This is the 100th post on the Hyde & Rugg blog. We’re taking this opportunity to look back at what we’ve covered and look forward to what comes next.
The image below shows some of the main themes and outputs so far, in the “knowledge cycle” format that underlies our Verifier framework for tackling human error. If you’ve come to this blog after reading Blind Spot, you might be pleased to discover that we’ve been covering the contents of Verifier here in more depth than was possible in the book, and that we’re well on the way to a full description.
In the image below you can see some of the main themes and topics we’ve covered so far in the “knowledge cycle” format that underlies our Verifier framework for tackling human error. If you’ve come to this blog after reading Blind Spot, it’s worth knowing that we’ve covered some of the the contents of Verifier in more depth here than was possible in the book, and that we’re well on the way to a full description.
The knowledge cycle, and topics that we’ve blogged about
That article was a broad overview. This article shows a worked example of how the framework operates for one category from the framework, namely compiled skills.
Image copyleft Hyde & Rugg, 2014
Compiled skills are a type of strictly tacit knowledge that have traditionally been viewed in the education world as something of a black box. They are particularly problematic for some views of education because their performance is usually adversely affected, or completely disrupted, by any attempt to verbalise them. For any sport enthusiast, they are a familiar phenomenon, usually under the name of “the flow” or of “muscle memory”.
This article unpacks the nature of compiled skills, and examines the implications for education theory and practice.
Education is about getting new content into student’s heads, via some combination of teaching and learning.
In order to do this in an evidence-based way, one key element is a solid categorisation framework for each of the variables involved. Three key variables are:
Types of content
Types of delivery
Types of learning
There are other important variables, such as physiological constraints, but we’ll focus for the moment on the three listed above.
Existing educational categorisations, such as the Visual/Auditory/Kinaesthetic model, tend to be unsystematic and/or very coarse-grained. In order to handle this area properly, a category system should as a minimum be able to handle systematically the types of content and of delivery and learning shown in the diagram below, and preferably be able to handle more.
This article is a brief overview of how we have been tackling this issue. We will go into more detail in later articles.