Skip to main content

Learning Analytics Challenges to Overcome in Higher Education Institutions

  • Chapter
  • First Online:

Abstract

While a large number of scientific publications explain the development of prototypes or the implementation of case studies in detail, descriptions of the challenges and proper solutions when implementing learning analytics initiatives are rare. In this chapter, we provide a practical tool that can be used to identify risks and challenges that arise when implementing learning analytics (LA) initiatives and discuss how to approach these to find acceptable solutions. In this way, implementers are given the opportunity to handle challenges early on and avoid being surprised at a critical moment in the project, which will save time, resources, and effort. We are aware that all aspects needed to successfully carry out learning analytics initiatives are co-dependent. Nonetheless, we identified and categorized the criteria necessary for implementing successful learning analytics initiatives. We conclude this chapter with an overview of the challenges faced and possible approaches that can be taken to facilitate the successful implementation of learning analytics.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Berg, A. M., Mol, S. T., Kismihók, G., & Sclater, N. (2016). The role of a reference synthetic data generator within the field of learning analytics. Journal of Learning Analytics, 3(1), 107–128.

    Article  Google Scholar 

  • Campbell, J. P. (2007). Utilizing student data within the course management system to determine undergraduate student academic success: An exploratory study. PhD, Purdue University, West Lafayette, IN.

    Google Scholar 

  • Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, 18(6), 683–695.

    Article  Google Scholar 

  • Cormack, A. N. (2016). A data protection framework for learning analytics. Journal of Learning Analytics, 3(1), 91–106.

    Article  Google Scholar 

  • De Laet, T., Broos, T., Verbert, K., van Staalduinen, J.-P., Ebner, M. & Leitner, P. (2018). Involving stakeholders in learning analytics: Opportunity or threat for learning analytics at scale? In Proceedings 8th international conference on learning analytics & knowledge (pp. 602–606). Sydney.

    Google Scholar 

  • Drachsler, H., & Greller, W. (2016). Privacy and analytics - it’s a DELICATE issue: A checklist to establish trusted learning analytics. In Proceedings of the 6th international conference on learning analytics and knowledge (pp. 89–96). https://doi.org/10.1145/2883851.2883893

  • Duval, E. (2012). Learning analytics and educational data mining, In Erik Duval’s weblog, 30 January 2012. Retrieved from https://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/. Accessed 16 March 2018.

  • Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning (IJTEL), 4(5/6), 304–317. https://doi.org/10.1504/IJTEL.2012.051816

    Article  Google Scholar 

  • Ferguson, R., Hoel, T., Scheffel, M., & Drachsler, H. (2016). Guest editorial: Ethics and privacy in learning analytics. Journal of learning analytics, 3(1), 5–15. https://doi.org/10.18608/jla.2016.31.2

    Article  Google Scholar 

  • Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64–71.

    Article  Google Scholar 

  • Hoel, T., & Chen, W. (2016). Privacy-driven design of learning analytics applications - exploring the design space of solutions for data sharing and interoperability. Journal of Learning Analytics, 3(1), 139–158.

    Article  Google Scholar 

  • Johnson, L., Adams, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2012). The NMC horizon report: 2012 higher education edition. The New Media Consortium.

    Google Scholar 

  • Khalil, M., & Ebner, M. (2015). Learning analytics: principles and constraints. In Proceedings of world conference on educational multimedia, hypermedia and telecommunications (pp. 1326–1336).

    Google Scholar 

  • Khalil, M., & Ebner, M. (2016). De-identification in learning analytics. Journal of Learning Analytics, 3(1), 129–138.

    Article  Google Scholar 

  • Laan, S. (2011). IT infrastructure architecture: Infrastructure building blocks and concepts. Morrisville, NC: Lulu Press.

    Google Scholar 

  • Lang, C., Macfadyen, L. P., Slade, S., Prinsloo, P., & Sclater, N. (2018, March). The complexities of developing a personal code of ethics for learning analytics practitioners: Implications for institutions and the field. In Proceedings of the 8th international conference on learning analytics and knowledge (pp. 436–440). ACM.

    Google Scholar 

  • Leitner, P., Broos, T., & Ebner, M. (2018). Lessons learned when transferring learning analytics interventions across institutions. In Companion proceedings 8th international conference on learning analytics & knowledge (pp. 621–629). Sydney.

    Google Scholar 

  • Leitner, P., & Ebner, M. (2017). In P. Zaphiris & A. Ioannou (Eds.), Learning and collaboration technologies. Technology in Education: 4th international conference, LCT 2017, held as part of HCI international 2017, Vancouver, BC, Canada, July 9–14, 2017, proceedings, part II (pp. 293–301). Cham, Switzerland: Springer.

    Chapter  Google Scholar 

  • Leitner, P., Khalil, M., & Ebner, M. (2017). Learning analytics in higher education - a literature review. In Learning analytics: Fundaments, applications, and trends (pp. 1–23). Cham, Switzerland: Springer.

    Google Scholar 

  • Long, P. & Siemens, G., (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 30. Retrieved from https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education. Accessed 16 March 2018.

  • Macfadyen, L. P., Dawson, S., Pardo, A., & Gasevic, D. (2014). Embracing big data in complex educational systems: The learning analytics imperative and the policy challenge. Research & Practice in Assessment, 9, 17–28.

    Google Scholar 

  • Murray, P. M. (1990). The history of informed consent. The Iowa Orthopaedic Journal, 10, 104–109.

    Google Scholar 

  • Prinsloo, P., & Slade, S. (2015). Student privacy self-management: Implications for learning analytics. In Proceedings of the fifth international conference on learning analytics and knowledge (pp. 83–92). New York: ACM.

    Chapter  Google Scholar 

  • Prinsloo, P., & Slade, S. (2016). Student vulnerability, agency and learning analytics: An exploration. Journal of Learning Analytics, 3(1), 159–182.

    Article  Google Scholar 

  • Rodríguez-Triana, M. J., Martínez-Monés, A., & Villagrá-Sobrino, S. (2016). Learning analytics in small-scale teacher-led innovations: Ethical and data privacy issues. Journal of Learning Analytics, 3(1), 43–65.

    Article  Google Scholar 

  • Romero, C., & Ventura, S. (2013). Data mining in education. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 3(1), 12–27.

    Google Scholar 

  • Sclater, N. (2016). Developing a code of practice for learning analytics. Journal of Learning Analytics, 3(1), 16–42.

    Article  Google Scholar 

  • Siemens, G., Gasevic, D., Haythornthwaite, C., Dawson, S., Buckingham Shum, S., Ferguson, R., … Baker, R. S. J. D. (2011). Open learning analytics: An integrated & modularized platform. Proposal to design, implement and evaluate an open platform to integrate heterogeneous learning analytics techniques. Society for Learning Analytics Research.

    Google Scholar 

  • Steiner, C. M., Kickmeier-Rust, M. D., & Albert, D. (2016). LEA in private: A privacy and data protection framework for a learning analytics toolbox. Journal of Learning Analytics, 3(1), 66–90.

    Article  Google Scholar 

  • Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education---challenges and policies: A review of eight learning analytics policies. In Proceedings of the seventh international learning analytics & knowledge conference (pp. 233–242). New York: ACM.

    Chapter  Google Scholar 

Download references

Acknowledgments

This research project is co-funded by the European Commission Erasmus+ program, in the context of the project 562167EPP-1-2015-1-BE-EPPKA3- PI-FORWARD. Please visit our website http://stelaproject.eu.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philipp Leitner .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Leitner, P., Ebner, M., Ebner, M. (2019). Learning Analytics Challenges to Overcome in Higher Education Institutions. In: Ifenthaler, D., Mah, DK., Yau, J.YK. (eds) Utilizing Learning Analytics to Support Study Success. Springer, Cham. https://doi.org/10.1007/978-3-319-64792-0_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64792-0_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64791-3

  • Online ISBN: 978-3-319-64792-0

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics