Episode #3: Cognitive Load Theory in Computing

This month we’ve decided to focus a whole episode on a single aspect of pedagogy and how it applies to teaching computing. Back in September the National Centre for Computing shared its first Pedagogy Quick Read focused on Cognitive Load Theory. I sat down with Duncan Maidens from the Raspberry Pi Foundation to talk about the importance of considering cognitive load when designing teaching activities.

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Thanks to Duncan Maidens for his contributions to this episode, and a special thanks to Oliver Quinlan for our intro theme built from Commodore 64 sounds.

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Notes

Below, you’ll find notes relating to ideas and reading discussed in the episode, you can also view a full transcript of this episode.

00:21

Download Quick Read #1 and follow our conversation, we also make reference to original research by John Sweller

Sweller, J., 1988. Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), pp.257-285.

Sweller, J., van Merriënboer, J.J. and Paas, F., 2019. Cognitive architecture and instructional design: 20 years later. Educational Psychology Review, pp.1-32.

01:30

Read  more about the Isaac Physics platform and CS accelerator programme which Duncan mentions in his introduction.

05:32

Diagram showing the limitations of working memory

14:18

Read more about the National Centre teaching Resources and try them with your classes.

Objectives graphs are a valuable tool for planning enabling educators to map dependencies between concepts

17:05

Where James says "us as learners", he means "us as educators"

22:51

Dijkstra's algorithm is used to find the shortest path between 2 points in a network.

32:11

Read more about the Worked example effect in our second Quick Read

37:04

You can read more about Pair Programming in quick read #3

43:17

Beyond the Sweller references earlier you can read more in:

Reif, F. (2008) Applying Cognitive Science To Education: Thinking And Learning In Scientific And Other Complex Domains. Cambridge, MIT Press.

Mühling, A. (2016) Aggregating concept map data to investigate the knowledge of beginning CS students. Computer Science Education. 26(3), 176–191.

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