Connecting computational thinking in everyday reasoning and programming for elementary school students

Shen, Ji; Chen, Guanhua; Barth-Cohen, Lauren; Jiang, Shiyan; Eltoukhy, Moataz

doi:10.1080/15391523.2020.1834474

Cited by 20 publications

(17 citation statements)

References 29 publications

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“…In total, 22 studies were analyzed to answer the research questions for this systematic review. It should be noted that two of these included studies were published online first during the literature search time period and later published on paper in 2022 (i.e., Hsiao et al, 2022;Shen et al, 2022).…”

Section: Data Sources and Analysismentioning

confidence: 99%

“…Among the 22 studies, 18 studies (82%) took place in formal education settings, including pre-kindergarten to elementary school classrooms (i.e., Angeli & Valanides, 2020;Bers et al, 2014Bers et al, , 2019Cherniak et al, 2019;Chevalier et al, 2020;Chiazzese et al, 2019;Fanchamps et al, 2021;García-Valcárcel-Muñoz-Repiso & Caballero-González, 2019;Hsiao et al, 2022;Kazakoff & Bers, 2012;Kopcha et al, 2021;Moore et al, 2020;Nam et al, 2019;Noh & Lee, 2020;Sáez-López et al, 2019;Shen et al, 2022;Taylor & Baek, 2019). Four studies took place in informal education settings, such as summer camps/programs and after-school programs (i.e., Luo et al, 2020;Newton et al, 2020;Pugnali et al, 2017).…”

Section: Settings and Durations Of The Robotics Curriculum Activitiesmentioning

confidence: 99%

“…Algorithmic Thinking, defined by Shen et al (2022) as devising a step-by-step solution to solve a problem, was examined in 5 studies (i.e., Angeli & Valanides, 2020;Chiazzese et al, 2019;Fanchamps et al, 2021;Shen et al, 2022) with learners of various ages from kindergarteners to 5 th graders. For example, Shen et al (2022) developed and implemented a humanoid robotics curriculum that involved fifth graders in creating solution algorithms (i.e., the coded steps of drawing a triangle). In Angeli and Valanides (2020) study, kindergarteners created algorithms that commanded the movements of a bee-shaped robot on a mat.…”

Section: Ct Skills Developedmentioning

confidence: 99%

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Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review

Ching

Hsu

2023

TechTrends

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Educational robotics has been adopted to create interactive and engaging learning environments to develop computational thinking (CT) in K-12 learners. This study systematically examined 22 peer-reviewed empirical research articles on the use of educational robotics to develop CT in young learners (pre-kindergarten to 6th grade) published between 2012 and 2021. The findings revealed that using robotics activities to develop CT has mostly been studied in the formal education settings with the duration of robotics curricular activities ranging from 80 minutes to 24 hours. The five CT skills studied most often include Sequencing, Conditionals, Loops, Debugging, and Algorithmic Thinking. The different versions of LEGO Mindstorms are the most frequently adopted robotic kits in the examined studies. The most frequently adopted learning and instructional strategies in the robotics activities include collaborative learning, project-based learning, and embodied learning. This paper identified and discussed developmentally appropriated CT skills, robotics kits, and pedagogical approaches suitable for supporting CT development in young learners. The findings can guide educators and instructional designers for future robotics activity design and development endeavors. This paper also identified gaps in the current research and recommended directions for advancing research in adopting robotics to develop CT in young learners.

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Section: Data Sources and Analysismentioning

confidence: 99%

Section: Settings and Durations Of The Robotics Curriculum Activitiesmentioning

confidence: 99%

Section: Ct Skills Developedmentioning

confidence: 99%

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Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review

Ching

Hsu

2023

TechTrends

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“…Although the problem solving challenge improved students' awareness of CT problem solving, Standl found that students struggled in abstraction and decomposition. Other studies (e.g., Chen et al, 2017; Shen et al, 2020) also included everyday problem solving in their investigations into CT. In the study by Chen et al (2017), everyday problems, such as finding an optimal way to load a washing machine, were operationalized as multiple‐choice questions.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…In the study by Chen et al (2017), everyday problems, such as finding an optimal way to load a washing machine, were operationalized as multiple‐choice questions. Shen et al (2020) operationalized everyday problem solving through an exercise in which participants were asked to deduce the most cost‐effective route between two locations, given a map showing a network of flights and information about costs and travel time. Although the task of finding the most cost‐effective flight was open‐ended and offered some insight into the use of CT in everyday problems, the researchers' analysis focused on comparing the pre‐test and post‐test improvements after a robotic intervention.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Discovering computational thinking in everyday problem solving: A multiple case study of route planning

Ezeamuzie

Leung

Garcia

et al. 2022

Computer Assisted Learning

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Background: The idea of computational thinking is underpinned by the belief that anyone can learn and use the underlying concepts of computer science to solve everyday problems. However, most studies on the topic have investigated the development of computational thinking through programming activities, which are cognitively demanding. There is a dearth of evidence on how computational thinking augments everyday problem solving when it is decontextualized from programming.Objectives: In this study, we examined how computational thinking, when untangled from the haze of programming, is demonstrated in everyday problem solving, and investigated the features of such solvable problems.Methods: Using a multiple case study approach, we tracked how seven university students used computational thinking to solve the everyday problem of a route planning task as part of an 8-week-long Python programming course.Results and Conclusions: Computational thinking practices are latent in everyday problems, and intentionally structuring everyday problems is valuable for discovering the applicability of computational thinking. Decomposition and abstraction are prominent computational thinking components used to simplify everyday problem solving.Implications: It is important to strike a balance between the correctness of algorithms and simplification of the process of everyday problem solving.

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How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

Jiang,

Islam,

et al. 2023

J Res Sci Teach

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Computational thinking (CT) is vital for success in numerous domains. However, the nature, definition, and scope of CT are ill‐defined, and research on how best to develop CT is very limited. This study focused on how thinking styles and STEM attitudes have effects on computational thinking. Using a proportionate stratified random sampling procedure, 1195 students from two universities were surveyed. A structural equation modeling analysis showed that students' thinking styles and STEM attitudes directly predicted their computational thinking skills and that thinking styles mediated the relationship between STEM attitudes and computational thinking skills. Thinking styles and STEM attitudes are strong predictors of CT skills. Based on the results, we recommended that the conceptualization of CT be broadened to reflect its trans‐disciplinary nature within the context of STEM education. This study adds to the limited theoretical understanding of CT and CT‐predictors in higher education, which has been studied much less than in K‐12 education.

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Connecting computational thinking in everyday reasoning and programming for elementary school students

Cited by 20 publications

References 29 publications

Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review

Educational Robotics for Developing Computational Thinking in Young Learners: A Systematic Review

Discovering computational thinking in everyday problem solving: A multiple case study of route planning

How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

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