Describing schools at data obsessed doesn’t quite convey the almost religious reverence that data is given in schools today. For some teachers pupil premium, ethnicity, and SEN are not just indicators of educational vulnerability but a category that requires immediate interventions to be planned and delivered to students.
We now habitually label students with grade, level and sub level targets that we use to determine what activity each student should complete in lessons. Which, for a lot of teachers, will be linked to Bloom’s Taxonomy, or Anderson’s revised taxonomy. Moreover, with the abolition of levels next year most schools appear to be replacing these measures with very similar surrogate systems.
Now, there’s nothing wrong with these approaches. Sometimes I want my gifted and talented GCSE students to generate their own categories to explain why an event happened. Doing this while my C target students are given rigid categories is usually the right amount of stretch and support to allow all students to make good progress.
However, sometimes, I need to differentiate by getting inside the minds of students and by working on precisely what they know and don’t know. I need rich data, I need big data, and I need it quickly analysed and provided to me in real-time so that I can use it. I need to differentiate live! With the effective use of technology, this can be a reality in any classroom…
So, back before the always hectic GCSE exam season I wanted one piece of rich data. I wanted to see exactly what my Year 11 Classics students knew and what they didn’t know. I had tracked their ability to write essays, and differentiated based on manageable targets for each student, but now it was crunch time. I needed better data.
- What did they know?
- What didn’t they understand?
- What knowledge could they gain in the last few weeks?
Being the total geek that I am I designed a PHP app that would make students answer questions on everything that they they had studied over the course. It would then produce a colour coded spreadsheet for the revision needs of each student. Students had to respond to this feedback by constructing a clear action plan of how they were going to tidy up the gaps in their knowledge.
I’d post the app here, but it seems my one day coding marathon has been usurped by the masters of assessment at Socrative. Now, the AfL and differentiation geek inside me is happy to see that quizzes taken by students on Socrative 2.0 will produce individual reports for students. So anyone can get this high quality data from students and differentiate from it instantly! Get over to http://www.socrative.com/ to check it out!
So, after the plans were made, I just supported and monitored students to ensure that each one of them was meeting their targets. Students were taking ownership of their learning. There really wasn’t that much for me to do!
After a couple of lessons of seeing students working on their needs I assessed them again using a similar quiz. This time, there were no gaps in subject knowledge! Success!
I had now acquired two valuable lessons which I could take forward with any GCSE group:
1) Differentiation is most effective when students take ownership of their learning.
2) If you collect data in real-time, and that is of a high quality, from students, you can differentiate very effectively and without much effort.
Now, I am keen advocate of differentiating live! Now…we’ll wait until August to see if this paid off in the actual GCSE exams!by