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Cracking the code: Co-coding with AI in creative programming education

Jonsson, Martin, Tholander, Jakob·2022·Creativity and Cognition
DOI 10.1145/3527927.3532801
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Figure 1 Participants engaged in co-creating computational graphics with the help of generative machine learning
Figure 1 Participants engaged in co-creating computational graphics with the help of generative machine learningCC-BY · From the PDF
Figure 3 Image artworks generated by the participants in the workshop. A majority of the sketches were animated and some of them were also interactive, reacting to mouse movements. P2 is omitted since the project did not contain any working programming code
Figure 3 Image artworks generated by the participants in the workshop. A majority of the sketches were animated and some of them were also interactive, reacting to mouse movements. P2 is omitted since the project did not contain any working programming codeCC-BY · From the PDF
Figure 4 An early attempt at creating an expression by asking the system to create a 'mountain using lines', resulting in a triangular shape resembling a mountain, but also a set of (not asked for) animated vertical lines
Figure 4 An early attempt at creating an expression by asking the system to create a 'mountain using lines', resulting in a triangular shape resembling a mountain, but also a set of (not asked for) animated vertical linesCC-BY · From the PDF

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Research works printed but not linked: 35

  1. 10.1145/3357236.3395538 · DOI
  2. 10.1145/3290605.3300233 · DOI · Paper page
  3. 10.1145/3373644 · DOI
  4. 10.1145/3126594.3126637 · DOI · Paper page
  5. 10.1215/9780822388128 · DOI · Paper page
  6. 10.1162/LEON_a_00934 · DOI
  7. Tom B. Brown , Benjamin Mann , Nick Ryder , Melanie Subbiah , Jared Kaplan , Prafulla Dhariwal , Arvind Neelakantan , Pranav Shyam , Girish Sastry , Amanda Askell , Sandhini Agarwal , Ariel Herbert-Voss , Gretchen Krueger , Tom Henighan , Rewon Child , Aditya Ramesh , Daniel M. Ziegler , Jeffrey Wu , Clemens Winter , Christopher Hesse , Mark Chen , Eric Sigler , Mateusz Litwin , Scott Gray , Benjamin Chess , Jack Clark , Christopher Berner , Sam McCandlish , Alec Radford , Ilya Sutskever , and Dario Amodei . 2020. Language Models are Few-Shot Learners. arXiv:2005.14165 [cs] (July 2020 ). http://arxiv.org/abs/2005.14165 arXiv:2005.14165. Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. arXiv:2005.14165 [cs] (July 2020). http://arxiv.org/abs/2005.14165 arXiv:2005.14165. · arXiv
  8. 10.1145/1357054.1357123 · DOI
  9. 10.1016/j.autcon.2004.12.004 · DOI
  10. Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Ponde de Oliveira Pinto Jared Kaplan Harri Edwards Yuri Burda Nicholas Joseph Greg Brockman Alex Ray Raul Puri Gretchen Krueger Michael Petrov Heidy Khlaaf Girish Sastry Pamela Mishkin Brooke Chan Scott Gray Nick Ryder Mikhail Pavlov Alethea Power Lukasz Kaiser Mohammad Bavarian Clemens Winter Philippe Tillet Felipe Petroski Such Dave Cummings Matthias Plappert Fotios Chantzis Elizabeth Barnes Ariel Herbert-Voss William Hebgen Guss Alex Nichol Alex Paino Nikolas Tezak Jie Tang Igor Babuschkin Suchir Balaji Shantanu Jain William Saunders Christopher Hesse Andrew N. Carr Jan Leike Josh Achiam Vedant Misra Evan Morikawa Alec Radford Matthew Knight Miles Brundage Mira Murati Katie Mayer Peter Welinder Bob McGrew Dario Amodei Sam McCandlish Ilya Sutskever and Wojciech Zaremba. 2021. Evaluating Large Language Models Trained on Code. arXiv:2107.03374 [cs] (July 2021). http://arxiv.org/abs/2107.03374 arXiv:2107.03374. Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Ponde de Oliveira Pinto Jared Kaplan Harri Edwards Yuri Burda Nicholas Joseph Greg Brockman Alex Ray Raul Puri Gretchen Krueger Michael Petrov Heidy Khlaaf Girish Sastry Pamela Mishkin Brooke Chan Scott Gray Nick Ryder Mikhail Pavlov Alethea Power Lukasz Kaiser Mohammad Bavarian Clemens Winter Philippe Tillet Felipe Petroski Such Dave Cummings Matthias Plappert Fotios Chantzis Elizabeth Barnes Ariel Herbert-Voss William Hebgen Guss Alex Nichol Alex Paino Nikolas Tezak Jie Tang Igor Babuschkin Suchir Balaji Shantanu Jain William Saunders Christopher Hesse Andrew N. Carr Jan Leike Josh Achiam Vedant Misra Evan Morikawa Alec Radford Matthew Knight Miles Brundage Mira Murati Katie Mayer Peter Welinder Bob McGrew Dario Amodei Sam McCandlish Ilya Sutskever and Wojciech Zaremba. 2021. Evaluating Large Language Models Trained on Code. arXiv:2107.03374 [cs] (July 2021). http://arxiv.org/abs/2107.03374 arXiv:2107.03374. · arXiv
  11. 10.1109/MSP.2017.2765202 · DOI · Paper page
  12. 10.1145/2901790.2901879 · DOI
  13. 10.1145/2702123.2702547 · DOI
  14. Tayebeh Fani and Farid Ghaemi . 2011. Implications of Vygotsky’s Zone of Proximal Development (ZPD) in Teacher Education: ZPTD and Self-scaffolding. Procedia - Social and Behavioral Sciences 29 (Jan . 2011 ), 1549–1554. https://doi.org/10.1016/j.sbspro.2011.11.396 10.1016/j.sbspro.2011.11.396 Tayebeh Fani and Farid Ghaemi. 2011. Implications of Vygotsky’s Zone of Proximal Development (ZPD) in Teacher Education: ZPTD and Self-scaffolding. Procedia - Social and Behavioral Sciences 29 (Jan. 2011), 1549–1554. https://doi.org/10.1016/j.sbspro.2011.11.396 · DOI
  15. 10.1162/desi_a_00612 · DOI
  16. 10.1007/s00779-013-0690-y · DOI
  17. 10.1016/j.intcom.2008.10.004 · DOI
  18. 10.1145/3173574.3173699 · DOI
  19. 10.1145/2858036.2858288 · DOI · Paper page
  20. Betti Marenko . 2015. When making becomes divination: Uncertainty and contingency in computational glitch-events. Design Studies 41 (Nov . 2015 ), 110–125. https://doi.org/10.1016/j.destud.2015.08.004 10.1016/j.destud.2015.08.004 Betti Marenko. 2015. When making becomes divination: Uncertainty and contingency in computational glitch-events. Design Studies 41 (Nov. 2015), 110–125. https://doi.org/10.1016/j.destud.2015.08.004 · DOI
  21. Betti Marenko and Philip van Allen . 2016. Animistic design: how to reimagine digital interaction between the human and the nonhuman. Digital Creativity 27, 1 (Jan . 2016 ), 52–70. https://doi.org/10.1080/14626268.2016.1145127 Publisher : Routledge _eprint: https://doi.org/10.1080/14626268.2016.1145127. 10.1080/14626268.2016.1145127 Betti Marenko and Philip van Allen. 2016. Animistic design: how to reimagine digital interaction between the human and the nonhuman. Digital Creativity 27, 1 (Jan. 2016), 52–70. https://doi.org/10.1080/14626268.2016.1145127 Publisher: Routledge _eprint: https://doi.org/10.1080/14626268.2016.1145127. · DOI
  22. Jon McCormack , Alan Dorin , and Troy Innocent . 2004 . Generative Design: A Paradigm for Design Research.DRS Biennial Conference Series (Nov. 2004 ). https://dl.designresearchsociety.org/drs-conference-papers/drs2004/researchpapers/171 Jon McCormack, Alan Dorin, and Troy Innocent. 2004. Generative Design: A Paradigm for Design Research.DRS Biennial Conference Series (Nov. 2004). https://dl.designresearchsociety.org/drs-conference-papers/drs2004/researchpapers/171
  23. 10.1147/sj.202.0184 · DOI
  24. James Mountstephens and Jason Teo . 2020 . Progress and Challenges in Generative Product Design : A Review of Systems. Computers 9 , 4 (Dec. 2020), 80. https://doi.org/10.3390/computers9040080 Number: 4 Publisher: Multidisciplinary Digital Publishing Institute. 10.3390/computers9040080 James Mountstephens and Jason Teo. 2020. Progress and Challenges in Generative Product Design: A Review of Systems. Computers 9, 4 (Dec. 2020), 80. https://doi.org/10.3390/computers9040080 Number: 4 Publisher: Multidisciplinary Digital Publishing Institute. · DOI
  25. J. Brian Pickering , Vegard Engen , and Paul Walland . 2017. The Interplay Between Human and Machine Agency . In Human-Computer Interaction. User Interface Design, Development and Multimodality(Lecture Notes in Computer Science) , Masaaki Kurosu (Ed.). Springer International Publishing , Cham , 47–59. https://doi.org/10.1007/978-3-319-58071-5_4 10.1007/978-3-319-58071-5_4 J. Brian Pickering, Vegard Engen, and Paul Walland. 2017. The Interplay Between Human and Machine Agency. In Human-Computer Interaction. User Interface Design, Development and Multimodality(Lecture Notes in Computer Science), Masaaki Kurosu (Ed.). Springer International Publishing, Cham, 47–59. https://doi.org/10.1007/978-3-319-58071-5_4 · DOI
  26. 10.1145/325737.325845 · DOI
  27. Mitchel Resnick and Eric Rosenbaum . 2013. Designing for tinkerability . In Design, make, play: Growing the next generation of STEM innovators, M Honey and D Kanter (Eds.) . Routledge , New York, NY, USA , 163–181. Mitchel Resnick and Eric Rosenbaum. 2013. Designing for tinkerability. In Design, make, play: Growing the next generation of STEM innovators, M Honey and D Kanter (Eds.). Routledge, New York, NY, USA, 163–181.
  28. Donald A. Schön . 1987 . Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. Jossey-Bass, San Francisco, CA , US. Pages : xvii , 355 . Donald A. Schön. 1987. Educating the reflective practitioner: Toward a new design for teaching and learning in the professions. Jossey-Bass, San Francisco, CA, US. Pages: xvii, 355.
  29. Lucy Suchman . 2017. Agencies in Technology Design: Feminist Reconfigurations* . In Machine Ethics and Robot Ethics . Routledge . Num Pages: 15. Lucy Suchman. 2017. Agencies in Technology Design: Feminist Reconfigurations*. In Machine Ethics and Robot Ethics. Routledge. Num Pages: 15.
  30. 10.1145/3313831.3376410 · DOI
  31. 10.1145/2207676.2208417 · DOI
  32. 10.1145/2858036.2858459 · DOI
  33. Ron Wakkary . 2020. A Posthuman Theory for Knowing Design. 14, 3 ( 2020 ), 12. Ron Wakkary. 2020. A Posthuman Theory for Knowing Design. 14, 3 (2020), 12.
  34. Ron Wakkary . 2021. Things We Could Design: For More Than Human-Centered Worlds . MIT Press. Google-Books-ID : UiY6EAAAQBAJ. Ron Wakkary. 2021. Things We Could Design: For More Than Human-Centered Worlds. MIT Press. Google-Books-ID: UiY6EAAAQBAJ.
  35. 10.1145/3192366.3192384 · DOI

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Metadata

Authors
Jonsson, M., & Tholander, J.
Affiliations
  • School of Natural Sciences, Technology and Environmental Studies, Södertörn University, Sweden
  • Department of Computer Systems and Sciences, Stockholm University, Sweden
Venue
Creativity and Cognition
Publisher
ACM
Published
2022-06-20
Pages
5-14
DOI
10.1145/3527927.3532801
Cited by
67
References
4
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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