Saturday, April 8, 2017

Qualitative Thinking


Qualitative Thinking
Multiple Responses
Qualitative Reasoning (QR) is an area of research within Artificial Intelligence (AI) that automates reasoning about continuous aspects of the physical world, such as space, time, and quantity, for the purpose of problem solving and planning using qualitative rather than quantitative information. Precise numerical values or quantities are avoided, and qualitative values are used instead (e.g., high, low, zero, rising, falling, etc.).

Qualitative and Qualitative Thinking

The world might be said to be made up of that which is relatively measurable and that which is relatively unmeasurable. Different schools of thinking place different levels of emphasis on the very measurable and the very unmeasurable. This is what has been the great debate between qualitative and quantitative approaches.

My professional position on this is that there is a continuum between quantitative and qualitative data definition and collection. Where you lie on this continuum depends on the question you are asking and how you define your outcomes.

There is no one best way of doing things!
  • Quantitative
    • Quantitative approaches are those where you make measurements using some relatively well-defined measurement tool. This can be as tight as a well developed intelligence test or it can be as loose as an ad-hoc questionnaire.
    • Tightly developed quantitaive devices have been developed through a rigorous application of psychometric theory. Emphasis has been placed on the reliablity or stability of the measurement. A great deal of work should have been done on establishing validity.
    • Assuming that the theory behind doing the measurement is valid, then a well developed quantitative tool should give you information in which you can have confidence.
    • The extreme of the quantitative approach is where people believe that all data should be tightly defined and validated; that any other data is purely exploratory and impressionistic.
    • The extreme of the extreme comes with those who believe that social research should be carried out with the same quantitative rigour as is supposed to exist in the physical sciences.

  • Qualitative
    • A qualitative approach refers to situtaions where you collect data in an unstructured way. If you use an unstructured interview you will have qualitative data. If you asks subjects to keep a diary of what they are doing, you are collecting qualitative data.
    • Often qualitative data will form the basis of a pilot study, where the aim is to get the best possible feel for the situation through broadly defined data. The results from the pilot study are then used to produce a relatively more quantified approach - e.g. from an open ended interview to a partially structured questionnaire.
    • At the extreme end of the qualitative approach is the belief that the only truly viable form of data collection is through open, unstructured methods.

  • When you might emphasise the Quantitative approach.
    • Some of the indicators for a quantitative approach are:
    • You are working with large samples - and you don't have the money for a large number of research support hours.
    • You have access to well defined tools developed elsewhere but which are appropriate to what you are doing.
    • You are doing research where you need data which will convince administrators or managers.
    • You are interested in being able to estimate or predict possible future performance on a large sample basis.

  • When you might emphasise Qualitative
    • The likely indicators for emphasising a qualitative approach are:
    • Your interest is in the qualitative nature of the subjects' behaviours.
    • You are searching out an area of interest and you cannot find anything much to guide you. So you need to get some sort of overview.
    • You have a long term research program in view. You want to get a good feel for the scope of the variables which might be involved.

There are two ways we approach listening to music, and it affects how we think about practicing.  Consider the illustration below.

(Picture borrowed from this website--I don't claim ownership of it)
On one side, you have a qualitative view of something.  It deals with abstract qualities of something: impressions, feelings, and descriptions.  The other side is concerned with a quantitative view, which measures specific and concrete data.

In regard to music, one can attribute a qualitative approach to the more artistic concerns: sound, dynamics, feel, ‘vibe’...all of those things that give us an emotional response.  Of course, quantitative thinking has to do with the technical aspects of music: tempo, rhythm, intonation, rhythmic accuracy...those which can be measured in an absolute sense.

As a drummer, one obvious case of this dichotomy is in regard to playing time.  There’s time, and then there’s feel.  I’ve always felt that the two are different, yet very closely linked, and the big difference is that they fall neatly into the quantitative/qualitative scale.  Time (quantitative) can be measured in terms of accuracy.  We can easily find out if it rushes or drags, or if the subdivisions are played solidly.  Feel (qualitative) has everything to do with one’s emotional response to the time being played: Does it propel the music and give it energy?  Does it make you want to dance, or does it sound stiff?  Does it fit with the song?  Accurate time alone, as we know, does not make for a great feel, yet to provide a great feel, the time does need to be steady and solid.

Oftentimes in a lesson I will have a student play through an exercise, solo or musical piece, and after they finish ask them how they felt about it.  What’s interesting to me is the answer I always get is something like, “Well, I messed up the fifth bar of the second line, rushed the ending, shortened the rest in bar 27”, etc.  In other words, their evaluation to their performance is always entirely quantitative.  All fine and dandy, I reply, but what about musical aspects?  Any thoughts on phrasing?  Dynamics?  Melody?  They get bogged down by technical concerns to the degree that the musical have been completely ignored.  Of course, one must first master the technical details (quantitative) in order to focus on the musical elements (qualitative).  What I see too often, however, is a failure on the students’ part to shift their focus to the musical aspects once they’ve achieved technical control on the exercise.

Understanding how the quantitative and qualitative characteristics of our playing work together can greatly enhance ones musical development.  A good place to start is with listening to music.

1.  When you listen to a new piece of music for the first time, listen once (or maybe a few times) through and notice the emotional response you get from it.  Usually the first couple listens of anything new to the listener are done at the “macro” level, so really be aware of the general qualities of the song and how they affect you on a base level.  You can even write your impressions down as an exercise.

2. Then, go back and listen for quantitative aspects: tempo, key, repeating rhythms, instrumentation, lyrics (if applicable), form, etc. so that you have a good understanding of the nuts and bolts of the song.

3.  Then, go back and listen again, once again shifting your listening focus back to the qualitative.  Perhaps this time you may be able to link the two a bit more. “Hmmm....The bass player comes in on the instrument’s upper register (quantitative), creating a ‘suspended’ feel (qualitative) at the top.  The drummer loosens the hi hats slightly on the 2nd verse (quantitative), which opens the song up a bit more and adds some lift (qualitative).”

The same can be done with ones own practicing.  Here’s yet another example of the value of recording your personal practice.  Listening to yourself play a musical piece, or even a technical exercise, and evaluating it (as above) on quantitative and qualitative levels can really open your ears.  You’ll discover a whole new way of listening to yourself when you play.

No comments:

Post a Comment