Edward Wright is Director of Studies at Eltham College in London, and is a member of the evidencebased.education Advisory Board. In this guest post, he talks about his approach to getting the most out of the MidYIS data (from Durham University’s Centre for Evaluation and Monitoring) he and his colleagues use, with particular focus on those students with scores in the middle of a group.
As far as data is involved, a good Director of Studies is very much like a Dentist; you’re constantly working to put yourself out of business. If a Dentist does a fantastic job you won’t need them again for a very long time, though in the world of privatised tooth care this is not an amazing business model. One of the hardest tasks as a Director of Studies is enabling staff to use and engage with data constructively without you, and coming from an Engineering background (as I do) it was difficult at first to concede that not all staff are overjoyed by columns of numbers: it has been a long process to move from that initial stage to where we are now.
To begin with we had to decide what we wanted to get out of the data. The school I teach at is a high-achieving private school in London and many of our students achieve above average MidYIS scores. We administer MidYIS tests in year 7 when the students arrive in order to help us identify areas in which students may need a little extra support. Primarily at this age, that means looking at the vocabulary and maths scores. In order to present this as easily as possible the data have been broken down into teaching groups and presented clearly in one graph (in the example below, names have been changed to the 1996 Newcastle United FC team).
It is important to remember at this stage that the MidYIS information has the same limitations as any other on-the-day test and individual external factors can play a huge part in a student’s performance. Data cannot provide you with the answers, merely suggest a sensible place to start asking questions. The vast majority of teachers will be able to identify the top and bottom of a cohort quite easily in their everyday teaching. Where we have found this most valuable is looking for students in the middle of the group.
From the graph above, a teacher would be able to identify that David Batty and Darren Peacock might struggle in subjects with significant demands on mathematical ability such as Maths and Physics, whereas Steve Howey and John Beresford may struggle with English and History. All subjects rely on elements of both Maths and Vocabulary ability to different degrees, so teachers will be looking out to provide support to students with particularly low scores (relative to their peers). In classwork, if Alan Shearer was outperforming his peers, then he would probably need congratulating as he was exceeding expectations; however, if Faustino Asprilla was in the middle of the cohort in classwork, then teachers might identify him as someone who could be pushed harder. Having information derived from MidYIS tucked into a markbook enables teachers quickly to see who is over- or under-achieving in their subject (relative to their ability scores) and direct their attention to where the data suggest it might have greatest impact.