Learning analytics in European higher education—Trends and barriers☆
Introduction
Learning analytics (LA) as a field emerged a decade ago in response to the digitalisation of education and the maturity of data mining technology (Ferguson, 2012). Under the growing pressure of financial sustainability and competition with the global market, the higher education (HE) sector is driven to demonstrate evidence of quality educational offerings. As a result, LA has risen as a means to measure learning and answer difficult questions pertaining to the overall performance of an institution in the HE sector (Viberg, Hatakka, Bälter, & Mavroudi, 2018). Despite the growing interest in using data analytics to inform educational decisions and personalise support for students, the sector has struggled to establish the value and impact of LA on the improvement of learning (Ferguson and Clow, 2017, Viberg et al., 2018). In the recent NMC Horizon Report, adaptive learning as a key objective of LA has fallen out of the list of key development areas in HE after being featured for four consecutive years (Alexander et al., 2019). In light of the trends of educational technology development and deployment, the report argues that adaptive learning technology has not been able to scale up to its potential due to various challenges in institutional adoption (Alexander et al., 2019). Our paper responds to this observation by outlining the trends in and barriers to LA adoption in the European HE sector. Our intention is to provide insights into shaping the practice and research in the field as it moves into a new decade. This paper attempts to answer the research question:
What is the state of the art in terms of learning analytics adoption in European higher education?
Drawing on survey and interview data collected in a large-scale study, we present detailed analyses of the observed phenomena, and reflect on the implications of how LA has been conceptualised and applied. In particular, we identify gaps in the roles of teachers and students in the adoption process. The study presented in this paper is by far the largest in terms of the geographical coverage, as opposed to similar studies of its kind in the same region (Ferguson et al., 2016, Nouri et al., 2019). The paper contributes to our understanding of the complex issues that impede LA from scaling, provides concrete cases illustrating the approaches taken by higher education institutions (HEIs) to move technological innovations into operation, and challenges researchers and practitioners to reflect on where we are with LA and areas to improve in order to scale the potential of LA.
Section snippets
Learning analytics in higher education
Learning Analytics (LA) is commonly defined as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs” (Long, Siemens, Conole, & Gašević, 2011). Essentially, LA makes use of the data footprints produced by students when interacting with digital technologies in the learning process for the purpose of leveraging human decisions such as designing educational
Methodology
This study adopts mixed methods using a survey and interviews. The former was primarily distributed through the European University Association (EUA) to 249 HEIs (from 38 countries in Europe) that had previously responded to an e-learning survey conducted by EUA regarding institutional experiences in e-learning (Gaebel, Kupriyanova, Morais, & Colucci, 2014). We further promoted the survey via newsletters of European-wide professional networks such as European University Information Systems
Adoption experience
The majority of the institutions had less than three years of experience adopting LA. As Fig. 1, Fig. 2 show, only 9 out of 46 institutions that participated in the interviews and 7 out of 45 institutions that responded to the survey had more than three years of experience. In terms of the scope, we labelled institutions by ‘full’(institution-wide implementation), ‘partial’ (implementation at piloting scales or in parts of the institution), ‘preparation’ (in preparation to implement LA), and
Discussion
This exploratory study consulted HEI leaders to understand the state of LA adoption in European HE. Although the study suffers from a self-selection bias, i.e., institutions that had taken interest in LA were more likely to respond to our survey and interview invitations, it is clear that the uptake of LA was at an early stage where the implementation among the interviewed institutions was primarily at small scales and few institutions had a dedicated strategy, policy, or evaluation framework
Final remarks
LA promises to enhance education by providing insights that may otherwise not be obtainable without the availability of data and technology today. The main question that concerns us is, has the intervention of LA really enhanced learning, teaching, and the overall educational environment? How should we evaluate the impact and develop our capacity to continuously learn and mature from the process of exploring the big question? In this paper, we have provided a glimpse of the current state of art
Limitations
This paper aims to present a picture of the institutional adoption of LA in European HE. To this end, we focus on our consultations with senior managers in order to take advantage of their knowledge regarding the strategic decisions and actions related to LA. As a result, this paper is limited in the diversity of perspectives, and thus should be compared with the results of our wider study (blinded for review). As mentioned previously, the study presented in this paper suffers from
CRediT authorship contribution statement
Yi-Shan Tsai: Methodology, Formal analysis, Investigation, Data curation, Writing - original draft, Writing - review & editing, Project administration. Diego Rates: Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Pedro Manuel Moreno-Marcos: Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Pedro J. Muñoz-Merino: Formal analysis, Investigation, Supervision, Writing - review & editing. Ioana Jivet: Formal analysis,
Acknowledgements
This work was supported by the Erasmus+ Programme of the European Union [562080-EPP- 1-2015-1-BE-EPPKA3-PI-FORWARD]. The European Commission support for the production of this publication does not constitute an endorsement of the contents which reflects the views only of the authors, and the Commission will not be held responsible for any use which may be made of the information contained therein. We would like to thank the participant of this study for their generous contributions.
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This document is the results of the research project funded by the Erasmus+ Programme of the European Union [562080-EPP-1-2015-1-BE-EPPKA3-PI-FORWARD].
- 1
Present address: Goethe Universität, Robert-Mayer-Str. 11–15, 60629 Frankfurt am Main, Germany.
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Present address: Monash University, 25 Exhibition Walk, Clayton, VIC 3800, Australia.