It’s logic, Jim, but not as we know it: Associative networks and parallel processing

By Gordon Rugg

A recurrent theme in our blog articles is the distinction between explicit knowledge, semi-tacit knowledge and tacit knowledge. Another recurrent theme is human error, in various forms. In this article, we’ll look at how these two themes interact with each other, and at the implications for assessing whether or not someone is actually making an error. We’ll also re-examine traditional logic, and judgement and decision-making, and see how they make a different kind of sense in light of types of knowledge and mental processing. We’ll start with the different types of knowledge.

Explicit knowledge is fairly straightforward; it involves topics such as what today’s date is, or what the capital of France is, or what Batman’s sidekick is called. Semi-tacit knowledge is knowledge that you can access, but that doesn’t always come to mind when needed, for various reasons; for instance, when a name is on the tip of your tongue, and you can’t quite recall it, and then suddenly it pops into your head days later when you’re thinking about something else. Tacit knowledge in the strict sense is knowledge that you have in your head, but that you can’t access regardless of how hard you try; for instance, knowledge about most of the grammatical rules of your own language, where you can clearly use those rules at native-speaker proficiency level, but you can’t explicitly say what those rules are. Within each of these three types, there are several sub-types, which we’ve discussed elsewhere.

So why is it that we don’t know what’s going on in our own heads, and does it relate to the problems that human beings have when they try to make logical, rational decisions? This takes us into the mechanisms that the brain uses to tackle different types of task, and into the implications for how people do or should behave, and the implications for assessing human rationality.

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Tacit knowledge: Can’t and won’t

By Gordon Rugg and Sue Gerrard

This is the third post in a short series on semi-tacit and tacit knowledge. The first article gave an overview of the topic, structured round a framework of what people do, don’t, can’t or won’t tell you. The second focused on the various types of do (explicit) and don’t (semi-tacit) knowledge. Here, we look at can’t (strictly tacit) and won’t knowledge.

The issues involved are summed up in the diagram below.

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Explicit and semi-tacit knowledge

By Gordon Rugg and Sue Gerrard

This is the second in a series of posts about explicit, semi-tacit and tacit knowledge.

It’s structured around a four way model of whether people do, don’t, can’t or won’t state the knowledge. If they do state it, it is explicit knowledge, and can be accessed via any method. If people don’t, can’t or won’t state the knowledge, then it is some form of semi-tacit or strictly tacit knowledge, which can only be accessed via a limited set of methods such as observation, laddering or think-aloud.

This is summed up in the image below.

The previous article in this series gave an overview. In the present article, we focus on do and don’t knowledge, i.e. explicit and semi-tacit knowledge.

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Tacit and semi tacit knowledge: Overview

By Gordon Rugg and Sue Gerrard

Tacit knowledge is knowledge which, for whatever reason, is not explicitly stated. The concept of tacit knowledge is widely used, and has been applied to several very different types of knowledge, leading to potential confusion.

In this article, we describe various forms of knowledge that may be described as tacit in the broadest sense; we then discuss the underlying mechanisms involved, and the implications for handling knowledge. The approach we use derives from Gordon’s work with Neil Maiden on software requirements (Maiden & Rugg, 1996; reference at the end of this article).

In brief, the core issue can be summed up as whether people do, don’t, can’t or won’t state the knowledge. If they do state it, it is explicit knowledge, and can be accessed via any method. If people don’t, can’t or won’t state the knowledge, then it is some form of semi-tacit or strictly tacit knowledge, which can only be accessed via a limited set of methods such as observation, laddering or think-aloud. Because of the neurophysiological issues involved, interviews, questionnaires and focus groups are usually unable to access semi-tacit and tacit knowledge.

The image below shows the key issues in a nutshell; the rest of this article unpacks the issues and their implications. There are links at the end of the article to other articles on the methods mentioned in the table. The image below is copyleft; you’re welcome to use it for any non-commercial purpose, including lectures, as long as you retain the coplyleft statement as part of the image.

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What’s so great about live lectures anyway?

By Gordon Rugg

So what’s so great about live lectures anyway, and why do people get so worked up about whether to put lectures online?

Live lectures have some significant advantages over other media; however, these advantages can be difficult to put into words unless you’ve encountered the relevant bodies of research and practice. This can be very frustrating if your employer wants to put everything online for whatever reason, and if they think that anyone who disagrees is simply a lazy Luddite unwilling and unable to change with the times.

There are very real reasons for including face to face lectures, tutorials etc in education and training. However, some important reasons aren’t as widely known as they should be. In this article, I’ll look at these reasons, and then consider the implications for choice of delivery methods in education.

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Games people play, and their implications

By Gordon Rugg

There are regularities in how people behave. There are numerous ways of categorising these regularities, each with assorted advantages and disadvantages.

The approach to categorisation of these regularities that I’ll discuss in this article is Transactional Analysis (TA), developed by Eric Berne and his colleagues. TA is designed to be easily understood by ordinary people, and it prefers to use everyday terms for the regularities it describes.

I find TA fascinating and tantalising. On the plus side, it contains a lot of powerful insights into human behaviour; it contains a lot of clear, rigorous analysis; it has very practical implications. On the negative side, it doesn’t make use of a lot of well-established methods and concepts from other fields that would give it a lot more power. It’s never really taken off, although it has a strong popular following.

An illustrative example of why it’s fallen short of its potential is the name of Berne’s classic book on the topic, Games People Play. When you read the book, the explanation of the name makes perfect sense, and the deadly seriousness of games becomes very apparent. However, if you don’t read the book, and you only look at the title, then it’s easy to assume that the book and the approach it describes are about trivial passtimes, rather than core features of human behaviour.

In this article, I’ll look at some core concepts of Transactional Analysis, and how they give powerful insights into profoundly serious issues in entertainment, in politics, and in science.

The image below shows games at their most deadly serious; Roman gladiatorial combat, where losing could mean death.

By Unknown author – Livius.org, Public Domain, https://commons.wikimedia.org/w/index.php?curid=3479030

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The persistence of old inventions

By Gordon Rugg

Old inventions seldom die; usually, they fade into the background, and then hang around there for a surprisingly long time.

In this article, I’ll look at how this happens with physical inventions; how it happens with innovative ideas; at what is going on underneath the regularities; and at what the implications are. A lot of those implications are important, and counter-intuitive.

I’ll start with pointy sticks.

Image credits are at the end of this article.

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Reflective reports 101

By Gordon Rugg

 

There’s a widespread belief in education that getting students to reflect on their learning is a Good Thing. Whether this is actually true or not is another question, for another time. The key point is that if you’re a student, you might well end up having to write a reflective report.

This experience can be challenging, especially if you’re in a discipline like computing, where you might not have expected anything quite so introspective. It’s particularly challenging if the reflection is about a piece of groupwork, as numerous memes about “What I learned from groupwork” will testify.

Many students under-perform when doing a reflective report. However, if you follow a couple of simple principles, then writing the reflective report becomes a lot easier. As an added bonus, there’s a good chance that you’ll get better marks, and even learn something genuinely useful from the experience.

So, what are these principles, and how do you apply them? They involve systematically describing choices. Here, by way of moral support, is a picture of someone making a choice. You may be reassured to know that the choices you’ll be working with are a lot more encouraging…

By Viktor Mikhailovich Vasnetsov – The knight at the crossroads

https://commons.wikimedia.org/w/index.php?curid=800287

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Presentations 101

By Gordon Rugg

Sooner or later, most students end up having to give a presentation. Most students hate giving presentations, with good reason.

The usual process goes something like this. Well before the date for the presentations, there is a lecture on how to do presentations. This lecture is usually worthy and well meaning, and consists largely of things that you knew already, plus advice like Make the presentation interesting, without telling you just how to do that. The lecture is usually accompanied by links to some of the many resources for doing presentations.

A lot of those resources are excellent in what they cover. However, they’re usually not so great in terms of what they don’t cover, whether because of space and time, or because they assume you already know it, or whatever.

In this article, I’m going to look at those absences. I’ll start with the big picture, then look at how to handle structure and content, and end with the practical stuff that makes the difference between doing it well and doing it not so well. Before I do that, here’s a picture of some hats.

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