Student outcome and experience measures

To help users to understand the methods we use to produce student outcome and experience measures, we have published a series of documents.

Latest documents

• Description of student outcome and experience indicators used in OfS regulation
  Descriptions of the measures and the methods used to construct and present them, which can be used to better understand our approach.
  • May 2026 version - applies to the size and shape of provision dashboard only.
  • October 2025 version - applies to all other dashboards.
    
    
• Technical algorithms for student outcome and experience measures
  Technical descriptions of the categorisations (or algorithms) applied to individualised student data records to generate our measures.
  
  
• Rebuild instructions for student outcome and experience measures
  Instructions for providers to rebuild our student outcome and experience measures from their individualised data files, which providers can use alongside the algorithms document to understand which students have contributed to our measures, and how those students contributed.
  
  
• Field name mappings for technical algorithms for student outcome and experience measures
  Mapping pre-March 2026 field names to new field names.
  
  
• Subject code mappings for constructing student outcome and experience indicators
  A guide to how Department for Education subject codes align with other classification frameworks such as the Joint Academic Coding System (JACS) and Common Aggregation Hierarchy Level 2 (CAH2).
  
  
• Benchmarking sector averages
  The sector averages that our benchmarking calculations use to construct provider indicator benchmarks, which can be used to understand how the outcomes and experiences of a providers students compare to similar students in the sector as a whole.

The documents align with the approach described in our consultation on the construction of student outcome and experience indicators.

While all of the algorithms described in these documents are relevant to production of our student outcome and experience measures, we also use some of them in other analysis and statistics. For example, algorithms found in our core algorithms documents are used as the basis for the definitions of published data on the student characteristics data.

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