O'Really?

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

February 15, 2022

Where have all the women gone?

Filed under: education,engineering,technology — Duncan Hull @ 2:12 pm
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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

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