Open Access
Computational Thinking 計算論的思考
Jeannette M. Wing,翻訳：中島 秀之 +1 more
- Vol. 56, Iss: 6, pp 584-587
TLDR
In this article, a universally applicable attitude and skill set for computer science is presented, which is a set of skills and attitudes that everyone would be eager to learn and use, not just computer scientists.Abstract:
It represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use.read more
Citations
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The promise of computational journalism
TL;DR: In this article, the authors argue that computational journalism techniques may provide new foundations for original investigative journalism and increase the scope for new forms of interaction with readers, drawing upon international examples.
It's computational thinking! Bebras tasks in the curriculum
Valentina Dagiene,Sue Sentance +1 more
TL;DR: It is proposed that Bebras tasks can be used within the school curriculum to promote computational thinking and provide teaching materials and examples of BebrAs tasks that could be incorporated into the curriculum are given.
INNODOCT/17. International conference on innovation,documentation and education
Fernando José Garrigós Simón,Sofia Estelles Miguel,Ismael Lengua Lengua,José Onofre Montesa,Carlos Manuel Dema Pérez,Juan Vicente Oltra Gutiérrez,Yeamduan Narangajavana,María José Verdecho Sáez +7 more
TL;DR: In this paper, the authors present an analysis of the 62 universities in Ecuador that are in the web ranking of universities, in order to evaluate the use of digital media and obtain information on the management of university e-branding.
MonographDOI
1 what is computational thinking
Peter J. Denning,Matti Tedre +1 more
TL;DR: An algorithm is a set of rules for getting a specific output from a specific input as mentioned in this paper, each step must be so precisely defined that it can be translated into computer language and executed by machine.
Proceedings ArticleDOI
PUMICE: A Multi-Modal Agent that Learns Concepts and Conditionals from Natural Language and Demonstrations
Toby Jia-Jun Li,Marissa Radensky,Justin Jia,Kirielle Singarajah,Tom M. Mitchell,Brad A. Myers +5 more
TL;DR: In this article, a multi-modal domain-independent approach that combines natural language programming and programming-by-demonstration is proposed to enable users to first naturally describe tasks and associated conditions at a high level, and then collaborate with the agent to recursively resolve any ambiguities or vagueness through conversations and demonstrations.
References
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Journal ArticleDOI
Scratch: programming for all
Mitchel Resnick,John Maloney,Andrés Monroy-Hernández,Natalie Rusk,Evelyn Eastmond,Karen Brennan,Amon Millner,Eric Rosenbaum,Jay Silver,Brian Silverman,Yasmin B. Kafai +10 more
TL;DR: "Digital fluency" should mean designing, creating, and remixing, not just browsing, chatting, and interacting.
Journal ArticleDOI
Computational Thinking in K–12 A Review of the State of the Field
Shuchi Grover,Roy Pea +1 more
TL;DR: The current state of discourse on computational thinking in K-12 education by examining mostly recently published academic literature that uses Wing's article as a springboard, identifies gaps in research, and articulates priorities for future inquiries as mentioned in this paper.
Journal ArticleDOI
Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community?
Valerie Barr,Chris Stephenson +1 more
TL;DR: The process of increasing student exposure to computational thinking in K-12 is complex, requiring systemic change, teacher engagement, and development of signifi cant resources.
Journal ArticleDOI
Computational thinking and thinking about computing
TL;DR: In thinking about computing, the authors need to be attuned to the three drivers of their field: science, technology and society, to revisit the most basic scientific questions of computing.
Journal ArticleDOI
How the Machine 'Thinks:' Understanding Opacity in Machine Learning Algorithms
TL;DR: This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring.