At Wellington, we have interim and full report cycles for each year group. These are spaced throughout the year at appropriate times to inform pupils, parents and staff about the projected IGCSE/IB outcomes for each pupil. More important than the outcomes though, is the ability to identify areas where pupils are struggling or where their effort seems to be falling so they can be addressed.
Pulling this data from ISAMS would normally require some heavy Excel work to make light of it following each reporting cycle. Thankfully, our IT tech gurus have added the report data to the data connection that pulls into my PowerBI model. This refreshes every hour giving us up-to-date access to the report data as it is added by teachers.
There are several checks that we like to do before reports are sent home, but also in the analysis that takes place following the closure of each reporting cycle. In the first instance, we want to check for mistakes that could have been made during data entry. By comparing the attainment and effort grades between two report cycles we can check for any wild swings that might suggest an error had been made.
We can also use this as a way to check for changes in effort or attainment over time. Where attainment and effort have improved this can be celebrated and conversely the appropriate intervention put in place where it is falling.
We can also use the CAT4 vs. attainment graph to analyse whether pupils are doing as well as we might expect based upon their CAT4 scores. Throughout this year, we will be developing a toolkit of strategies that can be used alongside this analysis so that all pupils can be supported effectively.
Teachers can also add their assessment data to the PowerBI model via the assessment data input Excel sheets. When data is added, it offers another lens to determine and analyse the attainment grades we award pupils. Whilst a percentage score from a test result is not the only form of assessment we use to determine attainment grades, it might still be expected to correlate strongly with them. The assessment vs. attainment graph therefore allows us to check that assessment data is informing attainment grades to some extent and if not then we can begin to question how valid our assessments are.
Using this suite of analytic tools we can easily check for mistakes, quickly identify trends in attainment and effort, calibrate attainment and assessment data, and assess whether pupils are meeting their potential according to the CAT4 data. Housemasters and tutors will look at a pupils’ progress across all the subjects they take, whilst Heads of Department and subject teachers will view it through the lens of their particular subject.
All of this data is open to all of our teachers so that we can have positive data-informed discussions that will ultimately result in the best support we can offer our pupils.