Promoting pupils’ computational thinking skills and self‑efficacy a problem-solving instructional approach

Computational thinking (CT) is a fundamental skill and an analytical ability that children in the twenty-first century should develop. Students should begin to work with algorithmic problem-solving and computational methods in K-12. Drawing on a conceptual framework (IGGIA) that combines CT and prob...

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Veröffentlicht in:Educational technology research and development Jg. 69; H. 3; S. 1599 - 1616
Hauptverfasser: Ma, Hongliang, Zhao, Mei, Wang, Huixin, Wan, Xinqi, Cavanaugh, Terence W., Liu, Ji
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer Science + Business Media 01.06.2021
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ISSN:1042-1629, 1556-6501
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Abstract Computational thinking (CT) is a fundamental skill and an analytical ability that children in the twenty-first century should develop. Students should begin to work with algorithmic problem-solving and computational methods in K-12. Drawing on a conceptual framework (IGGIA) that combines CT and problem-solving, this study designed and implemented an interdisciplinary Scratch course in a primary school, examined the impact of the new problem-solving instructional approach (the adapted IGGIA) on pupils’ CT skills and self-efficacy, and explored the gender differences in these two aspects. A pretest–posttest nonequivalent group design was conducted among 63 fifth-grade students in two computer science classes over 14 weeks. Both quantitative and qualitative data were collected through the administration of CT scales, Scratch artifacts analysis and focus group interviews. The results revealed that the adapted IGGIA (1) significantly improved the CT skills of primary school students; (2) had a significant positive impact on pupils’ CT self-efficacy, especially on their critical thinking, algorithmic thinking and problem-solving; and (3) significantly enhanced girls’ CT skills and self-efficacy. These findings indicated that problem-solving instructional approaches could promote both cognitive and noncognitive aspects of students’ deeper computational learning.
AbstractList Computational thinking (CT) is a fundamental skill and an analytical ability that children in the twenty-first century should develop. Students should begin to work with algorithmic problem-solving and computational methods in K-12. Drawing on a conceptual framework (IGGIA) that combines CT and problem-solving, this study designed and implemented an interdisciplinary Scratch course in a primary school, examined the impact of the new problem-solving instructional approach (the adapted IGGIA) on pupils' CT skills and self-efficacy, and explored the gender differences in these two aspects. A pretest-posttest nonequivalent group design was conducted among 63 fifth-grade students in two computer science classes over 14 weeks. Both quantitative and qualitative data were collected through the administration of CT scales, Scratch artifacts analysis and focus group interviews. The results revealed that the adapted IGGIA: (1) significantly improved the CT skills of primary school students; (2) had a significant positive impact on pupils' CT self-efficacy, especially on their critical thinking, algorithmic thinking and problem-solving; and (3) significantly enhanced girls' CT skills and self-efficacy. These findings indicated that problem-solving instructional approaches could promote both cognitive and noncognitive aspects of students' deeper computational learning.
Computational thinking (CT) is a fundamental skill and an analytical ability that children in the twenty-first century should develop. Students should begin to work with algorithmic problem-solving and computational methods in K-12. Drawing on a conceptual framework (IGGIA) that combines CT and problem-solving, this study designed and implemented an interdisciplinary Scratch course in a primary school, examined the impact of the new problem-solving instructional approach (the adapted IGGIA) on pupils’ CT skills and self-efficacy, and explored the gender differences in these two aspects. A pretest–posttest nonequivalent group design was conducted among 63 fifth-grade students in two computer science classes over 14 weeks. Both quantitative and qualitative data were collected through the administration of CT scales, Scratch artifacts analysis and focus group interviews. The results revealed that the adapted IGGIA (1) significantly improved the CT skills of primary school students; (2) had a significant positive impact on pupils’ CT self-efficacy, especially on their critical thinking, algorithmic thinking and problem-solving; and (3) significantly enhanced girls’ CT skills and self-efficacy. These findings indicated that problem-solving instructional approaches could promote both cognitive and noncognitive aspects of students’ deeper computational learning.
Audience Intermediate Grades
Grade 5
Middle Schools
Elementary Education
Academic
Author Wang, Huixin
Liu, Ji
Zhao, Mei
Cavanaugh, Terence W.
Wan, Xinqi
Ma, Hongliang
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  givenname: Xinqi
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  fullname: Wan, Xinqi
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  givenname: Terence W.
  surname: Cavanaugh
  fullname: Cavanaugh, Terence W.
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  givenname: Ji
  surname: Liu
  fullname: Liu, Ji
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Snippet Computational thinking (CT) is a fundamental skill and an analytical ability that children in the twenty-first century should develop. Students should begin to...
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SubjectTerms Computer science
Computer Science Education
Education
Educational Technology
Elementary School Students
Gender Differences
Grade 5
Instructional Effectiveness
Interdisciplinary Approach
Learning and Instruction
Methods
Problem Solving
Programming Languages
RESEARCH ARTICLE
Self Efficacy
Skill Development
Skills
Students
Thinking Skills
Subtitle a problem-solving instructional approach
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Title Promoting pupils’ computational thinking skills and self‑efficacy
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