O'Really?

November 29, 2022

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

Filed under: education — Duncan Hull @ 9:51 am
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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] From the abstract:

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

March 23, 2021

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

Filed under: Uncategorized — Duncan Hull @ 12:10 pm
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Scientist icon made by Eucalyp via 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

March 4, 2020

Join us to discuss student misconceptions in programming, March 23rd from 1pm to 2pm

Filed under: education,engineering,technology — Duncan Hull @ 10:34 am
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smallerscream

The Scream by Edvard Munch 😱, reproduced in LEGO by Nathan Sawaya, the BrickArtist.com

In Canterbury, Glasgow and Manchester, we’re starting a journal club, as part of uki-sigcse.acm.org, the Association for Computing Machinery (ACM) Special Interest Group (SIG) on Computer Science Education (CSE). Journal clubs are like a book clubs, but instead of chatting about books we discuss journal papers instead. Who should come? What’s on the agenda? How can you join and what are our club rules? Read on…

Who should come?

Our journal club will be of interest to:

  • Educators who teach some flavour of computing or you run a coding boot camp.
  • Employers who employ and train software engineers, data scientists, developers, coders, programmers, etc
  • Employees your boss has sent you on a training program or bootcamp to learn or improve your programming
  • Students what misconceptions about programming have you encountered?
  • Everyone and anyone who is curious. Our doors are open, this is not an ivory tower. Everyone has something to learn, everyone has something to teach.

Agenda: The paper we’ll be discussing

If you’d like to join us, read the paper: Identifying Student Misconceptions of Programming by Lisa Kaczmarczyk et al [1] which was voted a top paper from the last 50 years by SIGCSE members in 2019. Here is a summary:

Computing educators are often baffled by the misconceptions that their CS1 students hold. We need to understand these misconceptions more clearly in order to help students form correct conceptions. This paper describes one stage in the development of a concept inventory for Computing Fundamentals: investigation of student misconceptions in a series of core CS1 topics previously identified as both important and difficult. Formal interviews with students revealed four distinct themes, each containing many interesting misconceptions. Three of those misconceptions are detailed in this paper: two misconceptions about memory models, and data assignment when primitives are declared. Individual misconceptions are related, but vary widely, thus providing excellent material to use in the development of the CI. In addition, CS1 instructors are provided immediate usable material for helping their students understand some difficult introductory concepts.

In case you’re wondering, CS1 refers to the first course in the introductory sequence of a computer science major (in American parlance), roughly equivalent to first year undergraduate in the UK. CI refers to a Concept Inventory, a test designed to tell teachers exactly what students know and don’t know. According to Reinventing Nerds, the paper has been influential because it was the “first to apply rigorous research methods to investigating misconceptions”. After a brief introduction to the paper and its authors we will discuss the following:

  • What is good about the paper?
  • What could be improved?
  • What is the most surprising or interesting thing you got from the paper?
  • How convincing is the evidence, arguments and conclusions presented?
  • How could you use the results and insights in your own teaching or training program?
  • What are the next steps that follow on from this research? What has already been done to follow on from this work?
  • Has consensus and opinion moved since the publication of this paper ten years ago? If so, how and why?
  • Why was this paper voted top 10 of all time by SIGCSE.org members?
  • Are there any elephants in the room? Does the paper omit anything relevant or gloss over important details?
  • What do we know that we know (Rumsfeld’s known knowns)
  • What do we know that we don’t know (Rumsfeld’s known unknowns)
  • A.O.B.: Any other questions or comments?
  • Why was this paper chosen for journal club?
  • What paper should we discuss at our next meeting?

How can you join?

We’ll be meeting in the Atlas rooms, Kilburn building, Department of Computer Science, University of Manchester, M13 9PL, see bit.ly/directions-to-kilburn-building and www.cs.manchester.ac.uk/about/maps-and-travel online using Zoom, find login details and register at sigman1.eventbrite.co.uk.

Can’t make it this time? Groups will be running in parallel in Glasgow (23rd March at 1pm with Quintin Cutts) and Canterbury (Friday 27th March, 14.00, Room S132 in the Cornwallis building, School of Computing with Sally Fincher) to discuss the same paper. You can also join us online using the hashtag #SIGCSEJClub. If you’d like to know about future journal clubs in Manchester send an email to with the text…

subscribe sigcse-journal-club yourfirstname yoursecondname

…in the body of your email.

Start your own local journal club

If Manchester, Glasgow or Canterbury aren’t easy for you to get to, start your own journal club by joining SIGCSE at uki-sigcse.acm.org/membership and posting the details to their mailing list. We plan to have regular journal clubs every three months or so where we’ll discuss the same paper nationally during journal club week: this one is Monday 23rd to Friday 27th March.

 

Journal club rules

We will loosely be following the guidelines at Ten Simple Rules for Running a Journal Club including:

  • It will be casual  not formal. There will be coffee and refreshments available. We won’t be providing lunch but feel free to bring your own. Some companies call them brown bag meetings, because many of us may will only have an hour so we need to get straight down to business.
  • It’s about more than just the articles. We are building (and strengthening) communities of practice amongst peers in Computer Science education, not just inside academia but in industry as well. Don’t be shy, all are welcome!
  • Multidisciplinary is not a dirty word: we aim to foster equality, diversity and inclusion of different people, disciplines, practices and viewpoints. That means we’re open to anyone teaching computer science. That could be in a school, FE college, University, bootcamp, onboarding scheme, company induction or employers staff training program etc. Students are welcome too. The more diverse our journal club is, the stronger it will be.
  • Topics will reflect the diversity of our membership. We’ve started with student misconceptions, but we invite proposals for which paper we should discuss at our next meeting so we can vote on them.
  • We’ll pick interesting papers, but they don’t have to be award winning. Papers don’t need to be heavily cited either, but they do have to be thought provoking and provide something meaty to discuss alongside practical tips that can be put into practice straight away.

Any questions? Let me know in the comments section below, via email or twitter.

You might also like…

If you care about the training & education of software engineers and computer scientists, you might also be interested in #CSEdResearchBookClub which will take place on Thursday 5th March at 8pm. They’ll be discussing a paper by Sue Sentance et al. on using Predict, Run, Investigate, Modify & Make (PRIMM) called Teaching computer programming with PRIMM: a sociocultural perspective. CS education book club is co-ordinated by Jane Waite at Queen Mary University of London (QMUL) see below:

References

  1. Kaczmarczyk, Lisa C.; Petrick, Elizabeth R.; East, J. Philip; Herman, Geoffrey L. (2010). Identifying student misconceptions of programming, SIGCSE ’10: Proceedings of the 41st ACM technical symposium on Computer science education, pages 107–111. doi:10.1145/1734263.1734299

June 23, 2017

Nine ideas for teaching Computing at School from the 2017 CAS conference

Filed under: conferences,education,engineering,informatics,mathematics,NAP,programming,Science,technology — Duncan Hull @ 9:04 am
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CAS

Delegates at the Computing at School conference 2017 #CASConf17 answering diagnostic questions, picture by Miles Berry.

The Computing At School (CAS) conference is an annual event for educators, mostly primary and secondary school teachers from the public and private sector in the UK. Now in its ninth year, it attracts over 300 delegates from across the UK and beyond to the University of Birmingham, see the brochure for details. One of the purposes of the conference is to give teachers new ideas to use in their classrooms to teach Computer Science and Computational Thinking. I went along for my first time (*blushes*) seeking ideas to use in an after school Code Club (ages 7-10) I’ve been running for a few years and also for approaches that undergraduate students in Computer Science (age 20+) at the University of Manchester could use in their final year Computer Science Education projects. So here are nine ideas (in random brain dump order) I’ll be putting to immediate use in clubs, classrooms, labs and lecture theatres:

  1. Linda Liukas demonstrated some intriguing ideas from her children’s books and HelloRuby.com that are based on Montessori education. I shall be trying some of these out (particularly the storytelling stuff) at code club to keep girls involved
  2. Sue Sentance and Neil Brown from King’s College London gave an overview of some current research in pedagogy.  They discussed research questions that can be tackled in the classroom like (for example) do learners make more progress using visual programming languages (like Scratch and Blockly) or traditional text-based languages (like Python and Java etc)? Many of these research questions would make good projects for undergraduate students to investigate in secondary schools, see research on frame based editors, for example.
  3. Michel Wermelinger from the Open University demonstrated using iPython notebooks for teaching data literacy at the Urban Data School. Although I’m familiar with iPython, it had never occurred to me to actually use iPython in school for teaching. It is a no-brainer, when you think about it, even for primary, because you have your code, inputs and outputs all in one window, and can step through code execution instead of (or as well as) using more conventional tools like Trinket, Thonny or IDLE. Data literacy is fun to teach.
  4. Miles Berry from the University of Roehampton demonstrated Diagnostic Questions in Project Quantum. These are a collection of high quality quizzes to use interactively for example as hinge questions, where teaching is adapted depending on answers given, like this multiple choice question: 
    Consider the following Python code:

a = 20
b = 10
a = b

What are the values of a and b?

A: a = 10, b = 10
B: a = 20, b = 20
C: a = 30, b = 10
D: a = 10, b = 20

    You’ll have to try these five questions to check your answer. The useful thing here is that DiagnosticQuestions.com (the platform on which this is built) allows you to see lots of responses, for example each answer (A, B, C or D) above was selected by 25% of participants. You can also view explanations which illuminate common misconceptions (e.g. the classic mistake of confusing assignment with equality) as well as providing a bank of free questions for use in the classroom.

  5. Mark Guzdial from GeorgiaTech discussed using learning sciences to improve computing teaching. He demonstrated predictive questions (e.g. ask students What do you think will happen when we run this code? before actually executing it) alongside what he called subgoal labelling. These are simple ideas (with proven benefits) that can be put to use immediately. I’ll also be trying the Live Coding (with Sonic Pi) and Media Computation he demonstrated asap.
  6. Laurence Rogers demonstrated Insight: Mr. Bit  this looks like a good app for using BBC microbits in the classroom, connected to a range of sensors, provided you’ve got access to iPads.
  7. A copy of Hello World magazine was in the conference bag. The summer 2017 issue has an unusual article from Ian Benson from Kingston University and Jenny Cane describing their use of the Haskell programming language to teach 5-7 year olds to reason symbolically and learn algebra before arithmetic with help from Cuisenaire rods. The Scratch Maths project at University College London are doing similar things, building mathematical knowledge using Scratch, rather than Haskell. These are experimental ideas you could try out on unsuspecting (junior) family members.
  8. Lee Goss from Barefoot Computing, described the free CPD for primary school teachers on offer from BT. I’ve signed up and hope to plug some of the shortcomings in the Code Club Curriculum.
  9. Richard Jarvis demonstrated appJar, a handy Python library for teaching Graphical User Interfaces (GUIs). That’s Jar as in Jarvis and Jam, not JAR as in Java ARchive BTW. I’ve not tried GUIs at code club yet, but appJar looks like a good way to do it.

There were lots more people and projects at the conference not mentioned here including tonnes of workshops. If you’re interested in any of the above, the CAS conference will be back in 2018. Despite the challenging problems faced by Computer Science at GCSE level, it was reassuring and inspiring to meet some members of the vibrant, diverse and friendly community pushing the boundaries of computing in schools across the United Kingdom. Thanks again to everyone at CAS for putting on another great event, I will definitely consider attending next year and maybe you should too.

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