A correlation is a statistical measure that describes the size and direction of a relationship between two or more variables. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable. Two events can consistently correlate with each other but not have any causal relationship. An example is the relationship between reading ability and shoe size across the whole population. If someone ,performed this survey, they would find that the larger shoe sizes correlate with better reading ability. But this does not mean large feet cause good reading skills. Instead, it’s caused by the fact that young children have small feet and have not yet,or only recently, been taught to read. In this case, the two variables are more accurately correlated with a third: age.
Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. This is also referred to, routinely, ‘as cause and effect’. Theoretically, the difference between the two types of relationships are easy to identify — an action or occurrence can cause another (e.g. smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. smoking is correlated with alcoholism, but it does not cause alcoholism). In practice, however, it remains difficult to clearly establish cause and effect, compared with establishing correlation
James Fall, when reviewing on his blog the recent IFS report on the London Challenge, made an important point-worth repeating. ‘“Correlation is not causation” is a golden rule of science and statistics. Yet in politics correlation is the causation of most policies. That’s often been the case in education, where politicians look for instant, glitzy success. In reality, it seems early intervention is more important but that (unsurprisingly) this takes time to yield visible success.’
What the IFS report finds, he says, is that, though there are explanations that are contributory factors, they are not the main driver of why London’s schools have improved so much, so fast.
He adds ‘The single biggest explanation of the ‘London effect’ is… what happened in its primary schools more than a decade ago. In essence, London’s primary schools, particularly in English, achieved great success between 1999 and 2003, which – years later – fed through into improved GCSE results. Yet the most frequently cited causes (certainly by politicians of all stripes) – London Challenge, Teach First and academies – focused exclusively in secondary schools initially, their move into primary schools occurring after the big improvements in primary schools took place’.
The most commonly heard mantra in education nowadays is evidence led practice( and /or policy). But it has been clear for some time that what ‘good evidence’ looks like is only understood by the few . And politicians are still, in some areas at least, either ignoring good research because its inconvenient and conflicts with some short term political objective they cherish ,or alternatively, they cherry pick evidence giving it undue weight to support a particular favoured policy. Although the situation is clearly better than it was, politicians will still often stray, and need to be held to account for the evidence they use to support their policies.
But we must also leave space for the subjective element in education and teaching . Education is not, self-evidently, rooted in just science and empirical evidence . Quite a lot of what happens in schools ,and indeed outside schools, and which is part of a child’s learning experience ,cant easily be measured, using scientific method, but nonetheless has value, to the individual, to employers and society.
Gabriel Sahlgren and Julian Le Grand recently argued that much of the commentary interpretation and explanation provided by the OECD around the recent Pisa results (they cited, in particular, the effects of competition and private provision) is a series of correlations rather than involving causation , so politicians should take care before implementing at least some of the OECDs recommendations.