What are Learning Analytics?

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This is the first in a series of FAQs about learning analytics which are being produced by the LACE project.

What are Learning Analytics?

There is no universally agreed definition of the term ‘learning analytics‘. One popular definition states that learning analytics are “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs[1].

In a series of briefing papers on analytics [2] the term was defined as “the process of developing actionable insights through problem definition and the application of statistical models and analysis against existing and/or simulated future data“.

Erik Duval has proposed the definition “learning analytics is about collecting traces that learners leave behind and using those traces to improve learning[3].

In a presentation given to senior library staff [4] Rebecca Ferguson places learning analytics in a continuum:

High-level figures: Which can provide an overview for internal and external reports and used for organisational planning purposes.

Academic analytics: Figures on retention and success, used by the institution to assess performance.

Educational data mining: Searching for patterns in the data.

Learning analytics: Use of data, which may include ‘big data’, to provide actionable intelligence for learners and teachers.

Why the Interest in Learning Analytics?

The NMC Horizon Report: 2013 Higher Education Edition [5] identifies learning analytics as a key technology for the higher education sector which has an expected time-to-adoption horizon or two to three years. The report suggests that “Learning analytics, in many ways, is “big data,” applied to education. The term owes its beginnings to data mining efforts in the commercial sector that used analysis of consumer activities to identify consumer trends.

The current interest in learning analytics reflects wider interests in “Big Data” and Educational Data Mining (EDM). Big data has been described is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications [6] whereas Educational Data Mining (EDM) describes a research field concerned with the application of data mining, machine learning and statistics to information generated from educational settings [7].

The interest in learning analytics reflects the increased use of analytics in other sectors. Supermarkets, for example, analyse data on purchasing patterns, effectiveness of marketing campaigns, etc. in order to target spending and manage stock levels. It has also been suggested that analytics helped Germany win the 2014 World Cup [8]. However the use of analytics in a learning context poses challenges which are not applicable in other cases. A further FAQ will explore such challenges in more detail.

Who are the Key Beneficiaries?

The key beneficiaries of learning analytics include:

  • Institutional administrators taking decisions on matters such as marketing and recruitment or efficiency and effectiveness measures.
  • Individual learners to reflect on their achievements and patterns of behaviour in relation to others.
  • Teachers and support staff plan supporting interventions with individuals and groups;
  • Functional groups such as course teams seeking to improve current courses or develop new curriculum offerings.


[1] Learning and Academic Analytics, Siemens, G., 5 August 2011, http://www.learninganalytics.net/?p=131

[2] What is Analytics? Definition and Essential Characteristics, Vol. 1, No. 5. CETIS Analytics Series, Cooper, A., http://publications.cetis.ac.uk/2012/521

[3] Learning Analytics and Educational Data Mining, Erik Duval’s Weblog, 30 January 2012,  https://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/

[4] Learning analytics FAQs, Rebecca Ferguson, Slideshare, http://www.slideshare.net/R3beccaF/learning-analytics-fa-qs

[5] NMC Horizon Report > 2013 Higher Education Edition, http://redarchive.nmc.org/publications/2013-horizon-report-higher-ed

[6] Big Data, Wikipedia, http://en.wikipedia.org/wiki/Big_data

[7] Educational data mining, Wikipedia, http://en.wikipedia.org/wiki/Educational_data_mining

[8] How Analytics helped Germany win the 2014 FIFA World Cup!, Ivy Professional School | Official Blog, http://ivyproschool.com/blog/blog/2014/08/09/how-analytics-helped-germany-win-the-2014-fifa-world-cup/

About this Document

This is the first in a series of FAQs (frequently asked questions) about learning analytics which will be produced by the LACE project.

Date published: 15 December 2014

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