The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
How do we start? An approach to learning analytics adoption in higher education
Open accessAbstract
Purpose: The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward data-informed strategic decision making. Yet, progress to date in embedding such data-informed processes has been limited. The purpose of this paper is to address a commonly posed question asked by educators, managers, administrators and researchers seeking to implement learning analytics – how do we start institutional adoption of learning analytics? Design/methodology/approach: A narrative review is performed to synthesize the existing literature on learning analytics adoption in higher education. The synthesis is based on the established models for the adoption of business analytics and finding two projects performed in Australia and Europe to develop and evaluate approaches to adoption of learning analytics in higher education. Findings: The paper first defines learning analytics and touches on lessons learned from some well-known case studies. The paper then reviews the current state of institutional adoption of learning analytics by examining evidence produced in several studies conducted worldwide. The paper next outlines an approach to learning analytics adoption that could aid system-wide institutional transformation. The approach also highlights critical challenges that require close attention in order for learning analytics to make a long-term impact on research and practice of learning and teaching. Originality/value: The paper proposed approach that can be used by senior leaders, practitioners and researchers interested in adoption of learning analytics in higher education. The proposed approach highlights the importance of the socio-technical nature of learning analytics and complexities pertinent to innovation adoption in higher education institutions.
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“Studies suggest that professional development and training in LA can improve educators' capacity to use data-driven insights to support student learning (Bergdahl et al., 2020;Bond et al., 2020;Gašević et al., 2019).”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Gašević et al., 2019
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“Gašević et al. (2019) emphasised that LA must become more rigorous in adopting educational theory.”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Gašević et al. (2019)
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“Indicating that there may be a gap between LA research and theory development, Gašević et al. (2019) emphasised that LA must become more rigorous in adopting educational theory.”
From Unpacking student engagement in higher education learning analytics: a systematic review (2024) · cites this paper as Gašević et al. (2019)
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Cites
Complexity Leadership Theory: Shifting leadership from the industrial age to the knowledge era
Uhl‐Bien, M., Marion, R., & McKelvey, B. (2007) · The Leadership Quarterly · doi:10.1016/j.leaqua.2007.04.002 · Cited by 2,667
Learning Analytics: The Emergence of a Discipline
Siemens, G. (2013) · American Behavioral Scientist · doi:10.1177/0002764213498851 · Cited by 1,284
Let’s not forget: Learning analytics are about learning
Gašević, D., Dawson, S., & Siemens, G. (2015) · TechTrends · doi:10.1007/s11528-014-0822-x · Cited by 1,049
Self-citationCourse signals at Purdue: using learning analytics to increase student success
Arnold, K. E., & Pistilli, M. D. (2012) · Proceedings of the 2nd International Conference on Learning Analytics and Knowledge · doi:10.1145/2330601.2330666 · Cited by 987
Gašević, D., Dawson, S., Rogers, T., & Gašević, D. (2015) · The Internet and Higher Education · doi:10.1016/j.iheduc.2015.10.002 · Cited by 767
Self-citationLockyer, L., Heathcote, E., & Dawson, S. (2013) · American Behavioral Scientist · doi:10.1177/0002764213479367 · Cited by 473
Self-citation(2012) · PubMed · Cited by 435
Using learning analytics to scale the provision of personalised feedback
Pardo, A., Jovanovic, J., Dawson, S., Gašević, D., & Mirriahi, N. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12592 · Cited by 425
Self-citationLearning analytics to unveil learning strategies in a flipped classroom
Jovanović, J., Gašević, D., Dawson, S., Pardo, A., & Mirriahi, N. (2017) · The Internet and Higher Education · doi:10.1016/j.iheduc.2017.02.001 · Cited by 376
Self-citationDrachsler, H., & Greller, W. (2016) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2883851.2883893 · Cited by 374
Research works printed but not linked: 10
- 2012, Learning Analytics: Moving from Concept to Practice
- 2012, School Enrollment and Work Status: 2011
- 2005, Academic Analytics: The Uses of Management Information and Technology in Higher Education, 12
- Long, P.D., Siemens, G., Conole, G. and Gašević, D. (Eds) (2011), Proceedings of the 1st International Conference On Learning Analytics And Knowledge (LAK’11), ACM, New York, NY.
- 2012, Big Data: The Next Frontier for Innovation, Competition and Productivity
- 2015, Code of Practice for Learning Analytics
- 2014, Improving the Quality and Productivity of the Higher Education Sector - Policy and Strategy for Systems-Level Deployment of Learning Analytics
- 2015, Preparing for the Digital University: A Review of the History and Current State of Distance, Blended, and Online Learning
- 2009, Institutional Data Management in Higher Education, 180
- 2015, The Analytics Landscape in Higher Education, 34
Cited by
Sorted by citations
Automatic feedback in online learning environments: A systematic literature review
Cavalcanti, A. P., Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y.-S., Gašević, D., & Mello, R. F. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100027 · Cited by 440
Self-citationJin, Y., Yan, L., Echeverria, V., Gašević, D., & Martinez-Maldonado, R. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2024.100348 · Cited by 452
Liu, M., Ren, Y., Nyagoga, L. M., Stonier, F., Wu, Z., & Yu, L. (2023) · Future in Educational Research · doi:10.1002/fer3.10 · Cited by 267
Recent advances in Predictive Learning Analytics: A decade systematic review (2012–2022)
Sghir, N., Adadi, A., & Lahmer, M. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-11536-0 · Cited by 238
Learning analytics in European higher education—Trends and barriers
Tsai, Y.-S., Rates, D., Moreno-Marcos, P. M., Muñoz-Merino, P. J., Jivet, I., Scheffel, M., Drachsler, H., Delgado Kloos, C., & Gašević, D. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103933 · Cited by 192
“Similarly, Prieto, Rodríguez-Triana, Martínez-Maldonado, Dimitriadis, and Gašević (2019) emphasise the need to reach a common understanding among stakeholders including teachers, developers and researchers.”
BackgroundSelf-citation
Metadata
- Authors
- Gasevic, D., Tsai, Y.-S., Dawson, S., & Pardo, A.
- Affiliations
- University of Edinburgh (GB)
- University of South Australia (AU)
- Venue
- The International Journal of Information and Learning Technology
- Publisher
- Emerald
- Published
- 2019-08-05
- Volume
- 36
- Issue
- 4
- Pages
- 342-353
- ISSN
- 2056-4880 (ISSN-L)
- OpenAlex
- W2950279021
- Cited by
- 103
- References
- 43
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 20 · 2023: 25 · 2022: 22 · 2021: 13 · 2020: 10 · 2019: 1
- FWCI
- 12.45
- Type
- journal article
- Language
- en
- Open access
- green
- research.monash.edu
- Licence
- Locations
- International Journal of Information and Learning Technology (publishedVersion)
- Monash University Research Portal (Monash University) (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- HAL (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Physical Sciences › Computer Science › Information Systems › Educational and Technological Research
- Keywords
- learning analytics, institutional adoption, higher education, data-informed decision making, innovation adoption, institutional change, socio-technical systems, educational technology, learning and teaching practices
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