“What is learning analytics anyway?”
I’ve answered this question a lot since starting my PhD 5 weeks ago, with varying degrees of eloquence.
My go-to definition when writing assignments for my MA was:
“LEARNING ANALYTICS is 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”Society of Learning Analytics Research (n.d)
My operational – since that’s my background, rather than academic – answer is that Learning Analytics is looking at the data produced by online learning as it happens, and responding to that information in as close to real time as possible. The response is an action that leads to improvement in learning.
A simple example: if 100 students take an online quiz and 98 of them fail question 4 but pass overall, the tutor can investigate. Was the information needed for question 4 adequately covered in the course? Was the wording of question 4 clear? Is the answer to question 4 correctly coded in the quiz? Immediate action (covering the information for question 4 in the next lesson perhaps) means no knowledge gap, and the issue can be rectified for the next cohort.
My draft thesis title is Data driven reflection in professional learning: Learning design to engage final year student Chartered Accountants in learning analytics. I want to investigate the role of actionable feedback on both performance in mock exams and engagement with course materials. Part of this study will be creating a tool that uses marking data to give students real-time consistent and actionable feedback.
I’ve started my literature review by reading “Utilizing Learning Analytics to Support Study Success” (Ifenthaler et al, (eds) 2019). This extensive and relevant collection covers learning theory, implementation, and challenges both in depth and in an accessible way. I am still experimenting with how I will take useful notes on long (300+ pages) texts (I will use Mendeley for shorter articles and papers) – for this book I generated 44 pages of typed notes. These notes include follow up reading – 51 references in the edited version, which I now need to prioritise.
A useful exercise was to create a list of ‘key phrases’ from the notes I made – words or phrases that come up time and time again. I’ll use this to start to structure my literature review. In a moment of creativity (or perhaps procrastination) I dropped them into worditout.com and generated this word cloud.
It certainly shows the complexities of this field of study.
Now, onwards with that list of reading!
Ifenthaler, D., Mah, D., & Yau, JY. (eds) (2019) Utilizing Learning Analytics to Support Study Success, Switzerland, Springer Nature Switzerland AG. Available at https://ebookcentral.proquest.com/lib/open/detail.action?docID=5639430# (Accessed 5 November 2021).