Thinking about computational thinkingJames J. Lu, George H. L. Fletcher
Publikationsdatum:
Zu finden in: SIGCSE 2009, 2009
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Zusammenfassungen
Programming is to CS what proof construction is
to mathematics and what literary analysis is to
English.
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) Die Autoren vergleichen Programmieren mit dem Führen von Beweisen in der Mathematik oder der Literaturanalyse in der Sprache. Sie betonen, dass Programmieren bereits viele Konzepte von computational thinking voraussetze und sich deshalb nicht zum Einstieg in die Informatik eigne. Die Autoren schlagen eine computational thinking language als Alternative zu einer Programmiersprache vor. Der Artikel enthält 9 Beispiele, wie sich computatianal thinking ohne Programmieren vermitteln liesse.
Von Beat Döbeli Honegger, erfasst im Biblionetz am 23.04.2014While teaching everyone to think computationally is
a noble goal, there are pedagogical challenges. It is not
enough to simply repackage CS1, or CS0, and teach it at
an earlier stage, as many high schools and even lower-level
grades already do. Perhaps the most confounding issue is the
role of programming, and whether we can separate it from
teaching basic computer science. How much programming,
if any, should be required for CT proficiency? To answer
this question, we believe it is necessary to consider more
carefully the implications of aligning CT with the three R’s.
In this essay we explore this alignment and argue that to
successfully broaden awareness of the depth, breadth, and
beauty of computer science, efforts must be made to lay the
foundations of CT long before students experience their first
programming language.
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) Jeannette Wing’s call for teaching Computational Thinking
(CT) as a formative skill on par with reading, writing,
and arithmetic places computer science in the category of
basic knowledge. Just as proficiency in basic language arts
helps us to effectively communicate and in basic math helps
us to successfully quantitate, proficiency in computational
thinking helps us to systematically and efficiently process
information and tasks. But while teaching everyone to think
computationally is a noble goal, there are pedagogical challenges.
Perhaps the most confounding issue is the role of
programming, and whether we can separate it from teaching
basic computer science. How much programming, if any,
should be required for CT proficiency?
We believe that to successfully broaden participation in computer science, efforts must be made to lay the foundations of CT long before students experience their first programming language. We posit that programming is to Computer Science what proof construction is to mathematics, and what literary analysis is to English. Hence by analogy, programming should be the entrance into higher CS, and not the student’s first encounter in CS. We argue that in the absence of programming, teaching CT should focus on establishing vocabularies and symbols that can be used to annotate and describe computation and abstraction, suggest information and execution, and provide notation around which mental models of processes can be built. Lastly, we conjecture that students with sustained exposure to CT in their formative education will be better prepared for programming and the CS curriculum, and, furthermore, that they might choose to major in CS not only for career opportunities, but also for ist intellectual content.
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) We believe that to successfully broaden participation in computer science, efforts must be made to lay the foundations of CT long before students experience their first programming language. We posit that programming is to Computer Science what proof construction is to mathematics, and what literary analysis is to English. Hence by analogy, programming should be the entrance into higher CS, and not the student’s first encounter in CS. We argue that in the absence of programming, teaching CT should focus on establishing vocabularies and symbols that can be used to annotate and describe computation and abstraction, suggest information and execution, and provide notation around which mental models of processes can be built. Lastly, we conjecture that students with sustained exposure to CT in their formative education will be better prepared for programming and the CS curriculum, and, furthermore, that they might choose to major in CS not only for career opportunities, but also for ist intellectual content.
Dieses Konferenz-Paper erwähnt ...
Personen KB IB clear | Jeannette M. Wing | ||||||||||||||||||
Fragen KB IB clear | Gehört Programmieren zur Allgemeinbildung?Should programming be part of general education? | ||||||||||||||||||
Aussagen KB IB clear | Informatik ist mehr als Programmierencomputer science is more than programming | ||||||||||||||||||
Begriffe KB IB clear | computational thinkingcomputational thinking , computer science unpluggedcomputer science unplugged , Curriculum / Lehrplancurriculum , Informatikcomputer science , Programmierenprogramming | ||||||||||||||||||
Texte |
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Dieses Konferenz-Paper erwähnt vermutlich nicht ...
Nicht erwähnte Begriffe | Informatik-Didaktik, Informatik-Unterricht (Fachinformatik), Lehrplan 21 |
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7 Erwähnungen
- Computational Thinking Patterns (Andri Ioannidou, Vicki E. Bennett, Alexander Repenning, Kyu Han Koh, Ashok R. Basawapatna) (2011)
- Emerging Research, Practice, and Policy on Computational Thinking (Peter J. Rich, Charles B. Hodges) (2017)
- 7. Integrating Computational Thinking in Discrete Structures (Gerard Rambally)
- 14. Computational Thinking Conceptions and Misconceptions - Progression of Preservice Teacher Thinking During Computer Science Lesson Planning (Olgun Sadik, Anne-Ottenbreit Leftwich, Hamid Nadiruzzaman)
- Demystifying computational thinking (Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke) (2017)
- Proceedings of the 13th Workshop in Primary and Secondary Computing Education, WiPSCE 2018, Potsdam, Germany, October 04-06, 2018. (Andreas Mühling, Quintin I. Cutts) (2018)
- Informatics in Schools. New Ideas in School Informatics (Sergei Pozdniakov, Valentina Dagienė) (2019)
- Holistic STEAM Education Through Computational Thinking - A Perspective on Training Future Teachers (Arnold Pears, Erik Barendsen, Valentina Dagienė, Vladimiras Dolgopolovas, Eglė Jasutė)
- Computer programming skills - A cognitive perspective (Irene Graafsma) (2021)
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Beat und dieses Konferenz-Paper
Beat hat Dieses Konferenz-Paper während seiner Zeit am Institut für Medien und Schule (IMS) ins Biblionetz aufgenommen. Beat besitzt kein physisches, aber ein digitales Exemplar. Eine digitale Version ist auf dem Internet verfügbar (s.o.). Aufgrund der wenigen Einträge im Biblionetz scheint er es nicht wirklich gelesen zu haben. Es gibt bisher auch nur wenige Objekte im Biblionetz, die dieses Werk zitieren.