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Peter Hendry: CEM Consultant. Data for Target Setting, Monitoring and Reporting. Course: Using CEM Data in Practice Day 2 Session 2 Thursday 18 th October 2012. Peter.Hendry@cem.dur.ac.uk. Data for Target Setting and Monitoring.
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Peter Hendry: CEM Consultant Data for Target Setting, Monitoring and Reporting Course: Using CEM Data in Practice Day 2 Session 2 Thursday 18th October 2012 Peter.Hendry@cem.dur.ac.uk
Data for Target Setting and Monitoring What type of predictive data should be used to set the targets? • Points and/or Grades • Nationally standardised baseline • Independent sector standardised baseline (MidYIS only) • Prior value-added (MidYIS, Yellis and Alis) • Chances graphs
Case study no.1: setting targets. • Uses valid and reliable data e.g chances graphs • Involves sharing data with the students • Gives ownership of the learning to the student • Enables a shared responsibility between student, parent(s)/guardian, and the teacher • Encourages professional judgement • Leads to the teachers working smarter and not harder • Leads to students being challenged and not ‘over supported’, thus becoming independent learners…
Student no.1 GCSE Geography Prediction/expected grade: 5.4 grade B/C Most likely grade
Student no.1 GCSE Geography Prediction/expected grade: 6.2 grade B Most likely grade
Sharing data with parents and students CASE STUDY No. 2 • All students sit formal examinations twice per year, Christmas and Summer • Director of Studies standardises each set of marks and calculates a standardised average. • Standardised data sent to pastoral staff • Pastoral staff tutor the students and meet with them individually • Pastoral staff contact parents if exam performance is “out of kilter” with baseline test score
Sharing data with parents and students On report to parents…….. consistent concern improvement improvement