Data Galore!

Reading Time: 4 minutes

Whether or not you have great relationships with your students, how well do you know their prior data and pathway?

This post is offered as a professional development (interview practice) resource and is designed:

  • to test your knowledge of data;
  • to understand students’ prior starting points and pathways;
  • to consider the vast range of teaching strategies and intervention you could deploy to help target vulnerable students.
  • to ensure teachers can identify areas for development and help students make expected progress.

The data presented here is entirely fictitious.*

Dataset:

Take a moment to analyse the data presented below. There are 29 students in one class, so you will need to look between pages 1 and 2 of the table. It is shown this way for easy viewing on this blog.

You can also search the table and use the data filter function at the top of the table to rank in ascending or descending order. All the acronyms are explained in the footer.

Student Dataset

NameAttendanceHome LangaugeEAL stageSEND statusPupil PremiumReading AgeH/M/LKS2 APS
Student N Female75.5%EnglishEYes9.08Low24
Student P Male100%English16.04High39
Student E Female100%EnglishYes14.01High30
Student F Female95.5%EnglishKYes12.10Middle30
Student H Male100%English15.02High38
Student U Male100%English14.03High36
Student T Male100%English16.05High39
Student D Female99%English13.10High33
Student W Female99.5%English13.10Middle33
Student R Male98.5%EnglishKYes13.10High33
Student S Female100%EnglishYes14.10High33
Student Y Male100%ArabicDKYes13.05High36
Student J Female100%BengaliCKYes13.01Middle30
Student V Female99.5%ArabicDKYes13.07Middle33
Student O Male100%ArabicEYes14.09High36
Student Z Male98%UrduAKYes12.09Middle33
Student B Female95%SomaliBKYes11.11Low27
Student C Male91%SomaliAKYes10.0930
Student G Male95.5%ArabicBYes13.02High30
Student Q Female100%ArabicBYes12.06Low26
Student X Female99%ArabicBKYes12.09Low27
Student L Female100%PersianB12.10Low27
Student I Male100%PashtoBK12.09Middle30
Student AA Male100%PersianCK13.05Middle33
Student M Female100%Albanian AYes11.09Middle30
Student K Female100%KurdishBKYes12.09Low27
Student AC Female100%TagalogC14.04High33
Student AB Female100%PortugueseDYes13.10Low21
Student A Male95.5%FrenchD13.08High33
This data is entirely fictitious is is for a year 9 class (14 years old). It is offered as a CPD tool for teachers who wish to understand prior and current data better when considering a range of intervention strategies to deploy.

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Interventions Available:

Research (2011) from the University of York* and Sutton Trust and Education Endowment Foundation (2015) suggests that schools are adopting a number of promising strategies to improve outcomes for children living in poverty.

This Which-style guide summarised the world’s education evidence about interventions offering teachers best bets of what has worked more effectively in schools together with the relative costs of each approach. This enabled schools to decide how to allocate funding. Unlike other research summaries, the aim was to create a genuinely accessible guide for teachers. (Toolkit, 4 Years On: Lessons for Spending the Pupil Premium, page 16)

Here is a list of example interventions you could deploy for students; this list is not exhaustive and some will be more effective than others.

  1. Literacy intervention for students with a low reading age.
  2. Tailored tests to assess progress.
  3. Tutoring in maths and English to support students who are not making progress.
  4. Speech and language support for students new to English.
  5. Change the student’s location on your seating plan.
  6. Provide scaffolding resources and choices.
  7. Engage parents and student aspirations.
  8. Funding support from Pupil Premium to assist with classroom resources.
  9. Support from EWO (Education Welfare Officer) for students with poor attendance.
  10. Train teachers to better monitor and use of data.
  11. Extending the breadth of the curriculum.
  12. Improving feedback between teachers and pupils.
  13. Peer-to-peer tutoring schemes for pupils.
  14. Additional teachers.
  15. Reduce the class size.

Questions:

Having looked at the data above, what are your immediate thoughts:

  1. What interventions would you deploy?
  2. To which students? Why?
  3. What would you do for pupil premium students?
  4. How would you adjust your teaching, planning and marking?
  5. What would you do for students with low attendance or low reading ages?
  6. How would you adjust your teaching, planning and marking?
  7. How can teachers gain a secure overview of every child they teach?
  8. How would you measure the impact of the intervention selected?
  9. Does data vary between ethnicity or gender? Does it matter?
  10. At what point would you re-test students after interventions are put in place?

These questions are not exhaustive.

Acronyms Explained:

The following acronyms are explained in the order presented in the table.

  • Student A (name) and gender.
  • Attendance %
  • Home language
  • EAL codes: there is a good overview of the new codes in Schools Week.
    • A = new to English; needs a considerable amount of EAL support.
    • B = Early acquisition; have become familiar with some subject specific vocabulary
    • C = Developing competence; requires ongoing EAL support to access curriculum fully.
    • D = Competent; needs some/occasional EAL support to access complex curriculum material and tasks.
    • E = Fluent; operates without EAL support across the curriculum.
  • SEN codes: the K code amalgamates the two codes of A (School Action) and P (School Action Plus) and these codes will gradually be phased over by 2016 where a pupil has been assessed as having significant learning difficulties. Four types of action should be put in place for effective support, assess, plan, do and review. The E code this replaces the current code for statemented pupils (Code S). In line with the SEN Code of Practice, Education, Health and Care plan is Code E.
  • Pupil premium funding.The PPG per pupil for 2015 to 2016 is as follows: Source DfE.
Disadvantaged pupils Pupil premium per pupil
Pupils in year groups reception to year 6 recorded as Ever 6 FSM £1,320
Pupils in years 7 to 11 recorded as Ever 6 FSM £935
Looked-after children (LAC) defined in the Children Act 1989 as one who is in the care of, or provided with accommodation by, an English local authority £1,900
Children who have ceased to be looked after by a local authority in England and Wales because of adoption, a special guardianship order, a child arrangements order or a residence order £1,900
  • Reading ages versus a student’s chronological age (of birth).
  • H/M/L:  Defining Low, Middle and High Attainers. Key stage 2 (KS2) performance tables. Definitions are based on the key stage (KS1) results attained by pupils on completion of the infant phase. Further details here.
  • KS2 APS: Key Stage 2 (10 years old) Average Point Score. The output measure for each pupil is the average point score achieved in the English, mathematics and science KS2 tests. … A pupil’s value added score is calculated by comparing the KS2 performance with the median KS2 performance of other pupils with the same, or similar, prior attainment at KS1. Further details here.

I hope you find this a useful exercise.

TT.

*There may be contradictions of data; please comment and I will adjust.

Sources: 

@TeacherToolkit

In 2010, Ross Morrison McGill founded @TeacherToolkit from a simple Twitter account in which he rapidly became the 'most followed teacher on social media in the UK'. In 2015, he was nominated for '500 Most Influential People in Britain' in The Sunday Times as one of the most influential in the field of education - he remains the only classroom teacher to feature to this day ... Sharing online as @TeacherToolkit, he rebuilt this website (c2008) into what you are now reading, as one of the 'most influential blogs on education in the UK', winning the number one spot at the UK Blog Awards (2018). Today, he is currently a PGCE tutor and is researching 'social media and its influence on education policy' for his EdD at Cambridge University. In 1993, he started teaching and is an experienced school leader working in some of the toughest schools in London. He is also a former Teaching Awards winner for 'Teacher of the Year in a Secondary School, London' (2004) and has written several books on teaching (2013-2018). Read more...

6 thoughts on “Data Galore!

  • 26th Oct 2016 at 3:58 pm
    Permalink

    This is madness!! But ou English love your pointless data and paperwork…oh well continue on…

    Reply
  • 6th Nov 2016 at 9:52 am
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    I’m a SENCo and i lurve data. Thanks for this useful exercise. Only niggle. Why use reading ages instead of standardised scores? As a 14yr old, it’s not nice to be told you have the reading age of a 9yrold. I’m not criticising, as this is a seperate debate that a lot of schools need to have.

    Reply
    • 6th Nov 2016 at 10:44 am
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      In the UK, reading ages are becoming more and more valuable to help differentiate the needs of your students… rather than looking at the end-result e.g. the test score, use the reading age data to pre-plan intervention needed.

      Reply
  • 15th Nov 2018 at 1:32 pm
    Permalink

    I’m new to teaching and teach in an IB school in France. I had never heard of pupil premium before. as I’d never heard of it before. Would you say there is a slight or not so slight or even big risk of children being put in “needing extra help” categories and therefore more likely to be on the pupil premium list as a way to up the income available to the school since underfunding is a real issue?

    Reply
    • 16th Nov 2018 at 8:58 am
      Permalink

      The key issue here is ‘how do the schools distribute the money’ to those students who need it most.

      Reply

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