Friday, January 19, 2007

Telling the Fulltime Counselling Course Students about Quantitative Research

Entry for 19 January 2007:

For today I had to repeat my lecture on quantitative research, which I had given already last term to the Monday parttime counselling course. I was all ready with the same client PE-111 Hermeneutic Single Case Efficacy Design presentation, using the strategy of hooking the students with interesting case material, when it came to me that the key statistical parts of this presentation were really going to go right over the heads of about half of the students.

So as of 10 last night, I started over on a different lecture, focusing on designing a Person-Centred research protocol. I got up early this morning in order to finish this lecture, which turned out very nicely.

However, as I was leaving for work, I began to feel that this was not really going to work either, so on my walk to work (between looking at the magpies: see previous entry) I made mental notes about a presentation aimed to work more interactively with the students on their stuck points about quantitative research and what they would find helpful. This is what I did, then:

1. I began by reading my poem “Numbers are Words of Power”, part 1 of Magic my Dad Taught Me (

2. We explored their relationship with numbers. While a few of the students have math phobia processes, most are simply distrustful, suspicious and turned off by statistics, because of their jargon, lack of meaningfulness, and impersonal nature. Many wanted to know about things like what a “p-value” means, what reliability is, and so on. A few felt that it is not in their ability even understand statistics.

I am a believer in Mahayana statistics (from one of two main schools of Buddhism); that is, I believe that enlightenment into the True Nature of statistics is possible for all (or nearly all people). Therefore, I took this teaching input as a challenge to try to bring enlightenment not simply to a few MSc and PhD students (that is Hinayana statistics, the narrow path for the few), but all or nearly all the post-graduate students.

3. I had decided as part of the second planned lecture to hand out copies of the CORE Outcome Measure and the Working Alliance Inventory. But now, instead of just giving it to them as a example, I began to explain to them how an instrument like this actually works and what the problems are. This was hard going for all of us, but I could feel us moving forward for the most part, but still many were not quite getting it.

4. The breakthrough came, when one of them asked if I could demonstrate filling it out. This sounded like a strange request, but I decided to give it a try. I completed the first two items, describing my thought process as did so. After this, I looked up, noticed that this wasn’t terribly interesting for them, and so I suggested that we all just fill it out for ourselves, and I would take them through using the instrument. This turned out to be a winning strategy, as I could then take them through hardscoring it and beginning to interpret it.

5. In the end, I was able to get as far as explaining the Reliable Change Index so that most but not all of them could understand it. At the end, there was a lot of energy in the room. I left feeling very pleased with the outcome of a very challenging and stimulating morning.

6. Actually, I feel a bit silly at discovering yet again that the only way to understand research is to live it, to experience it form the inside, here by actually filling out, scoring and interpreting the CORE-Outcome Measure. Afterall, I had taken an experiential approach for the first lecture I gave them. I wonder how many times I will have to learn that experience trumps all. I guess it’s a lesson worth learning over and over again!

1 comment:

Gaberlunzie said...

I was at that lecture. I can confirm that at the end of it I felt I'd moved towards being able to begin to make some meaningful connection with tables of data. For me, the difficulty has been knowing just what to make of the data, just as someone faced with, say, a cricket scoring sheet (to take a very un-Scottish example!), whilst able to see how some of the numbers relate to each other, might have great difficulty knowing the significance of these numbers without real knowledge of the game: is this a close game? where are the areas of tension? what might we predict? etc. I've begun to be able to translate some of those figures into meaningful relationships. As a consequence, I too think the lecture was successful. Thanks