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Using data to support progression – the view from HEFCE

Using data to support progression – the view from HEFCE. Alison Brunt and Jessica Trahar. 21 October 2009. Overview: HEFCE’s use of data. Uses of data: To support policy formation and implementation To evaluate policy outcomes To inform our funding model

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Using data to support progression – the view from HEFCE

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

  2. Overview: HEFCE’s 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

  3. 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

  4. 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

  5. Table T1a - Participation of under-represented groups in higher education: Young full-time first degree entrants 2007/08

  6. 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

  7. Participants and participation rates in summer schools by school attainment quintiles

  8. 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

  9. Distribution of numbers of LLN students returned by an institution

  10. 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

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