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Coding and Computational Thinking across the Curriculum: A Review of Educational Outcomes

Title: Coding and Computational Thinking across the Curriculum: A Review of Educational Outcomes
Language: English
Authors: Kathy A. Mills (ORCID 0000-0003-1140-3545); Jen Cope (ORCID 0000-0001-7003-4474); Laura Scholes (ORCID 0000-0002-8849-2825); Luke Rowe (ORCID 0000-0001-5027-733X)
Source: Review of Educational Research. 2025 95(3):581-618.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 38
Publication Date: 2025
Document Type: Journal Articles; Reports - Research; Information Analyses
Descriptors: Coding; Programming; Computation; Thinking Skills; Educational Environment; Skill Development; Learner Engagement; Outcomes of Education; Educational Research; Curriculum
DOI: 10.3102/00346543241241327
ISSN: 0034-6543; 1935-1046
Abstract: Teaching coding and computational thinking is an emerging educational imperative, now embedded in compulsory curriculum in the United States, Finland, the UK, Germany, Belgium, the Netherlands, New Zealand, and Australia. This meta-synthesis of 49 studies critically reviews recent international research (2009-2022) of coding and computational thinking as core and integrated across the curriculum. It addresses four essential problems: (a) What are the key features of learning environments that successfully develop students' coding and computational thinking? (b) What is the impact of student engagement in coding and computational thinking on learning outcomes across curriculum areas? (c) What pedagogical constraints are evident for coding and computational thinking, including across curriculum areas? and (d) Which conceptual frameworks support coding and computational thinking, and what has been marginalized or excluded? The review advances knowledge of coding and computational thinking--vital to guide and develop future AI-based solutions to real-world problems that challenge disciplinary boundaries.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1471305
Database: ERIC