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NUS – Learning analytics: a guide for students’ unions (LAEP Inventory)

Cloud created by:

Rebecca Ferguson
27 May 2016


The UK’s National Union of Students (NUS) has compiled a brief good practice guide for student unions within the UK. The start of the guide defines learning analytics as ‘using the increasing potential of data insight to improve students’ learning.’ It then highlights the types of data that universities may use, such as virtual learning environment behaviours, use of books or assessment marks. Next, potential benefits of adopting learning analytics are discussed, such as avoiding drop-outs or reducing demotivation. The remainder of the document focuses on risks associated with learning analytics, and considerations for student unions in schools that use student data. The risks highlighted include: privacy, data sharing with third parties, consent, and ‘formative’ versus ‘summative’ data. The document also links to JISC’s Code of Practice and contact information for help from NUS.


Inventory type:

good practice advice

adoption/implementation advice

Document source:

Educational establishment: NUS



Student Unions

Policy Context




National: UK


This document was created by NUS specifically to inform student unions of their rights and areas of concern. It also explicitly links with JISC’s Code of Practice (which was created in consultation with NUS).

Maturity and Evidence of Utility

This good practice document is relatively short, but is an excellent summary for those new to understanding learning analytics. It is also one of the few policy documents available that are explicitly written from a student perspective and address students as agents in the process of adopting learning analytics. It’s connection with the more formal JISC Code of Practice document also lends to its maturity and evidence of utility.

Further Information

Location of policy document:

JISC Code of Practice:

See also LAEP Inventory records:

  • JISC Code of Practice

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