O'Really?

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

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 as we change from 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 2092?

As the 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.

References

  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
Tags:
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.

References

  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

References

  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.

References

  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.

References

  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

February 22, 2022

Happy Twosday! 22/2/22

Happy Twosday, 22.2.22 or 2.22.22! Picture adapted from a public domain image of the international maritime signal flag for the number two on Wikimedia Commons w.wiki/4sCm

Today is Tuesday, the 22nd day of the 2nd month of the year 2022 . Happy Twosday! Depending on where you live that makes today:

What order do you prefer your date in?

How many digits would you like? YYYY (2022) or just YY (22)? MM or just M? DD (02) or D? Numbers (2) or letters (FEB)? Which time zone are you in? Which separator would you like? Dots, slashes, spaces or emojis? 📅

Has the triviality and boredom of date formatting made you lose the will to live? If it hasn’t then the Wikipedia entry on date format by country will probably finish you off. For me, today has to be 22.2.22, despite the fact it doesn’t follow the very sensible ISO 8601 standard. Why? Because when the clock hits 22 hours, 22 minutes and 22 seconds it will be 22-2-22;22:22:22 in the brand new ISO-my-special-date-format that I just made up exclusively for you today. You’re welcome!

Two is a magic number

To cheer us all up and help us remember our times tables, Jazz musician Bob Dorough once sang that three is a magic number. [1] But two is a magic number. Yes it is, it’s a magic number. Somewhere in that ancient mystic duality, you get two as a magic number. There are three reasons why two is an even more magical number than three:

  1. the number two is both the smallest and the only prime number which is even, so it’s known as the oddest prime. See what they did there?
  2. the number two has spiritual and cultural significance, because duality has two sides. Good and evil. With us or against us. Yin and Yang. Dead or Alive. Female or male. Moscow or Washington. Binary or non-binary etc.
  3. the number two is the base of the binary numeral system and how computers compute everything from what sounds you’re listening to, to what show you’re watching, which words you are reading and which route your car takes.

Talking of binary, there are 10 kinds of people in this world, those who understand binary and those who don’t. So have a magic Twosday 22.2.22, whichever side of the binary divide you are.

References

  1. Bob Dorough (1973) Three is a magic number in Multiplication Rock, Capitol Records (also covered by De La Soul in their 1989 album 3 Feet High and Rising)


February 15, 2022

Where have all the women gone?

Public domain image of Margaret Hamilton standing next to a print out of software that she and her MIT team produced for the Apollo Guidance Computer in 1969 via Wikimedia Commons w.wiki/4mXY

Computing is too important to be left to men, but where have all the women gone? While women continue to play a key role in computing they are currently under-represented in Computer Science. How can we change this and what evidence is there for practices that get more women into computing? We discussed this paper by Briana Morrison et al [1] on Monday 7th February at journal club. Here is the abstract of the paper:

Computing has, for many years, been one of the least demographically diverse STEM fields, particularly in terms of women’s participation. The last decade has seen a proliferation of research exploring new teaching techniques and their effect on the retention of students who have historically been excluded from computing. This research suggests interventions and practices that can affect the inclusiveness of the computer science classroom and potentially improve learning outcomes for all students. But research needs to be translated into practice, and practices need to be taken up in real classrooms. The current paper reports on the results of a focused systematic “state-of-the-art” review of recent empirical studies of teaching practices that have some explicit test of the impact on women in computing. Using the NCWIT Engagement Practices Framework as a means of organisation, we summarise this research, outline the practices that have the most empirical support, and suggest where additional research is needed.

There is lot of stuff in this paper, and we barely scratched the surface. Personally, one of the things I found useful was the National Center for Women in Technology (NCWIT) Engaging Practices Framework which I’d not seen. These have advice on how to make computing a more inclusive subject for all students, not just women. Some of the guidelines include:

  1. Make it matter (e.g. by making interdisciplinary connections and addressing misconceptions)
  2. Build student confidence and professional identity (e.g. by encouraging a growth mindset)
  3. Grow an inclusive community (e.g. by using well-structured collaborative learning and avoiding stereotypes)

The evidence for which approaches work isn’t particularly strong, see Jane Waites lightning talk slides, but there is some evidence to suggest these practices can help to make small steps in the right direction. The evidence is outlined in the paper.

References

  1. Briana B. Morrison, Beth A. Quinn, Steven Bradley, Kevin Buffardi, Brian Harrington, Helen H. Hu, Maria Kallia, Fiona McNeill, Oluwakemi Ola, Miranda Parker, Jennifer Rosato and Jane Waite (2021) Evidence for Teaching Practices that Broaden Participation for Women in Computing in Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education DOI:10.1145/3502870.3506568

December 23, 2021

Join us virtually in Durham to discuss Computing Education Practice (CEP) on 6th Jan 2022

Filed under: education,Uncategorized — Duncan Hull @ 10:40 am
Tags: , ,
Picture of Durham Cathedral by Mattbuck on Wikimedia Commons w.wiki/4acc

The ACM Computing Education Practice (CEP) conference is aimed at practitioners and researchers in computing education, both within Computer Science departments and elsewhere. The conference provides a platform to share and discuss innovations and developments in the practice of computing education. CEP is a community, not just a series of proceedings; everybody is encouraged to participate even if they are not presenting. We have an exciting programme of talks and workshops scheduled which will be of interest to anyone teaching Computer Science including:

  • Narrowing and Stretching: Addressing the Challenges of Multi-track programming by Steven Bradley and Eleni Akrida, Durham University
  • Automated Code Tracing Exercises for CS1 by Sean Russell, University College Dublin
  • Feedback and Engagement on an Introductory Programming Module by Beate Grawemeyer et al Coventry University 
  • Gender parity in peer assessment of team software development projects by Tom Crick et al Swansea University
  • Promoting Engagement in Remote Computing Ethics Education by Joseph Maguire and Steve Draper, University of Glasgow
  • Co-constructing a Community of Practice for Early-Career Computer Science Academics in the UK by Tom Crick et al 
  • Assessing Knowledge and Skills in Forensics with Alternative Assessment Pathways by Joseph Maguire
  • Little Man Computer + Scratch: A recipe to construct a mental model of program execution by Noman Javed, London School of Economics
  • Application of Amazon Web Services within teaching & learning at a UK University by Dan Flood Coventry University

The conference will be held online on Thursday 6th January 2022. More info and registration at cepconference.webspace.durham.ac.uk/programme. We look forward to seeing you there. 

On behalf of the UK ACM Special Interest Group on Computer Science Education (SIGCSE) uki-sigcse.acm.org/about/

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