O'Really?

May 22, 2023

Join us on Zoom to dive into online interactive textbook publishing on Monday 12th June at 2pm BST

Filed under: sigcse — Duncan Hull @ 10:41 am
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CC licensed Scuba diver from flaticon.com

The textbook has long been a mainstay of education. Although online textbooks can give students easy (and sometimes free) access to increasingly interactive resources, authors have a bewildering array of tools and publishing models to select from. The likes of asciidoctor.org, bookdown.org, leanpub.com, pretextbook.org, quarto.org, runestone.academy, zybooks.com, and many others allow instructors to publish course material freed from the constraints of printed paper, monolithic Learning Management Systems (LMSs) and Massive Open Online Courses (MOOCs). Join us on Monday 12th of June at 2pm BST (UTC+1) to discuss a paper describing one example: Dive Into Systems an undergraduate textbook on computer systems. We’ll be joined by one of the co-authors of the paper [1] (and corresponding textbook) Suzanne Matthews, Tia Newhall and Kevin C. Webb from the United States Military Academy at Westpoint, New York and Swarthmore College, Pennsylvania. From the abstract of their paper:

This paper presents our experiences, motivations, and goals for developing Dive into Systems, a new, free, online textbook that introduces computer systems, computer organisation, and parallel computing. Our book’s topic coverage is designed to give readers a gentle and broad introduction to these important topics. It teaches the fundamentals of computer systems and architecture, introduces skills for writing efficient programs, and provides necessary background to prepare students for advanced study in computer systems topics. Our book assumes only a CS1 background of the reader and is designed to be useful to a range of courses as a primary textbook for courses that introduce computer systems topics or as an auxiliary textbook to provide systems background in other courses. Results of an evaluation from students and faculty at 18 institutions who used a beta release of our book show overwhelmingly strong support for its coverage of computer systems topics, its readability, and its availability. Chapters are reviewed and edited by external volunteers from the CS education community. Their feedback, as well as that of student and faculty users, is continuously incorporated into its online content at diveintosystems.org/book

We’ll also be discussing options for adding interactivity to textbooks, see diveintosystems.org/sigcse23. All welcome, as usual, we’ll be meeting on zoom, details at sigcse.cs.manchester.ac.uk/join-us

If there are any papers you’d like to discuss at future journal club meetings, you can nominate them at sigcse.cs.manchester.ac.uk/papers.

References

  1. Suzanne J. Matthews, Tia Newhall and Kevin C. Webb (2021) Dive into Systems: A Free, Online Textbook for Introducing Computer Systems SIGCSE ’21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, Pages 1110–1116 DOI: 10.1145/3408877.3432514

March 27, 2023

Join us to discuss using AI to solve simple programming problems on Monday 3rd April at 2pm BST

Filed under: sigcse — Duncan Hull @ 10:14 am
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CC licensed pilot image from flaticon.com

Maybe you wrote that code and maybe you didn’t. If Artificial Intelligence helped you, such as the OpenAI Codex in GitHub Copilot, how did it solve your problem? How much did AI help or hinder your solution? Join us to discuss a paper by Michel Wermelinger from the Open University published in the SIGCSE technical symposium earlier this month in Toronto on this very topic. [1] We’ll be joined by Michel who will present a lightning talk to kick-off our discussion. Here’s the abstract of his paper:

The teaching and assessment of introductory programming involves writing code that solves a problem described by text. Previous research found that OpenAI’s Codex, a natural language machine learning model trained on billions of lines of code, performs well on many programming problems, often generating correct and readable Python code. GitHub’s version of Codex, Copilot, is freely available to students. This raises pedagogic and academic integrity concerns. Educators need to know what Copilot is capable of, in order to adapt their teaching to AI-powered programming assistants. Previous research evaluated the most performant Codex model quantitatively, e.g. how many problems have at least one correct suggestion that passes all tests. Here I evaluate Copilot instead, to see if and how it differs from Codex, and look qualitatively at the generated suggestions, to understand the limitations of Copilot. I also report on the experience of using Copilot for other activities asked of students in programming courses: explaining code, generating tests and fixing bugs. The paper concludes with a discussion of the implications of the observed capabilities for the teaching of programming.

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

References

  1. Michel Wermelinger (2023) Using GitHub Copilot to Solve Simple Programming Problems in Proceedings of the 54th ACM Technical Symposium on Computer Science Education Pages SIGCSE 2023 page 172–178 DOI: 10.1145/3545945.3569830

February 13, 2023

Join us to discuss code comprehension on Monday 6th March at 2pm GMT

Filed under: sigcse — Duncan Hull @ 8:29 am
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CC licensed puzzle image via flaticon.com

It’s all very well getting an AI to write your code for you but reading code and writing code is not the same as understanding code. So what is going on in novices brains when they learn to actually understand the code they are reading and writing? Join us on Monday 6th March at 2pm GMT to discuss a paper by Quintin Cutts and Maria Kallia from the University of Glasgow on this very topic [1], from the abstract:

An approach to code comprehension in an introductory programming class is presented, drawing on the Text Surface, Functional and Machine aspects of Schulte’s Block Model, and emphasising programming as a modelling activity involving problem and machine domains. To visually connect the domains and a program, a key diagram conceptualising the three aspects lies at the approach’s heart, alongside instructional exposition and exercises, which are all presented. Students find the approach challenging initially, but most recognise its value later, and identify, unexpectedly, the value of the approach for problem decomposition, planning and coding.

We’ll be joined by one of the co-authors (Quintin Cutts), who’ll give us a lightning talk summary of the paper to kick-off our journal club discussion.

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

References

  1. Quintin Cutts and Maria Kallia (2023) Introducing Modelling and Code Comprehension from the First Days of an Introductory Programming Class in CEP ’23: Proceedings of 7th Conference on Computing Education Practice Pages 21–24 DOI:10.1145/3573260.3573266

November 3, 2022

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

Filed under: engineering,sigcse — Duncan Hull @ 10:30 am
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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

References

  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

April 4, 2022

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

Filed under: education,sigcse — Duncan Hull @ 11:46 am
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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

September 17, 2020

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

Filed under: engineering,sigcse,technology — Duncan Hull @ 9:18 am
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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 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.

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

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