examine gender differences in learning outcomes. The program was developed through a school–university partnership. Data were collected from 138 students over a 2.5-year period. Data sources included pre–post content assessments of computational concepts related to programming in addition to computational artifacts and interviews with a purposeful sample of 12 participants. Quantitative data were analyzed using statistical methods to identify gains in pre- and post-learning of computational thinking concepts and examine potential gender differences. Interview data were analyzed qualitatively. Results indicated that students made significant gains in their learning of computational thinking concepts and that gains persisted over time. Results also revealed differences in learning of computational thinking concepts among boys and girls both at the beginning and end of the program. Finally, results from student interviews provided insights into the development of computational thinking practices and perspectives over time. Results have implications for the design of after-school computing programs that help broaden participation in computing.

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“…They suggested further focus on mapping narrative elements to the code and problem structure was a necessity [104]. Grover et al [64] explored non-programming interactive activities with relevant narrative contexts prior to application in code. Their research found promise for such an approach, and specifically note that this approach allows for incremental abstraction of ideas [64].…”

Section: Analogy Within the Cs Disciplinementioning

confidence: 99%

“…Grover et al [64] explored non-programming interactive activities with relevant narrative contexts prior to application in code. Their research found promise for such an approach, and specifically note that this approach allows for incremental abstraction of ideas [64]. Suh [148] investigates the application of comics in learning programming, both with instructor designed comics as well as comic creation activities.…”

Section: Analogy Within the Cs Disciplinementioning

confidence: 99%

The Stained Glass of Knowledge: On Understanding Novice Mental Models of Computing

Bettin¹

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Concepts before coding: non-programming interactives to advance learning of introductory programming concepts in middle school

Cited by 37 publications

References 26 publications

Computational thinking in higher education: A review of the literature

Computational thinking in higher education: A review of the literature

A Multiyear Investigation of Student Computational Thinking Concepts, Practices, and Perspectives in an After-School Computing Program

The Stained Glass of Knowledge: On Understanding Novice Mental Models of Computing

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