The SMART university: the transformational role of learning analytics

Publication Date12 November 2018
DOIhttps://doi.org/10.1108/ILS-11-2018-135
Pages758-760
Date12 November 2018
AuthorDavid Jonathan Arwel Lewis
SubjectLibrary & information science,Librarianship/library management,Library & information services
The SMART university:
the transformational role of
learning analytics
David Jonathan Arwel Lewis
Jisc - Data and Analytics, Bristol, UK
Abstract
Purpose This paper aims to answer the followingquestions: What is the process and policy journey that a
universitymust go through in implementing an effective learning analytics programme?What are the drivers
for undertakingsuch an activity, and who are the stakeholders?
Design/methodology/approach The journey of the information, the process or the stakeholder is
placed at the heart of the programme, so a primarily ethnographic methodology is appropriate, although
ultimatelythe outcomes of analytics are usually quantitative.
Findings In undertaking the journey to a full implementation of an analytics programme, a university
must clearlyknow the strategic driver for starting, and the clear outcomes,if a purposeful path is to travelled.
Originality/value As a currently growing area of interest for lots of higher and further education
institutionsin the UK and worldwide, learning analytics should be high on everyonesagenda. This viewpoint
is intendedto provide a short overview to the process and the importantstrategic drivers.
Keyword EU
Paper type Viewpoint
So what is learning analytics and what opportunities does it offer higher education
institutions (HEIs)? There is a current focus for a lot of universities in using their existing
data for more constructive purposes, this can include student welfare, improved student
outcomes, or evidence driven course redesign. The data can be simply reported in more
timely or descriptive ways, or automated to learn or interpret in predictive models. In
partnership with Jisc, the Higher Education Funding Council for Wales (HEFCW)
announced the rst ever national programmeto cover learning analytics (HEFCW, 2018)in
July 2018. This was followed by Jisc launching the worldsrst nationalLearning Analytics
Service (McKie, 2018)in August 2018.
The collection and processing of data in an effective and timely manner is a key
component in any successfulbusiness, but perhaps even more important to a people-centred
organisation such as a University. All HEIs have a statutory obligation to collect
information about their students, at least to the standards prescribed by the Higher
Education Statistics Agency (HESA). All use a student records system to store
demographic, as well as academic information. All HEIs use at least one Virtual Learning
Environment to provide a teaching andlearning platform to all courses, as well as a library
management system and alsoin many cases systems to gather data on attendance (a Border
Agency requirementfor overseas students, also a professional requirement forsome courses
such as nursing). A lot of static and dynamic data is available for analysis. For many
institutions, this valuable data languishes in silos, or is manually processed on a cyclical
basis. Hence, it fulls it singlepurpose, but without more timely processing and ow outside
these silos, it will not provide anyinsight on individual student progress, provide alerts for
ILS
119,12
758
Received1 September 2018
Accepted3 September 2018
Informationand Learning Science
Vol.119 No. 12, 2018
pp. 758-760
© Emerald Publishing Limited
2398-5348
DOI 10.1108/ILS-11-2018-135
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2398-5348.htm

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