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
Tags: , , , , , ,

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.


  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

November 3, 2022

Join us to discuss novice use of Java on Monday 7th November at 2pm GMT

Java is widely used as a teaching language in Universities around the world, but what wider problems does it present for novice programmers? Join us to discuss via a paper published in TOCE by Neil Brown, Pierre Weill-Tessier, Maksymilian Sekula, Alexandra-Lucia Costache and Michael Kölling. [1] From the abstract:

Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices, and most studies look only at the types or frequency of errors. In this observational study we aim to learn how novices use different features of the Java language. Participants: Users of the BlueJ development environment have been invited to opt-in to anonymously record their activity data for the past eight years. This dataset is called Blackbox, which was used as the basis for this study. BlueJ users are mostly novice programmers, predominantly male, with a median age of 16. Our data subset featured approximately 225,000 participants from around the world. Study Methods: We performed a secondary data analysis that used data from the Blackbox dataset. We examined over 320,000 Java projects collected over the course of eight years, and used source code analysis to investigate the prevalence of various specifically-selected Java programming usage patterns. As this was an observational study without specific hypotheses, we did not use significance tests; instead we present the results themselves with commentary, having applied seasonal trend decomposition to the data. Findings: We found many long-term trends in the data over the course of the eight years, most of which were monotonic. There was a notable reduction in the use of the main method (common in Java but unnecessary in BlueJ), and a general reduction in the complexity of the projects. We find that there are only a small number of frequently used types: int, String, double and boolean, but also a wide range of other infrequently used types. Conclusions: We find that programming usage patterns gradually change over a long period of time (a period where the Java language was not seeing major changes), once seasonal patterns are accounted for. Any changes are likely driven by instructors and the changing demographics of programming novices. The novices use a relatively restricted subset of Java, which implies that designers of languages specifically targeted at novices can satisfy their needs with a smaller set of language constructs and features. We provide detailed recommendations for the designers of educational programming languages and supporting development tools.

All welcome, as usual we’ll be meeting on zoom, details at sigcse.cs.manchester.ac.uk/join-us


  1. Neil C. C. Brown, Pierre Weill-Tessier, Maksymilian Sekula, Alexandra-Lucia Costache and Michael Kölling (2022) Novice use of the Java programming language ACM Transactions on Computing Education DOI:10.1145/3551393

November 1, 2022

The wildness and freedom of using natural language with joy and pleasure

Filed under: education,engineering,mathematics,Science — Duncan Hull @ 9:32 am
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Public domain portrait of Stephen Fry by the US Embassy in London on Wikimedia Commons w.wiki/4wrn

It’s easy to undervalue the importance of natural languages like English because we use them everyday. Scientists and engineers can be particularly bad at this, often overlooking the importance of written and spoken language. It probably doesn’t help that in the UK, and many other countries, many students choose either an exclusively scientific-mathematical path OR an arty-humanities path through their education, especially in the latter stages. This means that the two cultures of humanities and science are thriving, but still living in separate houses like an estranged and bickering couple. In the worst case scenario, two cultures in society produces graduate scientists and engineers with weaker communication and literacy, and articulate humanities graduates with weaker technical & numeracy skills.

Over on BBC4, Alan Yentob is having conversations with prominent artistes. [1] The first episode in the series is with writer, presenter, comedian and actor Stephen Fry. As a self-confessed Fry-fanboi, I enjoyed his description of the joy of using language:

YENTOB: Why do you need all that stuff?

FRY: I think what underlies 90%, if not more, is language, is a real profound love and excitement at the process of putting one word after another and what happens when you do it.

Not just the meanings that are conveyed and the moods you can create with language, but even the text of it, the tip of the tongue hitting the back of the teeth, the rhythm, the swing, the swoop, the flow, the joy, the sound and sex of language. People have that with music. We all have it with music. Music is often described as being beyond language, and indeed it is and I’m the first to say how profound I think music is.

But everybody has language, and yet almost nobody has such a realisation of what a beautiful thing it can be. I mean one of the thrills that’s happened in music in the last 20 or so years, I suppose, is rap and hip-hop and poetry slamming and things like that because then it’s taken away from the normal people who are people like me, who, as it were, have an educated sense of language and its returned to where language belongs.

And so the wildness and freedom of using language with joy and pleasure and realising we’re all the equivalent of grade eight musicians, or painters, only with language.


  1. Janet Lee and David Shulman (2022) In Conversation with Alan Yentob: Stephen Fry bbc.co.uk/programmes/m001dh8p

September 19, 2022

Mind the gap at the end of the Elizabethan line

Elizabeth Line roundel by Transport for London via Wikimedia Commons w.wiki/5iib

So we’ve finally reached the end of the Elizabethan line. Not the the CrossRail route that straddles London but the seventy year reign of Elizabeth II from 1952 to 2022. Like many, I have mixed feelings about our monarch and monarchy but the history of the last seventy years should fascinate republicans, royalists and anarchists alike. So here are some historical facts about the start of the Elizabethan line for your amusement:

  • 🇬🇧 In 1952 Princess Elizabeth Alexandra Mary of York became Queen Elizabeth II en.wikipedia.org/wiki/Elizabeth_II
  • 🇪🇺 In 1952 The European Economic Community (EEC), precursor to the European Union (EU), did not exist. That came five years later in 1957, see en.wikipedia.org/wiki/European_Economic_Community
  • 🏳️‍🌈 In 1952 Alan Turing was working on two new areas of research he’d recently pioneered called “Computer Science” and “Artificial Intelligence” (AI). The very same year Turing was prosecuted for being homosexual which was shamefully labelled “gross indecency” and illegal at that time. He tragically committed suicide two years later in 1954 after being chemically castrated by the government of the UK. Her Majesty’s Government was led at the time by some bloke called Winston Churchill, see en.wikipedia.org/wiki/Gross_indecency
  • 🇺🇸 In 1952 The England National Football Team were recovering from their debut appearance in a FIFA World Cup two years previously. In a pattern that is now familiar, England failed to make it through to the final stages of the 1950 tournament in Brazil after beating Chile but losing to both Spain and the United States, see en.wikipedia.org/wiki/United_States_v_England_(1950_FIFA_World_Cup)
  • 🎼 In 1952 Alan Turing and Christopher Strachey had recently finished experimenting with creating the worlds first computer generated music, to accompany the worlds first computer game (draughts aka checkers), you can listen to the music they made (a tune you may have heard of called God Save The King) on a Ferranti Mark I computer in Manchester at blogs.bl.uk/sound-and-vision/2016/09/restoring-the-first-recording-of-computer-music.html
  • ⚛ In 1952, Geneva was selected as the site for the Organisation Européenne pour la Recherche Nucléaire (CERN), the vast network of underground tunnels and machines that can be found there now were just an idea seventy years ago see home.cern/about/who-we-are/our-history

It’s easy to view the events of the 1950s as ancient history and evidence of how far we have travelled down the Elizabethan line. However in 1952, when Elizabeth was 26 years old, her son Charles was 4 years old, Alan Turing was 40 and Winston Churchill was 78. So the history is not that ancient, especially if you’re an octogenarian or a nonagenarian.

Yes it is a long time ago, but it is almost within living memory. Almost.

Mind the Gaps

What a remarkable seventy years of history, so much has happened in a relatively short period of time. At the end of the journey, it feels like there’s a big gap at the end of the Elizabethan line as we search for our connection and onward destination. Not just one gap but lots of gaps:

  • The gaps between wealthy elites and everybody else
  • The gaps between those educated privately (including the royal family) and the other 93%
  • The gaps between London at the rest of the United Kingdom
  • The gaps between the UK and the rest of the world
  • The gaps between expectations and reality
  • The gaps between historical memories and the present day
  • The gaps between the Elizabethan line and the Carolean line

I wonder where we will be after another gap of seventy years, if the human race is here at all in the year 2092?

As the station announcers often warn as you disembark on the London Underground, mind the gap.

July 28, 2022

What’s your story, coding glory?

Filed under: engineering — Duncan Hull @ 11:21 am
Tags: , , , , ,
Congratulations to all this years graduates!

Last week we celebrated graduation, its been the first proper graduation since before the pandemic. A lot proverbial water has passed very quickly under our proverbial bridge since this years graduates starting studying back in 2018/19. What obstacles have they faced during their study and placements and how have they overcome them? Where are they going next? What’s their story? I interviewed five of this years graduands and previous years graduates to find out. Hear from some of our students including:

  • Sneha Kandane, she’s returning Matillion where she did her industrial placement cdyf.me/sneha
  • Carmen who did an internship at McKinsey and a placement at The Walt Disney Company cdyf.me/carmen
  • Brian Yim Tam who did a placement at Disney Streaming here in Manchester cdyf.me/brian
  • Raluca Cruceru who did a placement at CERN where she now works as a software engineer cdyf.me/raluca
  • Jason Ozuzu who did a placement at Morgan Stanley, an internship at FitBit and is joining Google in London cdyf.me/jason

Listen online at Coding your Future or subscribe wherever you get your podcasts cdyf.me/hearing#subscribing

Congratulations to all this years graduates, it was lovely to celebrate your achievements despite the considerable challenges you’ve faced during the last three of four years. Thanks to Sneha, Carmen, Brian, Raluca and Jason for sharing your stories too.

July 4, 2022

Join us to discuss the implications of the Open AI codex on introductory programming Monday 4th July at 2pm BST

Automatic code generators have been with us a while, but how do modern AI powered bots perform on introductory programming assignments? Join us to discuss the implications of the OpenAI Codex on introductory programming courses on Monday 4th July at 2pm BST. We’ll be discussing a paper by James Finnie-Ansley, Paul Denny, Brett A. Becker, Andrew Luxton-Reilly and James Prather [1] for our monthly SIGCSE journal club meetup on zoom. Here is the abstract:

Recent advances in artificial intelligence have been driven by an exponential growth in digitised data. Natural language processing, in particular, has been transformed by machine learning models such as OpenAI’s GPT-3 which generates human-like text so realistic that its developers have warned of the dangers of its misuse. In recent months OpenAI released Codex, a new deep learning model trained on Python code from more than 50 million GitHub repositories. Provided with a natural language description of a programming problem as input, Codex generates solution code as output. It can also explain (in English) input code, translate code between programming languages, and more. In this work, we explore how Codex performs on typical introductory programming problems. We report its performance on real questions taken from introductory programming exams and compare it to results from students who took these same exams under normal conditions, demonstrating that Codex outscores most students. We then explore how Codex handles subtle variations in problem wording using several published variants of the well-known “Rainfall Problem” along with one unpublished variant we have used in our teaching. We find the model passes many test cases for all variants. We also explore how much variation there is in the Codex generated solutions, observing that an identical input prompt frequently leads to very different solutions in terms of algorithmic approach and code length. Finally, we discuss the implications that such technology will have for computing education as it continues to evolve, including both challenges and opportunities. (see accompanying slides)

All welcome, details at sigcse.cs.manchester.ac.uk/join-us. Thanks to Jim Paterson at Glasgow Caledonian University for nominating this months paper.


  1. James Finnie-Ansley, Paul Denny, Brett A. Becker, Andrew Luxton-Reilly, James Prather (2022) The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming ACE ’22: Australasian Computing Education Conference Pages 10–19 DOI:10.1145/3511861.3511863

May 25, 2022

Join us to discuss teaching programming to Physics students on Monday 13th June at 2pm BST

Filed under: education — Duncan Hull @ 10:14 am
CC BY-SA image of Bohr model of the atom by Jabberwock on Wikimedia Commons w.wiki/59id 

print(’Hello World!’) is all very well but it doesn’t help physics students solve the Schrödinger equation. Join us for our next journal club meeting on Monday 13th June at 2pm BST where we’ll be discussing a paper by Lloyd Cawthorne on teaching programming to undergraduate Physics students. From the abstract:

Computer programming is a key component of any physical science or engineering degree and is a skill sought by employers. Coding can be very appealing to these students as it is logical and another setting where they can solve problems. However, many students can often be reluctant to engage with the material as it might not interest them or they might not see how it applies to their wider study. Here, I present lessons I have learned and recommendations to increase participation in programming courses for students majoring in the physical sciences or engineering. The discussion and examples are taken from my second-year core undergraduate physics module, Introduction to Programming for Physicists, taught at The University of Manchester, UK. Teaching this course, I have developed successful solutions that can be applied to undergraduate STEM courses.

All welcome. As usual we’ll be meeting on zoom, details are in the slack channel sigcse.cs.manchester.ac.uk/join-us.


  1. Lloyd Cawthorne (2021) Invited viewpoint: teaching programming to students in physical sciences and engineering, Journal of Materials Science 56, pages 16183–16194 DOI:10.1007/s10853-021-06368-1

April 4, 2022

Join us to discuss spatial skills in engineering on Monday 9th May at 2pm BST

CC BY-SA licensed image of a Rubik’s cube via by Booyabazooka Wikimedia Commons w.wiki/He9

Spatial skills can be beneficial in engineering and computing, but what are they and why are they useful? Join us to discuss this via a paper on spatial skills training by Jack Parkinson and friends at the University of Glasgow. Here is the abstract:

We have been training spatial skills for Computing Science students over several years with positive results, both in terms of the students’ spatial skills and their CS outcomes. The delivery and structure of the training has been modified over time and carried out at several institutions, resulting in variations across each intervention. This article describes six distinct case studies of training deliveries, highlighting the main challenges faced and some important takeaways. Our goal is to provide useful guidance based on our varied experience for any practitioner considering the adoption of spatial skills training for their students.

see [1]

All welcome. As usual we’ll be meeting on zoom, details are in the slack channel sigcse.cs.manchester.ac.uk/join-us. Thanks to Steven Bradley for suggesting the paper


  1. Jack Parkinson, Ryan Bockmon, Quintin Cutts, Michael Liut, Andrew Petersen and Sheryl Sorby (2021) Practice report: six studies of spatial skills training in introductory computer science, ACM Inroads Volume 12, issue 4, pp 18–29 DOI: 10.1145/3494574

March 7, 2022

Join us to discuss the feeling of learning ❤️ (vs. actual learning) on Monday 4th April at 2pm BST

Filed under: Uncategorized — Duncan Hull @ 4:08 pm

Learning can be an emotional process and we often don’t realise when we are actually learning. When you’re listening to an expert explain something well, it’s easy to mistake the speaker’s smooth delivery for your own understanding. You might feel like you’re learning, but actual learning is often hard work and feels uncomfortable. Join us to discuss actual learning vs. feeling of learning via a paper by Louis Deslauriers, Logan S. McCarty, Kelly Miller, Kristina Callaghan, and Greg Kestin at Harvard University here is the abstract:

We compared students’ self-reported perception of learning with their actual learning under controlled conditions in large-enrollment introductory college physics courses taught using 1) active instruction (following best practices in the discipline) and 2) passive instruction (lectures by experienced and highly rated instructors). Both groups received identical class content and handouts, students were randomly assigned, and the instructor made no effort to persuade students of the benefit of either method. Students in active classrooms learned more (as would be expected based on prior research), but their perception of learning, while positive, was lower than that of their peers in passive environments. This suggests that attempts to evaluate instruction based on students’ perceptions of learning could inadvertently promote inferior (passive) pedagogical methods. For instance, a superstar lecturer could create such a positive feeling of learning that students would choose those lectures over active learning. Most importantly, these results suggest that when students experience the increased cognitive effort associated with active learning, they initially take that effort to signify poorer learning. That disconnect may have a detrimental effect on students’ motivation, engagement, and ability to self-regulate their own learning. Although students can, on their own, discover the increased value of being actively engaged during a semester-long course, their learning may be impaired during the initial part of the course. We discuss strategies that instructors can use, early in the semester, to improve students’ response to being actively engaged in the classroom..

see [1]

Thanks to Uli Sattler and Andrea Schalk for highlighting the paper. All welcome. As usual we’ll be meeting on zoom, details are in the slack channel sigcse.cs.manchester.ac.uk/join-us.


  1. Logan S. McCarty; Kelly Miller; Kristina Callaghan; Greg Kestin (2019) “Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom”Proceedings of the National Academy of Sciences of the United States of America: 201821936. DOI:10.1073/PNAS.1821936116 PMC: 6765278 PMID: 31484770
  2. Jill Barshay (2022) College students often don’t know when they’re learning: Harvard experiment reveals the psychological grip of lectures, The Hechinger Report

March 1, 2022

Join us to discuss conversational programming on Monday 7th March at 2pm GMT

Between the traditional division of non-programmers and programmers, there is a third category of conversational programmers. These are people who learn programming so that they can speak in the “programmer’s language” in order to collaborate better with software engineers. Join us to discuss conversational programming via paper by Katie Cunningham et al. [1] This won a best paper award at SIGCSE 2022:

As the number of conversational programmers grows, computing educators are increasingly tasked with a paradox: to teach programming to people who want to communicate effectively about the internals of software, but not write code themselves. Designing instruction for conversational programmers is particularly challenging because their learning goals are not well understood, and few strategies exist for teaching to their needs. To address these gaps, we analyse the research on programming learning goals of conversational programmers from survey and interview studies of this population. We identify a major theme from these learners’ goals: they often involve making connections between code’s real-world purpose and various internal elements of software. To better understand the knowledge and skills conversational programmers require, we apply the Structure Behaviour Function framework to compare their learning goals to those of aspiring professional developers. Finally, we argue that instructional strategies for conversational programmers require a focus on high-level program behaviour that is not typically supported in introductory programming courses.

See [1] below

All welcome. As usual we’ll be meeting on zoom, details are in the slack channel sigcse.cs.manchester.ac.uk/join-us.


  1. Kathryn Cunningham, Yike Qiao, Alex Feng and Eleanor O’Rourke (2022) Bringing “High-level” Down to Earth: Gaining Clarity in Conversational Programmer Learning Goals in SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education, Pages 551–557 DOI:10.1145/3478431.3499370
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