Documents
Working with MIAP Data - Data Quality and the Unique Learner Number
MIAP and Data Quality
MIAP brings together learning and skills sector organisations and learners to use and share meaningful data about a learner’s participation and achievement from a trusted source, the Learner Record. The coverage of the MIAP Programme is being extended by the addition of new services such as Diplomas; and new suppliers of data such as the achievement data from the Department for Children, Schools and Families (DCSF).
Getting data quality ‘right’ is critical as the ULN and learner’s details are embedded in a variety of data and MIS systems across the education sector. Users should be aware that the learner details that they include with the ULN when communicating to other systems are very likely to be validated against the LRS by the third parties receiving them. For example, Awarding Bodies (ABs) will validate the learner details supplied by centres before they post any results to the Diploma aggregation service (DAS).
Any mismatches between the supplied information and that held against the learner on the LRS may result in users being asked to clarify the data supplied and where necessary update the relevant record in the LRS. Keeping the key details – given name, family name, date of birth and gender – in line between your MIS system and the LRS is good practice and minimises the possibility that mismatches may occur.
To mitigate the data quality risks, MIAP has implemented a combination of system based controls, best practice procedures and protocols and drafted guidance material to assist users get the most out of MIAP services. The data quality framework that MIAP has implemented to support the day to day LRS operations helps its customers to understand:
- Best practice approach to using the LRS and how to minimise the risk of data error
- How to avoid and minimise the risk of duplication
- How to search, create and update demographic data held against a ULN; and
- The implications of data sharing between third parties
For detailed guidance on maintaining data quality refer to the document:
Download: Working with MIAP Data – Data Quality and the Unique Learner Number
