Figures that don't add up
The second is the worrying observation from John Elvidge, the head of education within the Scottish Executive, that "simply because we can't measure everything is no excuse for not measuring what we can" - I'm about 156 centimetres tall by the way - and the third is Brian Boyd's excellent article on the reliability of research.
Brian Boyd is quite correct to point out that research carried out by bodies like the Scottish Council for Research in Education and the former Centre for Educational Sociology was careful and rigorous. For example, when Andrew McPherson was looking into the effectiveness of comprehensive education he waited until all the youngsters who had started in the selective system had left school so that he could be sure he was looking at the actual effects of the comprehensive system, and not at the process of change or at a comprehensive system moderated by any hangovers from selection.
It was on the basis of such careful research tha he concluded that a comprehensive system served all pupils well.
However, what has passed for "research" more recently has been a quick look at official statistics, followed by a knee-jerk reaction without any due consideration as to what the figures really mean. A classic example here has been the way the whole scare over modern language teaching was based on an utterly false comparison of the numbers taking a modern language Higher in 1996 and in 1976.
The figures used for the comparison were the percentage of those actually in the fifth form at the two dates, rather than the percentage of the whole year group, and no account was taken of changes in the percentage staying on to fifth year over the 20-year period. The statistics may have been correct; their use was invalid.
So the answer back to John Elvidge is that it's all very well measuring everything that you can measure, but it's useless unless you stop to work out what the figures actually mean.
Finally, I'd like to ask Mr Elvidge a question. Does the fact that education has twice as many statisticians as any other department mean it's twice as efficient, or twice as inefficient?
Findhorn Place, Edinburgh
Letters to the Editor