O'Really?

January 26, 2021

No need to run and hide, it’s a wonderful, wonderful life

Five years ago today, Colin Vearncombe passed away. While his birth name might not be familiar to many people, his stage name Black and the song Wonderful Life he wrote and performed are much more widely known. Wonderful life achieved commercial success across Europe in 1987.

The music video for Wonderful Life was shot in black and white around the English seaside resort of Southport, Merseyside and Wallasey on the Wirral

This haunting tune caught my again ear recently. The lyrics are particularly appropriate given the pandemic because it’s a sad but strangely comforting song written in a minor key. The refrain “no need to run and hide, it’s a wonderful, wonderful life” is optimistic and contrasts with the otherwise melancholy mood of the song.

Like many other listeners, I took the lyrics at face value and thought they were optimistic until I read a little about the circumstances that inspired the song:

“By the end of 1985 I had been in a couple of car crashes, my mother had a serious illness, I had been dropped by a record company, my first marriage went belly-up and I was homeless. Then I sat down and wrote this song called Wonderful Life. I was being sarcastic.”

Colin Vearncombe quoted in The Irish Times:
Memorial service video celebrating the life of Colin Vearncombe, played at Liverpool Anglican Cathedral, 19th February 2016

As described in the memorial service video above, Colin once dedicated this song to “anyone suffering needlessly in the world right now”.

No need to laugh and cry. It’s a wonderful, wonderful life. Rest in Peace Colin Vearncombe, born 26 May 1962, died 26 January 2016.

References

  1. Barry Roche (2016) Funeral of singer ‘Black’ to take place in County Cork: Liverpool-born ‘Wonderful Life’ singer died after car crash on way to Cork Airport, The Irish Times, irishtimes.com

January 18, 2021

Join us to discuss failure rates in introductory programming courses on 1st Feb at 2pm GMT

Filed under: education — Duncan Hull @ 12:39 pm
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Icons made by freepik from flaticon.com

Following on from our discussion of ungrading, this month we’ll be discussing pass/fail rates in introductory programming courses. [1] Here is the abstract:

Vast numbers of publications in computing education begin with the premise that programming is hard to learn and hard to teach. Many papers note that failure rates in computing courses, and particularly in introductory programming courses, are higher than their institutions would like. Two distinct research projects in 2007 and 2014 concluded that average success rates in introductory programming courses world-wide were in the region of 67%, and a recent replication of the first project found an average pass rate of about 72%. The authors of those studies concluded that there was little evidence that failure rates in introductory programming were concerningly high.

However, there is no absolute scale by which pass or failure rates are measured, so whether a failure rate is concerningly high will depend on what that rate is compared against. As computing is typically considered to be a STEM subject, this paper considers how pass rates for introductory programming courses compare with those for other introductory STEM courses. A comparison of this sort could prove useful in demonstrating whether the pass rates are comparatively low, and if so, how widespread such findings are.

This paper is the report of an ITiCSE working group that gathered information on pass rates from several institutions to determine whether prior results can be confirmed, and conducted a detailed comparison of pass rates in introductory programming courses with pass rates in introductory courses in other STEM disciplines.

The group found that pass rates in introductory programming courses appear to average about 75%; that there is some evidence that they sit at the low end of the range of pass rates in introductory STEM courses; and that pass rates both in introductory programming and in other introductory STEM courses appear to have remained fairly stable over the past five years. All of these findings must be regarded with some caution, for reasons that are explained in the paper. Despite the lack of evidence that pass rates are substantially lower than in other STEM courses, there is still scope to improve the pass rates of introductory programming courses, and future research should continue to investigate ways of improving student learning in introductory programming courses.

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

Thanks to Brett Becker and Joseph Allen for this months #paper-suggestions via our slack channel at uk-acm-sigsce.slack.com.

References

  1. Simon, Andrew Luxton-Reilly, Vangel V. Ajanovski, Eric Fouh, Christabel Gonsalvez, Juho Leinonen, Jack Parkinson, Matthew Poole, Neena Thota (2019) Pass Rates in Introductory Programming and in other STEM Disciplines in ITiCSE-WGR ’19: Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, Pages 53–71 DOI: 10.1145/3344429.3372502

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.

References

  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

References

  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.

References

  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
Tags: , ,
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.

References

  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

References

  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.

References

  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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