This post is an exercise in procrastination brought about by late afternoon writer’s block. I’m currently preparing a paper that examines a rare example of an institution-wide learning analytics implementation using a theoretical lens. The purpose of the paper is to contribute to the theoretical understanding of learning analytics implementation and to represent this as an initial set of design principles or heuristics for practitioners. However, I am noticing a fascinating irony in the research, an irony that is further reinforced by my experience with an enterprise-wide learning analytics implementation over the last five years.
Basically, I suspect the biggest barrier to organisation-wide learning analytics implementation is the organisation itself. I’m reminded of the oft cited quote:
“We have met the enemy and he is us”
Learning analytics, and particularly its implementation, seems to me to sit in an organisational no-mans-land. That it involves data and employs some information technology seems to see it pushed far too often in the direction of the IT department. But we know that this doesn’t work:
“All too frequently, LA is conceptualised as a technical solution to an education problem. As such oversight and management of LA is assigned to core administrative units (e.g. IT units) who establish the various rules and regulations guiding access to the data and adoption of the technologies”
(Dawson et al., 2018)
There seems to be a problem whereby we struggle to link what we know theoretically about learning analytics implementation, with how we approach implementation. For example:
- We know that learning analytics is, by and large, an applied research field (Dawson, Gašević, Siemens, & Joksimovic, 2014)
- We know that learning analytics is a multidisciplinary concept (Dawson et al., 2018)
- We know that one-size-fits-all approaches are fundamentally flawed with learning analytics (Gašević, Dawson, Rogers, & Gasevic, 2016)
- We know that our organizations are mired in technical, social and cultural challenges when it comes to learning analytics adoption (Macfadyen & Dawson, 2012)
So if we know these things as a sector, why is it that the gap between our research-based knowledge of learning analytics and our knowledge of how to implement learning analytics continues to grow (Colvin, Dawson, Wade, & Gasevic, 2017), and why do we see these mistakes repeated? I am wondering just how much of an impact our organisational structures / arrangements have on something like learning analytics, which needs to span our internal organisational boundaries? I also wonder if my anecdotal knowledge of the politicking that happens with learning analytics implementation across the sector, is somehow linked with this apparent homelessness?
If we are struggling to apply what we know when we conceptualise our learning analytics implementations, it follows that we will struggle to implement an approach that favours learning and adaptation; something that is needed while learning analytics remains generally undertheorised (Dawson, Mirriahi, & Gasevic, 2015).
Just a thought.
Colvin, C., Dawson, S., Wade, A., & Gasevic, D. (2017). Addressing the Challenges of Institutional Adoption. In C. Lang, G. Siemens, A. Wise, & D. Gasevic (Eds.), Handbook of Learning Analytics (Vol. 1, pp. 281 – 289). Australia: Society for Learning Analytics Research.
Dawson, S., Gašević, D., Siemens, G., & Joksimovic, S. (2014). Current state and future trends: A citation network analysis of the learning analytics field. Paper presented at the Proceedings of the fourth international conference on learning analytics and knowledge.
Dawson, S., Poquet, O., Colvin, C., Rogers, T., Pardo, A., & Gasevic, D. (2018). Rethinking learning analytics adoption through complexity leadership theory. Paper presented at the Proceedings of the 8th International Conference on Learning Analytics and Knowledge.
Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education, 28, 68-84.
Macfadyen, L. P., & Dawson, S. (2012). Numbers Are Not Enough. Why e-Learning Analytics Failed to Inform an Institutional Strategic Plan. Journal of Educational Technology & Society, 15(3), 149-163.