Tag Archives: Sue Sentance

Join us on zoom to discuss the implications of programming getting easier, Monday 15th May at 2pm BST

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Programming is hard, or at least it used to be. AI code generators like Amazon’s CodeWhisperer, DeepMind’s AlphaCode, GitHub’s CoPilot, Replit’s Ghostwriter and many others now make programming easier, at least for some people, some of the time. What opportunities and challenges do these new tools present for educators? Join us on Zoom to discuss an award winning paper by Brett Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather and Eddie Antonio Santos at University College Dublin, the University of Auckland and Abilene Christian University on this very topic. [1] We’ll be joined by two of the co-authors who will present a lightning talk to kick-off our discussion, for our monthly ACM journal club meetup. Here’s the abstract of his paper:

The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation tools present several immediate opportunities and challenges in this domain. In this position paper we argue that the community needs to act quickly in deciding what possible opportunities can and should be leveraged and how, while also working on overcoming otherwise mitigating the possible challenges. Assuming that the effectiveness and proliferation of these tools will continue to progress rapidly, without quick, deliberate, and concerted efforts, educators will lose advantage in helping shape what opportunities come to be, and what challenges will endure. With this paper we aim to seed this discussion within the computing education community.

All welcome, as usual we’ll be meeting on zoom at 2pm BST (UTC+1), details at sigcse.cs.manchester.ac.uk/join-us. Thanks to Sue Sentance at the University of Cambridge for nominating this paper for discussion.

See also linkedin.com/posts/duncanhull_ai-codewhisperer-alphacode-activity-7051921278923915264-7i_5

References

  1. Brett A. Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather, Eddie Antonio Santos (2023) Programming Is Hard – Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation in Proceedings of the 54th ACM Technical Symposium on Computer Science Education: SIGCSE 2023, pages 500–506, DOI: 10.1145/3545945.3569759

Join us to discuss Computing in school in the UK & Ireland on Monday 5th December at 2pm GMT

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Computing is widely taught in schools in the UK and Ireland, but how does the subject vary across primary and secondary education in Scotland, England, Wales and Ireland? Join us to discuss via a paper published at UKICER.com by Sue Sentance, Diana Kirby, Keith Quille, Elizabeth Cole, Tom Crick and Nicola Looker. [1]

Many countries have increased their focus on computing in primary and secondary education in recent years and the UK and Ireland are no exception. The four nations of the UK have distinct and separate education systems, with England, Scotland, Wales, and Northern Ireland offering different national curricula, qualifications, and teacher education opportunities; this is the same for the Republic of Ireland. This paper describes computing education in these five jurisdictions and reports on the results of a survey conducted with computing teachers. A validated instrument was localised and used for this study, with 512 completed responses received from teachers across all five countries The results demonstrate distinct differences in the experiences of the computing teachers surveyed that align with the policy and provision for computing education in the UK and Ireland. This paper increases our understanding of the differences in computing education provision in schools across the UK and Ireland, and will be relevant to all those working to understand policy around computing education in school.

(we’ll be joined by the co-authors of the paper: Sue Sentance and Diana Kirby from the University of Cambridge and the Raspberry Pi Foundation with a lightning talk summary to start our discussion)

All welcome, as usual we’ll be meeting on zoom, details at sigcse.cs.manchester.ac.uk/join-us. Thanks to Joseph Maguire at the University of Glasgow for proposing this months paper.

References

  1. Sue Sentance, Diana Kirby, Keith Quille, Elizabeth Cole, Tom Crick and Nicola Looker (2022) Computing in School in the UK & Ireland: A Comparative Study UKICER ’22: Proceedings of the 2022 Conference on United Kingdom & Ireland Computing Education Research 5 pp 1–7 DOI: 10.1145/3555009.3555015

Join us to discuss learning sciences for computing education on Monday 12th April at 2pm BST

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Learning sciences aims to improve our theoretical understanding of how people learn while computing education investigates with how people learn to compute. Historically, these fields existed independently, although attempts have been made to merge them. Where do these disciplines overlap and how can they be integrated further? Join us to discuss learning sciences for computing education via a paper by Lauren Margulieux, Brian Dorn and Kristin Searle, from the abstract:

This chapter discusses potential and current overlaps between the learning sciences and computing education research in their origins, theory, and methodology. After an introduction to learning sciences, the chapter describes how both learning sciences and computing education research developed as distinct fields from cognitive science. Despite common roots and common goals, the authors argue that the two fields are less integrated than they should be and recommend theories and methodologies from the learning sciences that could be used more widely in computing education research. The chapter selects for discussion one general learning theory from each of cognition (constructivism), instructional design (cognitive apprenticeship), social and environmental features of learning environments (sociocultural theory), and motivation (expectancy-value theory). Then the chapter describes methodology for design-based research to apply and test learning theories in authentic learning environments. The chapter emphasizes the alignment between design-based research and current research practices in computing education. Finally, the chapter discusses the four stages of learning sciences projects. Examples from computing education research are given for each stage to illustrate the shared goals and methods of the two fields and to argue for more integration between them.

There’s a 5 minute summary of the chapter ten minutes into the video below:



All welcome. As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details. Thanks to this months paper suggestions from Sue Sentance and Nicola Looker.

References

  1. Margulieux, Lauren E.; Dorn, Brian; Searle, Kristin A. (2019). “Learning Sciences for Computing Education“: 208–230. doi:10.1017/9781108654555.009. in In S. A. Fincher & A. V. Robins (Eds.) The Cambridge Handbook of Computing Education Research. Cambridge, UK: Cambridge University Press