Join us to discuss ten things engineers should learn about learning on Monday 5th February at 2pm GMT

See one, do one, teach one” is a popular technique for teaching surgery to medical students. It has three steps:

  • You see one: by watching it, reading about it or listening to it
  • You do one: by engineering it or making it
  • You teach one: by telling others all about it

If you’re teaching engineers, what do you need to know beyond the seeing and doing? Understanding how human memory and learning works and the differences between beginners and experts can improve your teaching. So what practical steps can engineers take to improve the training and development of other engineers? What do engineers need to know in order to improve their own learning?

Join us on Monday 5th February at 2pm GMT (UTC) for our monthly ACM SIGCSE journal club meetup on zoom to discuss a paper on this topic by Neil Brown, Felienne Hermans and Lauren Margulieux, published in (and featured on the cover of) the January issue of Communications of the ACM. [1]

We’ll be joined by the lead author, Neil Brown of King’s College London, who will give us a lightning talk summary of the paper to kick off our discussion.

All welcome, as usual, we’ll be meeting on zoom, details at


  1. Neil C.C. Brown, Felienne F.J. Hermans and Lauren Margulieux (2024) 10 Things Software Developers Should Learn about Learning, Communications of the ACM, Volume 67, No. 1. DOI:10.1145/3584859 (see accompanying video at )

Join us to discuss learning sciences for computing education on Monday 12th April at 2pm BST

Scientist icon made by Eucalyp

Learning sciences aims to improve our theoretical understanding of how people learn while computing education investigates with how people learn to compute. Historically, these fields existed independently, although attempts have been made to merge them. Where do these disciplines overlap and how can they be integrated further? Join us to discuss learning sciences for computing education via a paper by Lauren Margulieux, Brian Dorn and Kristin Searle, from the abstract:

This chapter discusses potential and current overlaps between the learning sciences and computing education research in their origins, theory, and methodology. After an introduction to learning sciences, the chapter describes how both learning sciences and computing education research developed as distinct fields from cognitive science. Despite common roots and common goals, the authors argue that the two fields are less integrated than they should be and recommend theories and methodologies from the learning sciences that could be used more widely in computing education research. The chapter selects for discussion one general learning theory from each of cognition (constructivism), instructional design (cognitive apprenticeship), social and environmental features of learning environments (sociocultural theory), and motivation (expectancy-value theory). Then the chapter describes methodology for design-based research to apply and test learning theories in authentic learning environments. The chapter emphasizes the alignment between design-based research and current research practices in computing education. Finally, the chapter discusses the four stages of learning sciences projects. Examples from computing education research are given for each stage to illustrate the shared goals and methods of the two fields and to argue for more integration between them.

There’s a 5 minute summary of the chapter ten minutes into the video below:

All welcome. As usual, we’ll be meeting on zoom, see for details. Thanks to this months paper suggestions from Sue Sentance and Nicola Looker.


  1. Margulieux, Lauren E.; Dorn, Brian; Searle, Kristin A. (2019). “Learning Sciences for Computing Education“: 208–230. doi:10.1017/9781108654555.009. in In S. A. Fincher & A. V. Robins (Eds.) The Cambridge Handbook of Computing Education Research. Cambridge, UK: Cambridge University Press