More on Learning Analytics and Disabled Students

I have now submitted two papers that cover Learning Analytics and Disabled Students.

1. Cooper, M., Sloan, D., Kelly, B. and Lewthwaite, S., 2012. A challenge to web accessibility metrics and guidelines: putting people and processes first. In: W4A 2012: 9th International Cross-Disciplinary Conference on Web Accessibility, 16-18 April 2012, Lyon.

2. Cooper, M., Ferguson, R., Wolff, A., 2012 What Can Learning Analytics Contribute to Disabled Students’ Learning and to Accessibility in e-Learning Systems? In HCI2012:  26th Annual Conference of the Specialist HCI group of the BCS, 12th-14th September 2012, Birmingham, UK.

Paper 1. is available for download from: Paper 2. is still under peer review.

The more I think about the topic the more I am sure there is significant potential here.

This arises from the fact that at a university, for example, it is possible to know which users (students) have a disability and indeed in many cases what disability or functional impairment.  Thus the behaviour and attainment of disabled students can be monitored in comparison to the general student population across the e-learning provision, in many cases in real-time.  Therefore modules, or part of modules that seem to be problematic for disabled students can be identified. Learning Analytics is unlikely to be able to identify what the problem is, but by indicating where it is, can trigger further investigation and remedial action. Such problems may be in the learning design, the technical accessibility, the assessment, etc.

Do readers of this blog have any examples envisaged or implemented of such approaches they would like to share?  This area is just under consideration at the Open University where I work.


One thought on “More on Learning Analytics and Disabled Students

  1. Martyn, I’m at IMS meetings this week (the Learning Impact conference) and learned about this project that might be of interest:

    Degree Compass

    They are using 10 years of grade data to understand which courses are the key indicators for success in various fields of study. Combining that with an individual student’s entrance exam scores and other course grades, they can predict how well a student will do in a variety of different courses.

    You can imagine adding in PNP or disability status data and getting even better predictions — though in some ways that is the opposite of what you are proposing, since you want to remediate the courses, not the students 🙂


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