introduction to the learning analytics data sharing workshop at ec-tel 2014

Learning Analytics Data SharingWorkshop

Adam Cooper, Cetis, U. Bolton (UK)ECTEL 2014, Graz, 2014-09-16

#laceproject

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Welcome!

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LACE = Learning Analytics Community Exchange• An EC Seventh Framework Programme

Coordination and Support Action• Objectives

– Promote knowledge creation and exchange– Increase the evidence base– Contribute to the definition of future directions– Build consensus on interoperability and data sharing

• Strands of work:– Schools– Workplace (especially “smart manufacturing”)– Higher Education– Interoperability and data sharing

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We do this by:

Collaborating with others to:• Run workshops and other discourse-centred events• Present at conferences (academic and practitioner)• Write articles and white papers

Creating and managing a knowledge base, the LACE Evidence Hub

Listening, thinking, studying, and sharing...

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Extra workshop – this afternoon

• Roadmapping actions to develop the European Learning Analytics Community– Research– Practice– Policy– Suppliers/Vendors

• What role for LACE, and for others?

• Covering all LACE strands of work (and more?)

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Morning Agenda

09:00-10:00• Welcome and introduction• Presentation of examples[coffee]10:30-12:30 • Presentation on strategies for dealing with privacy.• Group work to explore:

– desirable ideas– obstacles to progress and ways of avoiding or overcoming them

• Plenary: communicating group work and discussion

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Before Coffee:Presenting and Discussing Examples

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“Data Sharing Platform” – Workshop Scope

• Data– Focus on data about a person or their actions

• Sharing– Between organisations

• Platform– Technical – architecture, infrastructure, standards– Non-technical – business/sustainability models, policies, legal

Research and Delivery

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Some Examples in Brief

• PSLC DataShop• PAR Framework• InBloom• Open Academic Analytics Initiative• Open Knowledge Foundation/CKAN

For more details (but still summaries), see our working paper (PDF):http://bit.ly/wp7-dse

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PSLC DataShop

• School level• Research focus• ITS and cognitive theories – “knowledge components”• IRB/human subjects research.

– De-identification

• Repository, open and closed• Grant funded, plausibly sustainable

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PAR Framework

• Higher Education• Intervention focus

– Learner-specific– Strategies & benchmarks

• A “collaborative”, a centre of expertise.– Constrained sharing

• IRB/human subjects research• Grant funded, plausibly sustainable

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InBloom

• School level• Attainment tracking and individualised learning pathways

– >400 data elements, CEDS

• Multiple parties– InBloom– School Districts, States– Schools– TEL providers

• Grant funded, FAILED– No breaches, nothing “evil”– Failure of trust

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Open Academic Analytics Initiative• A project• Model sharing

Open Knowledge Foundation/CKAN• Open data, Open Education• CKAN – Comprehensive Knowledge Archive Network• Open Source, extensible• Data and metadata

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European MOOCs – Project EMMA

• A paper describing the EMMA approach to MOOCs, Learning Analytics, and learner data – see laceproject.eu/lads14

• Short oral presentation from Kairit Tammets, Tallinn UniversityKairit@tlu.ee

Learning Analytics with DEEDS Simulator –benefits and challenges of data sharing

Mehrnoosh Vahdat

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Before Lunch:Group Discussions on Feasibility

Strategies for Dealing with Privacyin the context of LA• Tore Hoel• Oslo and Akershus University College of Applied Sciences • Norway• September 2014

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Group Work – Task 1

Group discussion to generate some ideas for future examples.• be creative but not very futuristic• consider variations on existing ideas.

Select 2 ideas that interest the group, and which would be attractive to stakeholders. For each idea, note down:

• the intended educational aims and benefits– including from a learner perspective

• the kind, scale and variety of data involved• what motivates sharing

– rather than a single organisation

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Group Work – Task 2

Discussion of the feasibility of the ideas1. What are the most important challenges/obstacles to realising

the idea?– Consider technical, business/sustainability, and privacy/ethical and legal

aspects.– Is there evidence to demonstrate the obstacle?

2. How might these obstacles be avoided or overcome?– These could be technical features, working practices, etc, but they could

also be suggestions for how the design process could be carried out (e.g. design principles or design method).

– Is there any evidence to demonstrate this, possibly in a different context?

3. What actions, by which stakeholders, would be needed to overcome the obstacles and to make the idea from task 1 be feasible?

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A SuggestionThe Idea Obstacles Overcoming &

Avoiding

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Next Steps...

• We will write-up and synthesise the ideas and conclusions– laceproject.eu/lads14– Workshop papers and slides uploaded– Please add your reflections

• Come and talk with us about LACE generally– Afternoon community development road-mapping session– Leave your details

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“Learning Analytics Data Sharing Workshop” by Adam Cooper (Cetis, University of Bolton) was presented at ECTEL 2014 in Graz on 16 September 2014.

a.r.cooper@bolton.ac.uk

This work was undertaken as part of the LACE Project, supported by the European Commission Seventh Framework Programme, grant 619424.

These slides are provided under the Creative Commons Attribution Licence: http://creativecommons.org/licenses/by/4.0/. Some images used may have different licence terms.

www.laceproject.eu@laceproject