Skip to main content

Advertisement

Log in

Let’s not forget: Learning analytics are about learning

  • Published:
TechTrends Aims and scope Submit manuscript

Abstract

The analysis of data collected from the interaction of users with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process. This promise motivated the emergence of the new research field, learning analytics, and its closely related discipline, educational data mining. This paper first introduces the field of learning analytics and outlines the lessons learned from well-known case studies in the research literature. The paper then identifies the critical topics that require immediate research attention for learning analytics to make a sustainable impact on the research and practice of learning and teaching. The paper concludes by discussing a growing set of issues that if unaddressed, could impede the future maturation of the field. The paper stresses that learning analytics are about learning. As such, the computational aspects of learning analytics must be well integrated within the existing educational research.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ali, L., Hatala, M., Gašević, D., & Jovanović, J. (2012). A qualitative evaluation of evolution of a learning analytics tool. Computers & Education, 58(1), 470–489. doi:10.1016/j.compedu.2011.08.030

    Article  Google Scholar 

  • Arnold, K. E., & Pistilli, M. D. (2012). Course signals at Purdue: using learning analytics to increase student success. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 267–270). New York, NY, USA: ACM. doi:10.1145/2330601.2330666

    Chapter  Google Scholar 

  • Bayne, S., & Ross, J. (2014). The pedagogy of the Massive Open Online Course: the UK view. The Higher Education Academy. Retrieved from https://www.heacademy.ac.uk/resources/detail/elt/the_pedagogy_of_the_MOOC_UK_view

  • Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In Proceedings of the ascilite 2014 conference. Dunedin, NZ.

  • Dawson, S., Gašević, D., Siemens, G., & Joksimovic, S. (2014). Current State and Future Trends: A Citation Network Analysis of the Learning Analytics Field. In Proceedings of the Fourth International Conference on Learning Analytics And Knowledge (pp. 231–240). New York, NY, USA: ACM. doi:10.1145/2567574.2567585

  • Elton, L. (2004). Goodhart’s Law and Performance Indicators in Higher Education. Evaluation & Research in Education, 18(1-2), 120–128. doi:10.1080/09500790408668312

    Article  Google Scholar 

  • Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2014). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicating learning success. Submitted to The Internet and Higher Education.

  • Gašević, D., Mirriahi, N., & Dawson, S. (2014). Analytics of the Effects of Video Use and Instruction to Support Reflective Learning. In Proceedings of the Fourth International Conference on Learning Analytics And Knowledge (pp. 123–132). New York, NY, USA: ACM. doi:10.1145/2567574.2567590

  • Gašević, D., Mirriahi, N., Dawson, S., & Joksimovic, S. (2014). What is the role of teaching in adoption of a learning tool? A natural experiment of video annotation tool use. Submitted for Publication to Computers & Education.

  • Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of a sophisticated mental model of a complex system. Contemporary Educational Psychology, 34(1), 18–29. doi:10.1016/j.cedpsych.2008.05.006

    Article  Google Scholar 

  • Hadwin, A. F., Nesbit, J. C., Jamieson-Noel, D., Code, J., & Winne, P. H. (2007). Examining trace data to explore self-regulated learning. Metacognition and Learning, 2(2-3), 107–124. doi:10.1007/s11409-007-9016-7

    Article  Google Scholar 

  • Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. doi:10.3102/003465430298487

    Article  Google Scholar 

  • Jayaprakash, S. M., Moody, E. W., Lauria, E. J. M., Regan, J. R., & Baron, J. D. (2014). Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative. Journal of Learning Analytics, 1(1), 6–47.

    Google Scholar 

  • Kovanović, V., Joksimović, S., Gašević, D., Siemens, G., & Hatala, M. (2014). What public media reveals about MOOCs? Submitted for Publication to British Journal of Educational Technology.

  • Liu, Z., Nersessian, N. J., & Stasko, J. T. (2008). Distributed cognition as a theoretical framework for information visualization. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1173–1180.

    Article  Google Scholar 

  • Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing Pedagogical Action Aligning Learning Analytics With Learning Design. American Behavioral Scientist, 57(10), 1439–1459. doi:10.1177/0002764213479367

    Article  Google Scholar 

  • Lust, G., Elen, J., & Clarebout, G. (2013). Students’ tool-use within a web enhanced course: Explanatory mechanisms of students’ tool-use pattern. Computers in Human Behavior, 29(5), 2013–2021. doi:10.1016/j.chb.2013.03.014

    Article  Google Scholar 

  • Macfadyen, L. P., & Dawson, S. (2012). Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan. Educational Technology & Society, 15(3).

  • McGill, T. J., & Klobas, J. E. (2009). A task-technology fit view of learning management system impact. Computers & Education, 52(2), 496–508. doi:10.1016/j.compedu.2008.10.002

    Article  Google Scholar 

  • McNamara, D. S., Graesser, A. C., McCarthy, P. M., & Cai, Z. (2014). Automated Evaluation of Text and Discourse with Coh-Metrix. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • OECD. (2013). Education at a Glance 2013: OECD Indicators. Retrieved from http://dx.doi.org/10.1787/eag-2013-en

  • Reimann, P., Markauskaite, L., & Bannert, M. (2014). e-Research and learning theory: What do sequence and process mining methods contribute? British Journal of Educational Technology, 45(3), 528–540. doi:10.1111/bjet.12146

    Article  Google Scholar 

  • Siemens, G., & Gašević, D. (2012). Special Issue on Learning and Knowledge Analytics. Educational Technology & Society, 15(3), 1–163.

    Google Scholar 

  • Tanes, Z., Arnold, K. E., King, A. S., & Remnet, M. A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education, 57(4), 2414–2422. doi:10.1016/j.compedu.2011.05.016

    Article  Google Scholar 

  • Trigwell, K., Prosser, M., & Waterhouse, F. (1999). Relations between teachers’ approaches to teaching and students’ approaches to learning. Higher Education, 37(1), 57–70. doi:10.1023/A:1003548313194

    Article  Google Scholar 

  • Verbert, K., Duval, E., Klerkx, J., Govaerts, S., & Santos, J. L. (2013). Learning Analytics Dashboard Applications. American Behavioral Scientist, 57(10), 1500–1509. doi:10.1177/0002764213479363

    Article  Google Scholar 

  • Wilson, T. D. (1999). Models in information behaviour research. Journal of Documentation, 55(3), 249–270. doi:10.1108/EUM0000000007145

    Article  Google Scholar 

  • Winne, P. H. (2006). How Software Technologies Can Improve Research on Learning and Bolster School Reform. Educational Psychologist, 41(1), 5–17. doi:10.1207/s15326985ep4101_3

    Article  Google Scholar 

  • Winne, P. H., & Hadwin, A. F. (1998). Studying as selfregulated learning. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.

    Google Scholar 

  • Zhou, M., & Winne, P. H. (2012). Modeling academic achievement by self-reported versus traced goal orientation. Learning and Instruction, 22(6), 413–419. doi:10.1016/j.learninstruc.2012.03.004

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dragan Gašević.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gašević, D., Dawson, S. & Siemens, G. Let’s not forget: Learning analytics are about learning. TECHTRENDS TECH TRENDS 59, 64–71 (2015). https://doi.org/10.1007/s11528-014-0822-x

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11528-014-0822-x

Keywords

Navigation