Added: Crystle Fretwell - Date: 01.04.2022 20:31 - Views: 23199 - Clicks: 2499
Schools are complex places full of blood, sweat and break-times.
Making sense of all of the complex factors that determine the success of our students is a devilishly difficult task, like the proverbial needle-seeking in a haystack. When faced with such difficulty, whilst being tired and time-poor, we instinctively look for short-cuts to help us. One such shortcut to action is data.
Schools are awash with data. Despite all of the data, seldom do school leaders and teachers gain deep, sustained training about using it well. In the busy hubbub of the school week, we then become prone to all-too-human biases. Our short-cuts become deeply rooted in our daily experience.
One common short-cut is stereotyping.
Our biggest, more prevalent stereotype? Educational iconoclast, David Didauhas written a brilliantly provocative blog on how we use gender as a shortcut to action in schools, whilst drawing into question how prevalent it is in our thinking and school organisation:. And the extent to which gender might be causal is more likely due to cultural rather than biological causes, as this article makes clear. It is rather like the reality of shark attacks.
Thought they loom large in our imagination, the likelihood of our dying by shark attack is infinitesimally small compared to death by drowning, and yet our psyche is scarred with the dangers of sharks! Gender differences in our society are clearly so pronounced and salient, from unequal pay, to many more differences and inequalities predominantly tipped against womenthat it is natural to seek out gender as a cause for differences in the classroom, but we need to be better at scrutinising and analysing data and being aware of our intuitive biases.
All very familiar. What could we do? Perhaps, we needed to have an assembly telling their boys to buck their ideas up? What if mixed gender groupings were holding girls back? We had some subject specific issues in terms of under-attainment and behaviour, but those were not long-term trends. Typically, we analyse the data of year groups, starting with the usual Pupil Premium and disadvantage indicators. Crucially, we spot those salient patterns — remember the shark — such as gender.
We should be very wary of sub-group analysis. Put simply, the smaller the sample, the greater the variation. Where do we start then? Well, we know that gender can correlate with student outcomes, but we need to analyse an array of student and school level factors that are likely to prove more important. If you read the excellent Edudatalab website, you can crib up on how school with the most able prior attaining students still make most progress ; the influence of ethnicity, EAL and long-term disadvantage ; trends related to birth orderand much more.
Dr Becky Allendata expert and formerly leader of Edudatalabhas sage advice for every teacher and school leader:. You will almost always find some difference in attainment between one group and another purely due to chance. Beyond this, it is far more likely that your gap arises for reasons that are entirely outside the control of your school, such as home circumstances.
If you are still want to do something to help your boys, then the current research evidence says the most important thing to pay attention to is school behaviour, for boys learning appears to be ificantly affected by classroom disruption. After all, there is more that is similar in the minds and personalities of girls and boys than there is difference. Thank you to Dr Becky Allen — and her Edudatalab team — from pushing forward the profession to better analyse data and see beyond the salient headlines. Are sub-groups EAL, age, disadvantage, prior attainment, absence rates etc adding useful indicators to our data analysis?
Careful though, remember: How is the size of the data-set skewing the sub-group analysis and creating false headlines? How reliable and valid is the data I am analysing?
Are there three year trends I can explore so that I am not swayed by the latest exam data or similar? Thank you to Dr Becky Allen — and her Edudatalab team — from pushing forward the profession to better analyse data and see beyond the salient headlines Related. Follow Get the latest posts delivered to your mailbox:.Girls look here so
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