J
Joyce Malyn-Smith
Publications - 23
Citations - 1142
Joyce Malyn-Smith is an academic researcher. The author has contributed to research in topics: Computational thinking & Curriculum. The author has an hindex of 8, co-authored 22 publications receiving 799 citations.
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Journal ArticleDOI
Computational thinking for youth in practice
Irene Lee,Fred Martin,Jill Denner,Bob Coulter,Walter C. Allan,Jeri Erickson,Joyce Malyn-Smith,Linda Werner +7 more
TL;DR: A "use-modify-create" framework is presented, representing three phases of students' cognitive and practical activity in computational thinking, suggesting continued investment in the development of CT-rich learning environments, in educators who can facilitate their use, and in research on the broader value of computational thinking.
Journal Article
A K-6 computational thinking curriculum framework: implications for teacher knowledge
Charoula Angeli,Joke Voogt,Andrew Fluck,Mary Webb,Margaret Cox,Joyce Malyn-Smith,Jason Zagami +6 more
TL;DR: There is a lack of adequate empirical evidence in terms of the effectiveness of the frameworks proposed herein, but it is expected that the knowledge and research base will dramatically increase over the next several years, as more countries around the world add computer science as a separate school subject to their K-6 curriculum.
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Computational Thinking from a Disciplinary Perspective: Integrating Computational Thinking in K-12 Science, Technology, Engineering, and Mathematics Education
TL;DR: A recent special issue of the Journal of Science Education and Technology focused on computational thinking (CT) from a disciplinary perspective as discussed by the authors is an overview of recent work in CT integration in K-12 STEM education.
Journal Article
Arguing for computer science in the school curriculum
Andrew Fluck,Mary Webb,Margaret Cox,Charoula Angeli,Joyce Malyn-Smith,Joke Voogt,Jason Zagami +6 more
TL;DR: It is argued computer science is rapidly becoming critical for generating new knowledge, and should be taught as a distinct subject or content area, especially in secondary schools, and also a beneficence matrix to assist curriculum designers is explored.
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Machine learning for human learners: opportunities, issues, tensions and threats
Mary Webb,Andrew Fluck,Johannes Magenheim,Joyce Malyn-Smith,Juliet Waters,Michelle Deschênes,Jason Zagami +6 more
TL;DR: This article compares deep learning in computers and humans to examine their similarities and differences and concludes with recommendations about machine learning for teachers, students, policymakers, developers and researchers.