Streamlining the report checking process

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.

Checking the differences in effort and attainment between two selected reporting cycles enables us to quickly check for possible data entry errors and more importantly, to identify trends for each pupil.

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.

Upon selecting a particular pupil, the bar graphs on the left are filtered to show the changes for that pupil. Conversely, we could select a particular subject to filter the data to just show changes for that subject.
We can also use the attainment trends page to see more detail. Hovering over the attainment track over time line graph activates a tooltip which shows the grades for each individual subject at this point in time.

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.

In this instance, student 512 has a high verbal CAT score but a lower than average attainment track. We can hover over the dot to see the average attainment by subject and see if the lower than expected performance is across all subjects or within particular ones. This analysis then allows the appropriate action to take place to help this pupil improve.

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.

It could be argued that student 650 has a slightly higher average attainment grade than their assessment data indicates they should be awarded since there is a student to the left of them with the same assessment percentage but a lower attainment grade. Asking questions about this can improve the validity of both our assessments and attainment data.

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.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s