Using data to support progression – the view from HEFCE 21 October 2009 Alison Brunt and Jessica Trahar

Overview: HEFCEs use of data Uses of data: To support policy formation and implementation To evaluate policy outcomes To inform our funding model To inform our knowledge of the sector

Using data to support our widening participation policies Evidence base used to inform our widening access funding methodology Use of data to evaluate and measure success in WP policies Provides us with evidence that our investment in WP is making a difference to under-represented groups

Using existing datasets/sources Types of data and uses HESA, ILR, UCAS Labour Force Survey Advantages Low burden on institutions Consistent data collection across the sector Established data source Disadvantages Limited depth of information

Table T1a - Participation of under-represented groups in higher education: Young full-time first degree entrants 2007/08 From state schools or colleges Total full-time first degree entrants No. who are young % who are youn g No. with known data % with know n data No. from state schools or colleges % from state schools or colleges Bench -mark (%) Standard deviation (%)+/- Location - adjusted bench- mark (%) Standar d deviatio n (%) +/-+/- Total UK Total England Anglia Ruskin University Aston University Bath Spa University The University of Bath University of Bedfordshire Birkbeck College(#3)

Creating new data collections Types of data and uses Aimhigher summer schools Aimhigher Associates Advantages Develop a data specification with the sector which is specific to our needs Evaluate success of specific programmes Disadvantages Guidance needed Time consuming

Participants and participation rates in summer schools by school attainment quintiles

The middle ground Uses existing datasets but with an additional element of collection Advantages National picture of how ASNs are utilised by LLNs Track students progression in the future Disadvantages Only one part of a much wider possible evidence base Identification of LLN learners not always straight-forward Lifelong learning networks – HESA data collection

Distribution of numbers of LLN students returned by an institution

LLNs – collecting data through monitoring reports Advantages Further form of data collection to monitor and evaluate progress Introduction of a standardised template enables us to see progress of all LLNs, across key areas Disadvantages Retrospective data collection in some areas Some assumptions must be made by LLNs