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Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

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Page 1: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Mining the DataMining the Data

Jo WiggansJo Wiggans Director Director

Page 2: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.
Page 3: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

The Workshop includes:The Workshop includes:

What is in the Aimhigher data caveWhat is in the Aimhigher data cave

The uses of statistics in AimhigherThe uses of statistics in Aimhigher

Targeting and the allocation of resourcesTargeting and the allocation of resources

Digging into the data to uncover hidden Digging into the data to uncover hidden needsneeds

Page 4: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Action ResearchVolume 6(2): 123–127Copyright© 2008

“From small local projects to those with large-scale national policy outcomes and international implications, action research provides the means not only to define more clearly ‘what is wrong’ – to clarify the problematic features of a situation – but also to identify ‘what is right’– the strengths and assets that provide the base from which to construct effective and sustainable solutions. … moving from understanding to practical action is an integral part of the action research process.”

Ernie Stringer, Meghna Guhathakurta, Mwajuma Masaigana and Steve Waddell

Page 5: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

30 - Action Research as a Strategy for Advancing Community-Based Natural Resource Management

Action Research Action Research as a Strategy for as a Strategy for Advancing Advancing Community-Based Community-Based Natural Resource Natural Resource ManagementManagement

Doug HendersonDoug Henderson

Page 6: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

What’s in the Aimhigher data cave?What’s in the Aimhigher data cave?

UCAS and HESA data on the local populationUCAS and HESA data on the local population School PLASC analysis – deprivation, ethnicity, gender, School PLASC analysis – deprivation, ethnicity, gender,

attainment, FSM, attainment, FSM, Detailed pupil profiles – FSM, ACORN, IDACI, LAC, FFT Detailed pupil profiles – FSM, ACORN, IDACI, LAC, FFT

scores and predicted scores, actual attainment grades, scores and predicted scores, actual attainment grades, SEN and School Action, etc….SEN and School Action, etc….

HE heritage and NS SECHE heritage and NS SEC Area population profilesArea population profiles Economic trend and employment dataEconomic trend and employment data Masses of qualitative feedback, case studies etc.Masses of qualitative feedback, case studies etc.

Page 7: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

How we use statistical dataHow we use statistical data

To distribute resources fairly To distribute resources fairly To define the priority target cohortTo define the priority target cohort To assess progress in widening To assess progress in widening

participation in the areaparticipation in the area To identify issues and revise practice To identify issues and revise practice

prioritiespriorities To inform partner strategies and grow To inform partner strategies and grow

understanding of HE participation issuesunderstanding of HE participation issues

Page 8: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Informing partner strategiesInforming partner strategies

What partners don’t have:What partners don’t have:Higher Education InstitutionsHigher Education Institutions: population : population

participation data for their local area; participation data for their local area; comparative data on local school pupils; comparative data on local school pupils;

Local AuthoritiesLocal Authorities: HE participation data; : HE participation data; comparative progression data for local comparative progression data for local institutions; deprivation cross-referencing. institutions; deprivation cross-referencing.

Page 9: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Informing local strategiesInforming local strategies

JARs – Joint Area Reviews for local JARs – Joint Area Reviews for local authoritiesauthorities

SEFs – Self Evaluation Frameworks for SEFs – Self Evaluation Frameworks for SchoolsSchools

College reportsCollege reports 14-19 strategies at LA and LSC levels14-19 strategies at LA and LSC levels WPSAs and OFFA reportsWPSAs and OFFA reports Aimhigher web-based partner data systemAimhigher web-based partner data system

Page 10: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.
Page 11: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Local authorities: NI 106Local authorities: NI 106

To increase the proportion of young people To increase the proportion of young people from low income backgrounds progressing from low income backgrounds progressing to HE. to HE.

Measured by: the gap between the Measured by: the gap between the proportion of 15 year olds eligible for FSM proportion of 15 year olds eligible for FSM and those not eligible for FSM progressing and those not eligible for FSM progressing to HE at age 18. to HE at age 18.

Page 12: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Table 5: Proportions of students who were/were not in receipt of FSM aged 15 in 2001/02, who went to an HEI aged 18 in 2004/05 or aged 19 in 2005/06

Local Authority FSM Non-FSM All Gap

Bolton 15% 33% 31% 18%

Bury 17% 35% 33% 18%

Manchester 17% 27% 23% 11%

Oldham 18% 33% 30% 16%

Rochdale 16% 28% 25% 12%

Salford 7% 22% 19% 15%

Stockport 12% 36% 33% 24%

Tameside 10% 26% 23% 16%

Trafford 13% 42% 39% 29%

Wigan 10% 31% 28% 21%

England 14% 33% 30% 19%

Source: DIUS

Page 13: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Allocating resourcesAllocating resources

National modelNational model

50% of funding for 50% of funding for Aimhigher is allocated by Aimhigher is allocated by need based on GCSE need based on GCSE outcomes of maintained outcomes of maintained schoolsschools

50% is allocated on need 50% is allocated on need based on 15 year olds based on 15 year olds living in 40% most living in 40% most deprived by IMDdeprived by IMD

Area modelArea model

Three criteria, equally Three criteria, equally weighted: weighted:

IMDIMD FSM (school population)FSM (school population) POLARPOLAR

Page 14: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Borough Allocations 08-09

Deprivation Indicator Participation Indicator FSM Indicator

 

Estimate of Y7-11 pupils in target IMD

LSOAs

Estimate of 15 YOs in POLAR Less than 27%

Secondary pupils eligible for FSM

£ Distribution 2008/09

Bolton 10.8% 7.8% 8.5% 9.0%

Bury 5.7% 4.4% 4.6% 4.9%

Manchester 21.0% 21.1% 33.3% 25.1%

Oldham 9.9% 9.0% 10.0% 9.7%

Rochdale 10.1% 9.7% 9.1% 9.7%

Salford 9.5% 12.1% 11.0% 10.9%

Stockport 5.8% 8.4% 5.2% 6.5%

Tameside 10.2% 12.9% 6.5% 9.9%

Trafford 5.5% 2.0% 4.1% 3.9%

Wigan 11.4% 12.5% 7.6% 10.5%

Total       100.0%

Page 15: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Inarguable prioritiesInarguable priorities

LAname Name Pupil_Count

%_of_year_7 to

11_pupils_who_

live_in_IMD2007

target_areasFSM_count %_FSM

%_livingoutside_LA

Oldham Grange School 804 99% 506 63% 0%

Oldham The Hathershaw College of Technology & Sport 1020 99% 418 41% 1%

Oldham Breeze Hill School 785 96% 352 45% 0%

Oldham Kaskenmoor School 709 96% 292 41% 21%

Oldham The Radclyffe School 1349 92% 395 29% 14%

Oldham St Augustine of Canterbury RC High School 785 86% 178 23% 2%

Oldham South Chadderton School 718 85% 150 21% 27%

Oldham Failsworth School 1471 71% 243 17% 19%

Oldham Counthill School 1072 60% 225 21% 0%

Oldham Royton and Crompton School 1178 51% 163 14% 2%

Oldham Our Lady's RC High School 950 44% 101 11% 6%

Oldham The Blue Coat CofE School 1105 41% 47 4% 44%

Oldham North Chadderton School 1346 30% 95 7% 3%

Oldham Crompton House CofE School 1001 30% 14 1% 39%

Oldham Saddleworth School 1292 11% 66 5% 3%

Page 16: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

A recipe for defining the Aimhigher A recipe for defining the Aimhigher target cohorttarget cohort

1.1. A ‘basket’ of data including: A ‘basket’ of data including: Postcode to define Postcode to define IMD; FSM entitlement; SEN/school action; IMD; FSM entitlement; SEN/school action; gender; FFT scores and predictors – this is the gender; FFT scores and predictors – this is the initial cohort groupinitial cohort group

2.2. Stir in: teacher recommendation on potential to Stir in: teacher recommendation on potential to achieve and to benefit from Aimhigherachieve and to benefit from Aimhigher

3.3. Add a pinch of: considerations re friendship Add a pinch of: considerations re friendship groups etc.groups etc.

4.4. AND all Looked After Children irrespective of AND all Looked After Children irrespective of attainment profiles. attainment profiles.

Tracking the learners – local data collection in Tracking the learners – local data collection in conjunction with LA data leads.conjunction with LA data leads.

Page 17: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Assessing progressAssessing progress

Annual statistical updates at local levelAnnual statistical updates at local level Compare cohort progress against whole Compare cohort progress against whole

school year group and against similar school year group and against similar profile pupils not in the cohort – look for profile pupils not in the cohort – look for value addedvalue added

Longitudinal trackingLongitudinal tracking Case studiesCase studies Regular reporting at local and area level Regular reporting at local and area level

Page 18: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Change in UCAS Applicants Aged 18-20 in 2007 Compared to 2002

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Salfo

rd

Man

ches

ter

Traff

ord

Tam

esid

e

Bolto

n

Wig

an

Oldha

mBur

y

Stoc

kpor

t

Rochd

ale

England average

Greater Manchester average

Source: UCAS datasets

Page 19: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Change in UCAS Accepted Applicants 2001-2008

100

110

120

130

140

150

160

170

2001 2002 2003 2004 2005 2006 2007 2008

Greater Manchester England

Page 20: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

First Degree Entrants Aged 20 & Under in 2006/ 07

Rest of the North West36%

University of Salford

5%Royal Northern College of Music

0% Open University1%

University of Manchester

5%

Manchester Metropolitan

University11%

The University of Bolton

2%

East Midlands4% North East

4%

London3%

East of England1% Northern I reland

0%

Scotland2%

South West2%

West Midlands4%

South East2%

Wales2%

Yorkshire & the Humber

16%

Page 21: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Dig deep - it could be goldDig deep - it could be gold

UCAS acceptance rates at local FE UCAS acceptance rates at local FE collegescolleges

Russell Group Applications by Russell Group Applications by deprivation/domiciledeprivation/domicile

Beneath the gap in participation by Beneath the gap in participation by deprivation: the gender and ethnicity gapsdeprivation: the gender and ethnicity gaps

Page 22: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

In groups: In groups: You are a local Aimhigher partnership, tasked to plan You are a local Aimhigher partnership, tasked to plan

activities and interventions. You represent: activities and interventions. You represent: a university anda university anda local authority anda local authority anda local school or collegea local school or college

Look at the data and decide: Look at the data and decide:

How should we intervene?How should we intervene? When should we intervene?When should we intervene? Where (which institution or locality) is the Where (which institution or locality) is the

priority?priority? What else do we want to know?What else do we want to know?

Page 23: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Russell Group AdmissionsRussell Group Admissions

Looked at ward detail and previous education Looked at ward detail and previous education institutioninstitution

Published partner report to raise awarenessPublished partner report to raise awareness Worked with University of Manchester to shift Worked with University of Manchester to shift

targeting of their outreach programmes towards targeting of their outreach programmes towards Aimhigher prioritiesAimhigher priorities

Included presentations from Oxford, Cambridge Included presentations from Oxford, Cambridge and UoM in FE tutor staff developmentand UoM in FE tutor staff development

Talked to G&T coordinators in local authoritiesTalked to G&T coordinators in local authorities

Page 24: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

FEC Acceptance ratesFEC Acceptance rates Discussed data locally with local authority Discussed data locally with local authority

coordinatorscoordinators Met with college principals where acceptance Met with college principals where acceptance

rates were lowest – individually.rates were lowest – individually. Produced foundation degree guidesProduced foundation degree guides Work with college to run big induction event Work with college to run big induction event

featuring HE options and involving local HEIsfeaturing HE options and involving local HEIs Series of staff development events for FE tutorsSeries of staff development events for FE tutors One FEC now includes HE progression in their One FEC now includes HE progression in their

performance review for tutors and continues to performance review for tutors and continues to monitor HE progression by tutor groupmonitor HE progression by tutor group

Page 25: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Gender and ethnicity gapsGender and ethnicity gaps

Way to go yet!Way to go yet! Special projects for boysSpecial projects for boys Amended summer school and Aimhigher Amended summer school and Aimhigher

cohort guidance to encourage participation cohort guidance to encourage participation of boysof boys

Specific projects with BME communitiesSpecific projects with BME communities Focus on breaking down gendered career Focus on breaking down gendered career

and subject optionsand subject options

Page 26: Mining the Data Jo Wiggans Director. The Workshop includes: What is in the Aimhigher data cave What is in the Aimhigher data cave The uses of statistics.

Further informationFurther information

www.aimhighergreatermanchester.co.ukwww.aimhighergreatermanchester.co.uk

Joanne Moore: Research and Data Joanne Moore: Research and Data Manager Manager

[email protected]@open.ac.uk

Jo Wiggans Jo Wiggans [email protected]@open.ac.uk