What data do you need in order make sound judgements about your team’s performance?
Homework and assessment data, coursework data, data from interim reports (attainment, effort and indicative grades), KS2, KS3 and GCSE and AS data, GCSE targets and ALPs targets.
Where will you get the data you need in an appropriate format?
SIMs and interim report analysis from our data manager, department spreadsheets which are colour coded for comparison to ALPs target and GCSE target.
Do you know how to interpret it and apply it to your situation?
Interpretation in terms of percentages of each grade and key indicators such as A/A*, A*-C, A*-G for GCSE and A*-E for A level, interpretation in terms of value added.
How will you test it to ensure that it is valid and reliable?
Moderation of coursework, external marking of GCSE and AS examinations, work scrutiny for homework validity and reliability, moderation/discussion of marking of assessments with both colleagues and students. All data is recorded in departmental spreadsheets that can be easily updated and analysed.
How will you discuss it with your team?
Previously I have shared data electronically but I feel this has perhaps been lost in amongst all the other emails people receive on a daily basis. I am now going to attempt to have a personal conversation with each member of my department when interim data analysis comes in highlighting key areas for praise/concern and also hold more regular discussions about the data in our departmental spreadsheets and the students that require additional support.
What have you learned from the data and what actions do you need to take?
This will vary with each set of data - usually I find that there are certain individuals that need highlighting for extra support in lessons (simple strategies like making sure that they are required to answer a couple of questions each lesson or spending an extra few minutes with these individuals when circulating and facilitating activities in lessons). At GCSE any individuals who are at risk of not achieving can be selected for extra sessions to give them another attempt at improving their coursework score and at A level individuals who are not achieving are placed in a Chemistry study support group once a week for an hour after school where they focus on study skills. The data is often useful for highlighting early on which students we are concerned about through their indicative grade. I now need to make sure I have data conversations with colleagues rather than just expecting them to analyse the data themselves.
When and how will you review your findings? What are the implications?
When I receive the interim report data analysis I will take a day or two to analyse it before informally meeting with the relevant colleagues to discuss the key points and identify students that require additional support. It might be helpful to have a document to guide this (perhaps just an A5 sheet per class where we can make a note of which students are causing concern and what will be done). Hopefully this will raise teacher awareness of 'at risk' individuals and the subsequent conversation with students may be sufficient intervention to see an improvement. If not the teacher can also provide extra support in lessons to these individuals.
Having analysed the school-based data relevant to your subject, key stage or project, what are the implications for your team in relation to closing the gap?
School deprivation factor of 0.37 (above the national average), and also above national average for FSM, ethnic minority groups, EAL, school action plus and statemented students
· Chemistry GCSE - selective (triple) but above average for A/A* and A*-C, above school average
· Core - below average A*-C, above average A/A*, below school average
· Additional - average A*-C, above average A/A*, below school average
Areas to improve in science:
· First language English
· SEN without a statement
· School action plus
· Indian (but Bangladeshi above average)
These findings should be shared with the department and particular areas focused on in lesson observations and work scrutiny. Students that are not achieving should be highlighted at the earliest possibly opportunity through data conversations with colleagues. High quality teaching across the board is obviously important in order to improve attainment but it might also be worth considering with colleagues, students and perhaps parents what barriers may be in place for the groups that have been identified above. To evaluate the impact of leadership on closing the gap we should revisit the data.