H817-20b – Block 4 – Week 21 – Activity 5
Make a list in your learning journal or blog of the main points you would share with someone in your context, or in a context that you know well, who had asked for a brief introduction to learning analytics.
Further to studying the paper by Ferguson (2020) I would initially share the basic definition of Educational Data Mining (EDM). This would involve a brief explanation of the use of data sets too large to be handled manually.
I would introduce them to the Social Networks Adapting Pedagogical Practice (SNAPP). This tool is used to analyse interactions in networks. It can help to identify those students who are socially isolated on a course.
I could prepare a short list of resources related to the Signals system. We have used such traffic light systems before on attendance data so this may be an area to expand our understanding of the wider data set in the college.
Challenge 2 would be a suitable discussion point for future widening of data uses.
“9.2 Challenge 2: develop methods of working with a wide range of datasets in order to optimise learning environments Understanding and optimising the environments in which learning occurs introduces a second challenge. Increasingly, learners will be looking for support from learning analytics outside the VLE or LMS, whilst engaged in lifelong learning in open, informal or blended settings. This will require a shift towards more challenging datasets and combinations of datasets, including mobile data, biometric data and mood data. In order to solve the problems faced by learners in different environments, researchers will need to investigate what those problems are and what success looks like from the perspective of learners. “
I would also highlight the importance of the ethical guidelines to control expectations about how student data can be used without infringing their privacy.
References:
Ferguson, R. (2012) ‘Learning analytics: drivers, developments and challenges’, International Journal of Technology Enhanced Learning (IJTEL), vol. 4, nos. 5/6, pp. 304–17 (Online) Available at http://oro.open.ac.uk/ 36374/ (Accessed 3rd July 2020).