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ADAPTTER: Developing a framework for teaching computational thinking in second‑level schools by design research

Kirwan, Colette orcid logoORCID: 0000-0003-3145-3574, Costello, Eamon orcid logoORCID: 0000-0002-2775-6006 and Donlon, Enda orcid logoORCID: 0000-0003-2817-9033 (2022) ADAPTTER: Developing a framework for teaching computational thinking in second‑level schools by design research. TechTrends, 66 . pp. 495-509. ISSN 8756-3894

Abstract
Computational Thinking (CT) is a problem-solving process applicable across all disciplines. It has been defined as a 21st-century skill (Wing, Communications of the ACM, 49(3), 33–35, 2006). Unfortunately, little pedagogical research is available to guide teachers and designers when devising a CT course. This study addresses this issue by describing how a framework to teach CT to second-level students evolved. This framework, ADAPTTER, has been shown to result in a high quality, engaging, low threshold, effective, and practical course. A three-phase Educational Design Research study was employed to develop this framework. It involved six schools, eleven teachers, four content experts, and 446 students. Data was gathered using various means: teacher interviews and diaries, students' questionnaires, artefacts, and tests. The ADAPTTER framework is offered as a way for teachers and researchers to design a CT course, understand its components and have conversations around the same.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:Computational thinking; Framework; Teaching; Learning; Second-level education; Educational designresearch
Subjects:Social Sciences > Education
Social Sciences > Teaching
DCU Faculties and Centres:Research Institutes and Centres > NIDL (National Institute for Digital Learning)
DCU Faculties and Schools > Institute of Education > School of STEM Education, Innovation, & Global Studies
Publisher:Springer
Official URL:https://doi.org/10.1007/s11528-022-00735-8
Copyright Information:© 2022The Authors.
Funders:Open Access funding provided by the IReL Consortium
ID Code:27083
Deposited On:29 Apr 2022 13:12 by Thomas Murtagh . Last Modified 23 Mar 2023 15:10
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