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Forecasting SEN Participation in Post-16 Provision in London

ethanael-nathan avatar
ethanael-nathan
6 diapositives · 186 Views · Nov 09, 2014

This project addresses the need for systematic forecasting of demand for post-16 education and training for 16-25 year-olds with Special Educational Needs (SEN) in London. Utilizing historical PLASC data, we model trends among learners with different primary needs. An interactive forecast model will be developed, allowing users to analyze data at the local authority level, adjust variables, and generate visual reports. Key questions about current and future SEN learner needs will be addressed to facilitate better planning and resource allocation among local authorities.

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  1. Forecasting SEN Participation in Post-16 Provision in London Data Advisory Group

  2. Project Context • Local Authorities have a responsibility to ensure suitable education & training to meet the needs of 16-25 year olds with Learning Difficulties and/or Disabilities • To date there has been no systematic method of predicting levels of demand which means planning for this group is challenging

  3. Modelling • Using “PLASC” data across multiple years as primary source • Linked to attainment where available • Focussing only on SEN stages where Primary Need is returned: School Action Plus and Statemented for Post-16 Projections • Using historical data to identify how volumes of SEN learners are changing over time • Identifying whether there are specific trends for particular Primary Needs

  4. Forecasting & Visualisations • Develop an interactive forecast model which allows users to drill through London level data to individual LAs • Potentially allow the user to adjust certain variables • Output a series of graphical analyses and overall “dashboard” reports, including visualisations. For example:

  5. Variables & Feedback • Are you more interested in LLDD resident in your LA or LLDD in your schools? • What are they key questions on LLDD you have? • How many there are post-16 now? • How many there will be in the future? • What their type of needs are? • Would you envisage any problems with either Census data before a certain time in your LA or with focussing on School Action Plus and Statemented Learners? • What variables should be used in modelling future demand? • Should other data sources be included (eg: ILR, Connexions) to help understand supply? • What time horizon would be most appropriate?

  6. Further Questions • YPES • Glyn Parry – glyn.parry@londoncouncils.gov.uk • Mime Consulting: • Steve Preston – steve.preston@mimeconsulting.co.uk • Phil Rossiter – phil.rossiter@mimeconsulting.co.uk