The Wyvern Integrated Master Plan (WIMP)

After a five-year study of the curriculum being taught at the Citadel of the Wyverns, the following points were clearly supported by a conservative interpretation of the evidence.

1. Content. There is nothing new under the sun. Except perhaps that the old GEP curriculum has been a) extended, and b) diluted. The original IP has been drowned in the blood of innocents. Content has been altered slightly, but the textbooks are 95% identical to the kind used in non-IP institutions.

2. Methodology. Same old teaching methods. No power, no point. A few more radical people teaching in unusual ways, which is to be expected since the staff was doubled in size. In fact, they seem to have become even more boring, overall.

3. Results. Well within the expected outcomes for a random cohort at the percentile intake. There is no significant value added.

4. Conclusion. They spent all that money on what, exactly?

Responses 002 (2011-2012)

Looking at the new list began to be interesting in a whole new way with Question 2: "Compare and contrast knowledge which can be expressed in words/symbols with knowledge that cannot be expressed in this way. Consider CAS and one or more areas of knowledge."

It's the first question I've seen that would be partly incomprehensible except to a student of the International Baccalaureate Diploma Programme. That's because it has the term 'CAS' in it — an acronym for 'Creativity, Action, Service'. This core element of the Diploma is supposed to act as a counterbalance to academic work, and consists largely of activities one might think of as 'experiential learning'.

And that immediately supplies us with one possible key. To participate in CAS is to design a course of study for yourself, but one which acts as a counterpoint to traditional academic studies — all of which consist largely of knowledge expressed and assessed by words/symbols. Evaluation in CAS consists of documenting your reflections on what you have done and how that has affected your outlook and perception of life; it's more about knowledge that can be described but not expressed fully without going through similar experiences.

That's not to say that none of it can be expressed in words and symbols. If you've learnt how to make pots or have been digging latrines in Peru, the physical and material aspects can be communicated — e.g. 'How to Dig a Latrine in 5 Easy Steps', or 'How to Make a Basic Pot' — in words and diagrams. But what you've learnt about cameraderie, teamwork and working in an alien environment — these are much less easy to convey.

This is a difficult question, though, because of at least one philosophical position. If your brain is a machine, then its inputs and outputs can theoretically be completely described in words and symbols. All your sensory perceptions, emotional changes, communication abilities and reasoning processes can be converted to symbolic form. It's a big 'if', but a discussion of its 'iffiness' is crucial to the discussion of this question.

So... what exactly is knowledge that CANNOT be expressed in words or symbols? Is there such a thing? Or does it only exist in a way because some people are just not articulate enough to express their knowledge by such means? A famous researcher is rumoured to have said, "There is no such thing as qualitative research, just quantitative research that hasn't been adequately defined." Ho ho.

Qualitative and Quantitative

Recently, I've had to speak with various students on the subject of what 'qualitative' and 'quantitative' mean, in the sense of qualitative or quantitative data or research methodology. It's interesting how oversimplication (the subject of my previous post) creeps in.

For instance, one of them said, "Quantitative means you can put a number on it."

I replied, "Well, you can put a number on a marathon runner and it doesn't make her quantitative data. You can have a school survey with ratings on items (a 'Likert scale') from 1 to 5, and that doesn't make it quantitative research either."

Quantitative data is actually data that can be gathered and placed within a scale of measurement, and can legitimately be subjected to mathematical operations. Sometimes this definition works to confuse people.

Take for example the idea of 'an average age'. Suppose that we ask your class how old they are in years (number of birthdays passed), and your class replies "17!" (40%) and "18!" (60%). Does this mean that the average age of the class is (0.4 x 17 + 0.6 x 18) = 17.6? That would make the average member of the class roughly 17 years, 7 months and 6 days old. What do you think? I suspect not. But the problem here is one of insufficient resolution and definition, not one of illegitimacy. Age can indeed be used as quantitative data in some contexts.

Qualitative data is actually data that specifies a kind or a class of property without being subject to scalar manipulation. It cannot be subjected legitimately to mathematical operation, although it is possible to try. This also confuses people.

Take for example the idea of 'colour'. Suppose we ask your class what their favourite colours are, and your class replies "Blue!" (50%) and "Gold!" (50%). Does this mean that the average favourite colour is metallic green? What do you think? I suspect not. The problem here is not numerical, but conceptual. You can't find an 'average' of favourite colours, since the average is unlikely to be anybody's favourite in this context.

The thing about this colour example is that it can be treated both quantitatively and qualitatively, with different kinds of results. A person can say, "My favourite colour can be expressed as that produced by a photon source in which all the radiation has the wavelength 530 nm. It's a kind of green."

Well, the wavelength is a manipulatable scalar, as is the intensity of the source and so on. But the greenness of the colour is what we call an example of the qualia, those sensory occurrences which we find difficult to think about, and which are almost by definition the basis of qualitative data. It is extremely unlikely that any two people will see exactly the same shade of green when exposed to a light source at 530 nm. This can be due to biology, biography or biasedness of some unknown kind. In fact, it is even less likely that the colour will affect them in exactly the same way.

This is why the methodologies that handle quantitative and qualitative data tend to be, respectively, mathematical and social. The former manipulates numbers of the kind that can be manipulated (vectors, scalars, cardinals — but not most ordinals); if any explanatory power resides in numbers, it is of the statistical and correlative kind. The latter tries to come to humanly acceptable consensus on what qualia could possibly have been observed and what kinds of explanation would be sufficient to account for them.

Of course, books have been written on guidelines for research in both kinds of methodologies and their deployment in many different areas of knowledge. I myself used mixed methodologies when doing my 1999 Master's thesis on Why Teachers Quit Teacher Development in Atlantis. Most of it was qualitative though; qualitative data is a lot better at explaining social phenomena and general insanity than quantitative data is. You can find my research online if you know where to look. Enjoy!