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This is another option for an Overview slide.
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SoLAR storm 25 10-12 - learning analytics - disabled students - accessibility - mc - slideshare
WHAT CAN LEARNING/ACADEMIC ANALYTICS CONTRIBUTE TO DISABLED STUDENTS’ LEARNING; AND TO ACCESSIBILITY IN E-LEARNING SYSTEMS? Martyn Cooper (OU - IET) email@example.com Learning Analytics symposium A SoLAR Storm event hosted by The Open University 1.25-4.30pm BST, Thursday 25 October 2012
Programme• 1.25pm BST Welcome from Simon Buckingham Shum• 1.30 pm BST Bieke Schreurs from OU NL will talk about her work in progress as an intern developing social network analytics for the SocialLearn project, together with Maarten de Laat and Chris Teplovs• 2.00pm BST Martyn Cooper: What Can Learning/Academic Analytics Contribute to Disabled Students’ Learning and to Accessibility in e-Learning Systems?• 2.30pm BST Gill Kirkup: Data Wrangling – Bridging the Gap between Analytics and Users• 3.00pm BST Denise Whitelock: Good Pedagogical Practice Driving Learning Analytics: OpenMentor, Open Comment and SAFeSEA• 3.30pm BST Discussion
LA/AA for DisabledStudents/AccessibilityA New Area of Work –since Dec 2011
Overview Explore the potential for improving accessibility Enhanced support for disabled students Issues
Accessibility Case Study• Accessibility refers here to properties of VLEs and Learning Recourses that make them useable by disabled students• The OU currently (Sep 2012) has 17,000+ students declaring a disability
In last week:Analysis of completion and passrates• Disabled students vs. those not declaring a disability• Data visualization (shard diagrams)• % of students on all modules with 10+ disabled students completing / passing (2010/11)• Supported by IET’s Student Statistics Team – thanks to Naomi Jeffery
Case Study: Support for disabled students (dashboards)ScenarioKris is a disabled student who has access to adashboard of analytics that provide him withfeedback when he is at his computer or using amobile device. He has set the dashboard tosend him a weekly summary of his activity onuniversity sites and on a set of external siteswhere he has chosen to share his data with theanalytics system. He receives basic statistics onattendance, participation and marks on hisformal assignments and exams. He receivespersonalised recommendations suggestingresources and contacts available at his locationand relevant to his range of learning interests.However, what he finds most useful forreflection are the visual ‘mirrors’ that thesystem presents to him, plus suggestions ofways in which he might become a more The Learning Analytics Cycleeffective, strategic learner.
Discussion• What we can learn from LA about disabled students?• How else might approaches enhance accessibility• Issues?
Who’s Who Lead Contact information Martyn Cooper firstname.lastname@example.org (IET) Rebecca Ferguson (IET) Annika Wolff (KMi) Naomi Jeffery (IET Student Survey & Statistics Team)
Summary• Academic analytics has potential to identify where remedial action on accessibility might be needed – promotes continued improvement!• Any learning analytics advantage for students should be extended to disabled students• Specialist disability support can be brought to bear in a timely fashion for disabled students
Resources• Martyn’s Blog: http://martyncooper.wordpress.com/• LinkedIn Group: “Learning Analytics for Accessibility” http://tinyurl.com/csyklmd• This slide deck and related resources: Slide Share (tbc)