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On the cruelty of teaching Computer Science

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37 review for On the cruelty of teaching Computer Science

  1. 5 out of 5

    Brody

    Dijkstra's main point is that to use analogy to teach Computer Science is a failure of imagination and boldness. He argues that because computers can and will allow us to do such *un*imaginable things it's a pedagogical mistake to constrain the student mental model of what is possible with concepts or ideas that are fundamentally constrained and/or misleading. At first I laughed this off. Literally. Dijkstra is not a likable character even in his own speech! But with a few weeks to think about h Dijkstra's main point is that to use analogy to teach Computer Science is a failure of imagination and boldness. He argues that because computers can and will allow us to do such *un*imaginable things it's a pedagogical mistake to constrain the student mental model of what is possible with concepts or ideas that are fundamentally constrained and/or misleading. At first I laughed this off. Literally. Dijkstra is not a likable character even in his own speech! But with a few weeks to think about his point I think there is something fundamentally right about insisting we never anthropomorphize computers or analogize what they can do. To do so does actually constrain our imagination about them with practical results. I will strive to try and see this more radical, more novel, more scary universe that Dijkstra points to.

  2. 4 out of 5

    Max Lybbert

    This isn't truly a book, but a paper (an "EWD") available at http://www.cs.utexas.edu/users/EWD/ew... or http://www.cs.utexas.edu/users/EWD/tr... . Dijkstra was a professor for much of his life, and after making incredible contributions to computer science in the early days (recursion in Algol, wrote the first standard compliant Algol compiler, designed mutexes and semaphores, created the coloring garbage collection algorithm, created an algorithm for finding shortest paths ("Dijkstra's shortest This isn't truly a book, but a paper (an "EWD") available at http://www.cs.utexas.edu/users/EWD/ew... or http://www.cs.utexas.edu/users/EWD/tr... . Dijkstra was a professor for much of his life, and after making incredible contributions to computer science in the early days (recursion in Algol, wrote the first standard compliant Algol compiler, designed mutexes and semaphores, created the coloring garbage collection algorithm, created an algorithm for finding shortest paths ("Dijkstra's shortest paths"), created the Dijkstra banker's algorithm, etc.), he watched computer science education begin to resemble skilled tradesman education (e.g., http://cacm.acm.org/magazines/2010/1/... ). "On the cruelty of teaching Computer Science" was one of his efforts to lay out his ideals on computer science and on education from the perspective of a Texas A&M professor in 1988. The last paragraph of the paper is: Teaching to unsuspecting youngsters the effective use of formal methods is one of the joys of life because it is so extremely rewarding. Within a few months, they find their way in a new world with a justified degree of confidence that is radically novel for them; within a few months, their concept of intellectual culture has acquired a radically novel dimension. To my taste and style, that is what education is about. Universities should not be afraid of teaching radical novelties; on the contrary, it is their calling to welcome the opportunity to do so. Their willingness to do so is our main safeguard against dictatorships, be they of the proletariat, of the scientific establishment, or of the corporate elite.

  3. 4 out of 5

    քամի

    նշուում ա որպէս «համակարգչային գիտութիւնների մասին», բայց առհասարակ, շատ լաւ տեքստ ա նորարարութիւնների, մարդկանց/համալսարանների վերաբերմունքի եւ մօտեցման մասին։

  4. 5 out of 5

    Miki

    Very precise and well written. With the truth of a few of the challenges encountered when teaching a "new" science.

  5. 5 out of 5

    Alexei

    It’s disturbing

  6. 4 out of 5

    Aarti Kashyap

  7. 5 out of 5

    Samuel Sampaio

  8. 5 out of 5

    Samantha

  9. 4 out of 5

    Grzegorz

  10. 5 out of 5

    MarkusQ

  11. 5 out of 5

    Gustavo Gonzalez

  12. 4 out of 5

    Brian

  13. 4 out of 5

    destone28

  14. 4 out of 5

    Subhajit Das

  15. 5 out of 5

    Ezequiel

  16. 5 out of 5

    Eric Kaun

  17. 4 out of 5

    Suri

  18. 5 out of 5

    Dnyaneshwer Pendurkar

  19. 4 out of 5

    Tim

  20. 4 out of 5

    John Cajucom

  21. 4 out of 5

    Leela

  22. 4 out of 5

    Walden

  23. 4 out of 5

    Julian

  24. 4 out of 5

    Tabina Bajwa

  25. 5 out of 5

    Ewerton Mores

  26. 4 out of 5

    M.ramachandran

  27. 5 out of 5

    Alex

  28. 4 out of 5

    Nithin Saji

  29. 5 out of 5

    Cảnh Nguyễn

  30. 5 out of 5

    Vector Shaw

  31. 4 out of 5

    Giada Morat

  32. 4 out of 5

    Matthew Chan

  33. 5 out of 5

    Jina

  34. 4 out of 5

    Kristóf

  35. 4 out of 5

    Sam

  36. 5 out of 5

    Rúnar

  37. 4 out of 5

    Morgan Showman

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