November 2, 2020

Join us to discuss why minimal guidance doesn’t work on Monday 2nd November at 2pm GMT

Photo via NESA by Makers on Unsplash

Minimal guidance is a popular approach to teaching and learning. This technique advocates teachers taking a back seat to facilitate learning by letting their students get on with it. Minimal guidance comes in many guises including constructivism, discovery learning, problem-based learning, experiential learning, active learning, inquiry-based learning and even lazy teaching. According to its critics, unguided and minimally guided approaches don’t work. Join us to discuss why via a paper [1] published by Paul KirschnerJohn Sweller and Richard Clark, here is the abstract:

Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide “internal” guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

This is a controversial, heavily cited and politically motivated paper which has provoked numerous rebuttals, making it an ideal candidate for a juicy journal club discussion!

As usual, we’ll be meeting on zoom, see sigcse.cs.manchester.ac.uk/join-us for details and meeting URLs.


  1. Kirschner, Paul A.; Sweller, John; Clark, Richard E. (2006). “Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching”. Educational Psychologist. 41 (2): 75–86. DOI: 10.1207/s15326985ep4102_1

September 17, 2020

Join us to discuss learning git on Monday 5th October at 2pm

The use of git is widespread in software engineering, however many novices struggle to get to grips with its complex distributed information model, challenging command line syntax and leaky abstractions. To investigate these pitfalls, we’ll be talking about a paper published by Santiago Perez De Rosso and Daniel Jackson on Purposes, Concepts, Misfits, and a Redesign of Git at OOPSLA. [1] From the abstract:

Git is a widely used version control system that is powerful but complicated. Its complexity may not be an inevitable consequence of its power but rather evidence of flaws in its design. To explore this hypothesis, we analysed the design of Git using a theory that identifies concepts, purposes, and misfits. Some well-known difficulties with Git are described, and explained as misfits in which underlying concepts fail to meet their intended purpose. Based on this analysis, we designed a reworking of Git (called Gitless) that attempts to remedy these flaws.

To correlate misfits with issues reported by users, we conducted a study of Stack Overflow questions. And to determine whether users experienced fewer complications using Gitless in place of Git, we conducted a small user study. Results suggest our approach can be profitable in identifying, analysing, and fixing design problems.

Details of the zoom meeting have been posted on our slack workspace, see sigcse.cs.manchester.ac.uk/join-us for further information. Thanks to Juha Sorva at Aalto University for recommending this paper. The Git logo by Jason Long at git-scm.com/downloads/logos is licensed under a Creative Commons Attribution 3.0 Unported License.

Journal club dates for your diary

We’ll be meeting on the first Monday of every month throughout autumn, so if you’d like to join us next month or a subsequent month, add these journal club dates to your diary:

  • Monday 5th October at 2pm
  • Monday 2nd November at 2pm
  • Monday 7th December at 2pm


  1. Santiago Perez De Rosso and Daniel Jackson (2016) Purposes, Concepts, Misfits, and a Redesign of Git in Proceedings of the 2016 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications, (OOPSLA), pages 292–310 DOI: 10.1145/2983990.2984018

September 8, 2020

What’s The Story, Coding Glory?

If the Gallagher brothers were software engineers:

“All your dreams are made, when you’re chained to the Jira and the software trade”

Noel Gallagher

Tomorrow never knows what it doesn’t know too soon.


  1. Noel Gallagher (1995) Morning Glory in (What’s The Story) Morning Glory? Creation Records

September 3, 2020

Join us to discuss using theory in Computing Education Research, 7th September at 11am

Filed under: sigcse — Duncan Hull @ 12:56 pm
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cc-licensed image from the thenounproject.com/term/theory/2332503/

Join us on Monday 7th September to discuss using theory in Computing Education Research at 11am. We’ll be talking about a paper [1] by Greg L. Nelson and Amy Ko at the University of Washington:

A primary goal of computing education research is to discover designs that produce better learning of computing. In this pursuit, we have increasingly drawn upon theories from learning science and education research, recognising the potential benefits of optimising our search for better designs by leveraging the predictions of general theories of learning. In this paper, we contribute an argument that theory can also inhibit our community’s search for better designs. We present three inhibitions: 1) our desire to both advance explanatory theory and advance design splits our attention, which prevents us from excelling at both; 2) our emphasis on applying and refining general theories of learning is done at the expense of domain-specific theories of computer science knowledge, and 3) our use of theory as a critical lens in peer review prevents the publication of designs that may accelerate design progress. We present several recommendations for how to improve our use of theory, viewing it as just one of many sources of design insight in pursuit of improving learning of computing.

Details of the zoom meeting will be posted on our slack workspace at uk-acm-sigsce.slack.com. If you don’t have access to the workspace, send me (Duncan Hull) an email to request an invite to join the workspace.


  1. Greg L. Nelson and Andrew Ko (2018) On Use of Theory in Computing Education Research in ICER ’18: Proceedings of the 2018 ACM Conference on International Computing Education Research, August 2018 Pages 31–39 DOI:10.1145/3230977.3230992

July 27, 2020

Join us to discuss how video production affects student engagement Monday 3rd August at 11am

The MOOC! the movie image by Giulia Forsythe image published CC-BY-NC-SA

As Universities transition to online teaching during the global coronavirus pandemic, there’s increasing interest in the use of pre-recorded videos to replace traditional lectures in higher education. Join us to discuss how video production affects student engagement, based on a paper published by Philip Guo at the University of California, San Deigo (UCSD) from the Learning at Scale conference on How video production affects student engagement: an empirical study of MOOC videos. (MOOC stands for Massive Open Online Course). [1] Here is the abstract:

Videos are a widely-used kind of resource for online learning. This paper presents an empirical study of how video production decisions affect student engagement in online educational videos. To our knowledge, ours is the largest-scale study of video engagement to date, using data from 6.9 million video watching sessions across four courses on the edX MOOC platform. We measure engagement by how long students are watching each video, and whether they attempt to answer post-video assessment problems.

Our main findings are that shorter videos are much more engaging, that informal talking-head videos are more engaging, that Khan-style tablet drawings are more engaging, that even high-quality pre-recorded classroom lectures might not make for engaging online videos, and that students engage differently with lecture and tutorial videos.

Based upon these quantitative findings and qualitative insights from interviews with edX staff, we developed a set of recommendations to help instructors and video producers take better advantage of the online video format. Finally, to enable researchers to reproduce and build upon our findings, we have made our anonymized video watching data set and analysis scripts public. To our knowledge, ours is one of the first public data sets on MOOC resource usage.

Details of the zoom meeting will be posted on our slack workspace at uk-acm-sigsce.slack.com. If you don’t have access to the workspace, send me (Duncan Hull) an email to request an invite to join the workspace. The paper refers to several styles of video production, some examples below.

Khan style tablet drawings

The paper refers to Khan style videos, this is an example, taken from Khan Academy course on algorithms, khanacademy.org/computing/computer-science/algorithms

What is an algorithm? Video introduction to Khan Academy algorithms course by Thomas Cormen and Devin Balkcom

Talking Heads

Some examples of “talking head” videos:

How to frame a talking head with Tomás De Matteis

There’s more than one way to do talking head videos, see Moving to Blended Learning, Part 3: Types of Video at www.elearning.fse.manchester.ac.uk/fseta/moving-to-blended-learning-part-3-types-of-video/

Making video-friendly slides

My colleague Steve Pettifer explains how to make video-friendly slides

Lose the words! Your PowerPoint / Keynote presentation should not be a script or a handout


  1. Guo, Philip J.; Kim, Juho; Rubin, Rob (2014). “How video production affects student engagement“. Proceedings of the first ACM conference on Learning @ scale conference: 41–50. doi:10.1145/2556325.2566239.

July 2, 2020

Join us to discuss blended learning & pedagogy in Computer Science on Monday 6th July at 3pm

What is innovative pedagogy? CC licensed image by @giuliaforsythe

Join us for our next journal club meeting on Monday 6th July at 3pm, the papers we’ll be discussing below come from the #paper-suggestions channel of our slack workspace at uk-acm-sigsce.slack.com.

Show me the pedagogy!

The first paper is a short chapter by Katrina Falkner and Judy Sheard which gives an overview of pedagogic approaches including active learning, collaborative learning, cooperative learning, contributing student pedagogy (CSP), blended learning and MOOCs. [1] This was published last year as chapter 15 of the Cambridge Handbook on Computing Education Research edited by Sally Fincher and Anthony V. Robins. A lot of blended learning resources focus on technology, this chapter talks about where blended learning fits with a range of different pedagogic approaches.

A video summary of all sixteen chapters of the Cambridge Handbook of Computing Education Research, including chapter 15 which we’ll be discussing

Implementing blended learning

The second paper (suggested by Jane Waite) is Design and implementation factors in blended synchronous learning environments [2], here’s a summary from the abstract:

Increasingly, universities are using technology to provide students with more flexible modes of participation. This article presents a cross-case analysis of blended synchronous learning environments—contexts where remote students participated in face-to-face classes through the use of rich-media synchronous technologies such as video conferencing, web conferencing, and virtual worlds. The study examined how design and implementation factors influenced student learning activity and perceived learning outcomes, drawing on a synthesis of student, teacher, and researcher observations collected before, during, and after blended synchronous learning lessons. Key findings include the importance of designing for active learning, the need to select and utilise technologies appropriately to meet communicative requirements, varying degrees of co-presence depending on technological and human factors, and heightened cognitive load. Pedagogical, technological, and logistical implications are presented in the form of a Blended Synchronous Learning Design Framework that is grounded in the results of the study.

Hope to see you there, zoom details are on the slack channel, email me if you’d like to request an invitation to the slack channel. Likewise, if you don’t have access to the papers let me know.


  1.  Falkner, Katrina; Sheard, Judy (2019). “Pedagogic Approaches”: 445–480. doi:10.1017/9781108654555.016. Chapter 15 of the The Cambridge Handbook of Computing Education Research
  2. Bower, Matt; Dalgarno, Barney; Kennedy, Gregor E.; Lee, Mark J.W.; Kenney, Jacqueline (2015). “Design and implementation factors in blended synchronous learning environments: Outcomes from a cross-case analysis”. Computers & Education86: 1–17. doi:10.1016/j.compedu.2015.03.006ISSN 0360-1315.

May 26, 2020

Join us to discuss blended learning, Monday 1st June at 11am on Zoom

Filed under: education,Uncategorized — Duncan Hull @ 2:41 pm
Tags: ,

7704609288_14d335dd87_cAt our next journal club, on Monday 1st June at 11am, we’ll be discussing blended learning. We’ve picked a subject, but we haven’t picked a paper yet. So, if you know interesting papers on blended learning, post them to the “paper suggestions” channel at  uk-acm-sigsce.slack.com – there are a few suggestions up there already for starters.

If you’ve not got access to the workspace yet, ping me or Alcywn Parker and we’ll add you to the group. Journal Club is part of the Association for Computing Machinery (ACM) Special Interest Group (SIG) on Computer Science Education (CSE) – all welcome!

May 22, 2020

Congratulations and thank you Jess Wade for 1000 new biographies @Wikipedia 🏆

Filed under: Uncategorized — Duncan Hull @ 10:01 am

Wiki Loves Scientists

Jess_Wade_-_2017_(cropped) Jess Wade, editor extraordinaire, in 2017. Portrait by Dave Guttridge via Wikimedia Commons CC BY-SA

Today Jess Wade published her one thousandth new Wikipedia article, a wiki-biography of Sylvie Briand. This biography joins 999 others Jess has written at a rate of one per day since September 2017. All of these articles have been about people from under represented groups, with a particular focus on women in Science, Technology, Engineering and Mathematics (STEM). Passing the 1k milestone is a fantastic achievement in its own right, but also something we should all be grateful for because:

  1. She has significantly improved Wikipedia. Wikipedia is undoubtedly one of the Seven Wonders of the World Wide Web but it also has well known limitations. The gender of editors on Wikipedia is notoriously unbalanced and coverage of many people and topics is incomplete or non-existent. For example, according to the Wikidata Human…

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April 28, 2020

Join us to discuss learning programming languages: Monday 4th May at 11am #sigcsejclub

Filed under: education,engineering,Uncategorized — Duncan Hull @ 10:17 am
Tags: , , , ,


Hieroglyphs from the tomb of Seti I, by Jon Bodsworth via Wikimedia Commons and the Egypt archive

ACM SIGCSE Journal Club returns Monday 4th May at 11am. The paper we’re discussing this month is “Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages” by Chantel Prat et al published in Scientific Reports. [1] Here’s the abstract:

This experiment employed an individual differences approach to test the hypothesis that learning modern programming languages resembles second “natural” language learning in adulthood. Behavioral and neural (resting-state EEG) indices of language aptitude were used along with numeracy and fluid cognitive measures (e.g., fluid reasoning, working memory, inhibitory control) as predictors. Rate of learning, programming accuracy, and post-test declarative knowledge were used as outcome measures in 36 individuals who participated in ten 45-minute Python training sessions. The resulting models explained 50–72% of the variance in learning outcomes, with language aptitude measures explaining significant variance in each outcome even when the other factors competed for variance. Across outcome variables, fluid reasoning and working-memory capacity explained 34% of the variance, followed by language aptitude (17%), resting-state EEG power in beta and low-gamma bands (10%), and numeracy (2%). These results provide a novel framework for understanding programming aptitude, suggesting that the importance of numeracy may be overestimated in modern programming education environments.

The paper describes an experiment which investigates the relationship between learning natural languages and programming languages and draws some interesting conclusions that provide some good discussion points. Does being good at learning natural languages like English make you good at learning programming language like Python? Do linguists make good coders? We’ll be meeting on Zoom, details will be sent to anyone who registers at sigman2.eventbrite.co.uk


  1. Prat, C.S., Madhyastha, T.M., Mottarella, M.J. et al. (2020) Relating Natural Language Aptitude to Individual Differences in Learning Programming Languages. Scientific Reports 10, 3817 (2020). DOI:10.1038/s41598-020-60661-8


March 4, 2020

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


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:


  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 educationages 107–111doi:10.1145/1734263.1734299
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