Join us to discuss why we teach Computing at School (and University) on Monday 7th April at 2pm BST

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Why do we even bother? What (exactly) is the point? In this age of AI why would anyone need to learn about Computing? What value does it add, what skills do students learn and what knowledge do students actually need to develop? Join us on Monday 7th April at 2pm BST (UTC+1) to discuss a paper co-authored by Sue Sentance and published at iticse.acm.org [1]. From the abstract:

K-12 computing education research is a rapidly growing field of research, both driven by and driving the implementation of computing as a school and extra-curricular subject globally. In the context of discipline-based education research, it is a new and emerging field, drawing on areas such as mathematics and science education research for inspiration and theoretical bases. The urgency around investigating effective teaching and learning in computing in school alongside broadening participation has led to much of the field being focused on empirical research. Less attention has been paid to the underlying philosophical assumptions informing the discipline, which might include a critical examination of the rationale for K-12 computing education, its goals and perspectives, and associated inherent values and beliefs. In this working group, we conducted an analysis of the implicit and hidden values, perspectives and goals underpinning computing education at school in order to shed light on the question of what we are talking about when we talk about K-12 computing education. To do this we used a multi-faceted approach to identify implicit rationales for K-12 computing education and examine what these might mean for the implemented curriculum. Methods used include both traditional and natural language processing techniques for examining relevant literature, alongside an examination of the theoretical literature relating to education theory. As a result we identified four traditions for K-12 computing education: algorithmic, design-making, scientific and societal. From this we have developed a framework for the exemplification of these traditions, alongside several potential use cases. We suggest that while this work may provoke some discussion and debate, it will help researchers and others to identify and express the rationales they draw on with respect to computing education.

We’ll be joined by one of the papers co-authors, Sue Sentance from the University of Cambridge.  Sue is Director of the Raspberry Pi Computing Education Research Centre, recipient of the BCS Lovelace medal and an editor of the book Computer Science Education: Perspectives on Teaching and Learning in School published by Bloomsbury Academic. Sue will give us a lightning talk on the paper which is also summarised on the computing education research blog and in the slides from her talk.

All welcome, meeting URL is public at zoom.us/j/96465296256 (meeting ID 9646-5296-256) but the password is private and pinned in the slack channel which you can join by following the instructions at sigcse.cs.manchester.ac.uk/join-us

References

  1. Carsten Schulte, Sue Sentance, Sören Sparmann, Rukiye Altin, Mor Friebroon-Yesharim, Martina Landman, Michael T. Rücker, Spruha Satavlekar, Angela Siegel, Matti Tedre, Laura Tubino, Henriikka Vartiainen, J. Ángel Velázquez-Iturbide, Jane Waite and Zihan Wu (2024) What We Talk About When We Talk About K-12 Computing Education Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE 2024), Pages 226 – 257 DOI:10.1145/3689187.37096

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

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

CC licensed school image via flaticon.com

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

Scientist icon made by Eucalyp flaticon.com

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