Timmis, Sue

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                          Timmis, S. (2017). Learning analytics: what is it and why do you need toknow? Post-16 Educator, (89), 20-21.Publisher's PDF, also known as Version of recordLink to publication record in Explore Bristol ResearchPDF-documentThis is the final published version of the article (version of record). It first appeared online via Post 16 Educatorat http://www.post16educator.org.uk/. Please refer to any applicable terms of use of the publisher.University of Bristol - Explore Bristol ResearchGeneral rightsThis document is made available in accordance with publisher policies. Please cite only the publishedversion using the reference above. Full terms of use are available:http://www.bristol.ac.uk/pure/about/ebr-termsLEARNING ANALYTICS20 Post-16 Educator 89Over the past five to six years, there has been anoticeable rise of the new ‘field’ of learning analyticsand its growing influence on learning and teaching atall levels of education. The term learning analytics isnot always well understood but has been called thecollection, measurement and monitoring of learnergenerated digital data (Ferguson, 2012). Thesedevelopments are drawing significant attention fromsenior managers, administrators and IT services incolleges and universities, but are less wellunderstood by teaching staff and students.    Learning analytics is a growing, internationalresearch field that is devoted to the study of the useof digital data, it has its own Society (Society forLearning Analytics Research - SOLAR(1)) and hasjust had its seventh international conference. TheSOLAR website suggests that this is an inter-disciplinary network of leading internationalresearchers, exploring the role and impact ofanalytics on teaching, learning, training anddevelopment. One of its stated aims is to raiseawareness of learning analytics amongstpolicymakers in educational institutions andgovernments. Furthermore, the EU has a fundedcommunity hub for learning analytics called LACEand in the UK, there is to be a Learning AnalyticsService, run by JISC (Joint Information SystemsCommittee). Whilst there are some voices withinthis community that do offer critical perspectives(e.g. Kirschner, 2016), in the main it is dominated bytechnically focused researchers and a broadenthusiasm for what is seen to be the enormouspotential of using big data to improve learning.However, it is questionable how much consultationthere has been with staff and students on theseissues. Indeed, the broader post-16 educationacademic communities may be unaware of theextent of these research and development activities,and their reach and growing influence on educationpolicy locally and nationally. This article aims toraise awareness of learning analytics and itsgrowing influence on post-16 education and to offer acritical perspective on its value for teaching andlearning and the kinds of data and purposes forwhich learning analytics are appropriated.    There is now a proliferation of digital datacollected and stored on students (and staff) inuniversities and colleges across the world and it isno longer possible to be a student without engagingin online systems and processes (Dahlstrom et al,2013). Feedback from such systems, for examplethrough dashboards (intended to allow students tomonitor their activities and behaviours), and throughthe repurposing of centralised, aggregated data, areclaimed to offer the potential for adaptations,improvements and recommendations for learners,teachers and institutions as a whole. Yet, there hasbeen a much slower pace of technologies designedto share control with students (Facer, 2011) and, Iargue, the focus remains primarily on institutionalbenefits.    For example, the assertion that learning analyticscan lead to improvements in retention and academicperformance has led to the institutional adoption ofearly warning or predictive systems (see for exampleColvin et al, 2016). This is in line with the trendtowards a more individualistic and performative viewof learning in post-16 education where the onus ison ‘self regulation’. In other words, where the learneris expected to focus on their individual performanceand address ‘deficiencies’ but with little control overtheir data and where little account is taken of thesocial and community aspects of learning. There aresome new developments that are beginning to focusmore on critical and student-led approaches (see forexample the Learning Analytics Report Card projectat University of Edinburgh (2)) but much morediscussion is needed with lecturers and students toexplore what might be the most useful ways inwhich student data might be exploited and whatkinds of tools could be used to support studentsindividually and collectively.Sue TimmisLearning analytics:what is it and why doyou need to know?LEARNING ANALYTICS 21Post-16 Educator 89    Furthermore, the issues around datamanagement, ownership and sharing are likely tocontinue to multiply for both individuals and theorganisations and networks they belong to. Indeed,the data flow within the post-16 education sector, atclassroom, institution and national levels is alreadyprolific. This raises ethical issues about the degreeof consent students may have over the collection ofsuch data and the purpose to which it is put.Equally important is the issue of how they canaccess, own or control their own personal data. In arecent review of the literature on learning analytics inrelation to assessment, ethical issues seemed to berarely raised in learning analytics research or whendiscussing its implementation (Timmis et all, 2016).    A report in the Times Higher claimed that‘seventy-one per cent of students questioned byJISC, the sector technology body, said they wouldbe happy for data such as their library or virtuallearning environment usage to be used by theiruniversity, if it could help to improve their grades.’(THE, 2016b). This presupposes that meaningfuldata will be analysed and that students will be ableto understand and interpret this data in a way that isof benefit to them. Whilst this is not impossible, it isby no means a foregone conclusion. It alsosuggests potential conflicts in purposes of databeing collected and stored and also that studentsmay be being sold an overly positive message. TheUK Learning Analytics Service that is beingestablished is reported to be designed to feed intothe Teaching Excellence Framework (THE, 2016a)and is therefore intended for institutions andpolicymakers, in direct contrast to the earlier reportsthat the purposes of learning analytics were mainlyabout student welfare and progress. It is this conflictthat permeates much of the discussion of learninganalytics and, whilst it is often claimed to be aimedat students, the evidence so far is less convincing.    Colleges and universities have previously fallenprey to technologically deterministic policies, forexample the notion of a generation of ‘digital natives’remains fixed in the minds of policymakers despitebeing thoroughly dismissed by research (Jones,2013). I am cautioning that learning analytics isgaining credibility in policy circles in similar ways,through an over zealous belief in technology andthrough a learning analytics community that isprincipally focused on the potential of thetechnology, without there being sufficient scrutiny ofwhat this entails, what measures are beingproposed, the ethical implications and the validity ofsuch measures. This is of particular concern in theUK, where frameworks for accountability andmanaging teaching ‘excellence’ are alreadymainstream in universities and similar performancemetrics are in operation across the education sectoras a whole, but this applies equally elsewhere,where similar regimes are being implemented orconsidered. It is in this context that the rise oflearning analytics needs to be revealed andscrutinised, in particular by teaching staff andstudents who should be central to any discussionson its value and purpose.Notes1. https://solaresearch.org2. http://www.de.ed.ac.uk/project/learning-analytics-report-cardReferencesColvin, C., Rogers, T., Wade, A., Dawson, S., Gasevic,D., Buckingham Shum, S., Nelson, K., Alexander, S.,Lockyer, L., Kennedy, G., Corrin, L., & Fisher, J. (2016).Student retention and learning analytics: a snapshot ofAustralian practices and a framework for advancement.Canberra, ACT: Australian Government Office forLearning and TeachingDahlstrom, E., Walker, J., & Dziuban, C. (2013). TheECAR Study of Undergraduate Students andInformation Technology (Vol. 2010). LouisvilleFacer, K. (2011) Learning futures: Education,technology and social change. Abingdon, Oxon,RoutledgeFerguson, R. (2012) The state of learning analytics in2012: A review and future challenges. Technical ReportKMI-12-01, Knowledge Media Institute (Milton Keynes,The Open University)Jones, C. (2013) ‘The digital university: A concept inneed of definition’, in: R. Goodfellow & M. Lea (Eds)Literacy in the digital university: Critical perspectives onlearning, scholarship, and technology. Abingdon, Oxon,Routledge. 162-172Kirschner, P. (2016) Learning Analytics: Utopia ordystopia. Keynote address - Learning AnalyticsConference - 2016, University of EdinburghTimes Higher Education (2016a) National learninganalytics service: could it feed into the TEF? March 24th2016Times Higher Education (2016b) JISC finds moststudents ‘happy to share data for learning analytics’February 25th 2016Timmis, S., Broadfoot, P., Sutherland, R. & Oldfield, A.(2016, online 2015). ‘Rethinking assessment in adigital age: opportunities, challenges and risks’. BritishEducational Research Journal, Vol 42 (3) pp 454-476.

Learning analytics:what is it and why do you need to know?

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Learning analytics:what is it and why do you need to know?

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