Data Sharing – Need and Feasibility (LADS14)
Many applications of learning analytics require large scale data for educational data mining techniques. Although the data from an institutional learning platform or a MOOC may be considered large, the scale and coverage of such datasets may sometimes be insufficient to allow the potential of learning analytics to be fully realised. This challenge applies to both learning science research and to potential products and services built around data generated during learning activities. To move beyond inefficient ad-hoc bilateral institutional arrangements with limited returns is not a trivial undertaking.
The technical possibilities for data sharing range from a fully-specified centralised shared repository to a highly decentralised approach based around a paradigm such as Linked Data and an appropriate choice of data licence. The practical feasibility of data sharing for learning analytics is, however, a great deal more complex than the selection of a good technical architecture for data sharing and it is imperative that initiatives intended to work towards a data sharing platform – comprising technical, operational, business, policy, and governance factors – have a better basis on evidence than has so far been established and related to the problem at hand.
The intention of this workshop is to gain contributions of evidence (both project successes and limitations), contextualised to learning analytics data sharing, and to critically assess the feasibility of various options with a view to developing a roadmap for action by multiple stakeholders. The roadmap is intended to be a bridge between research and practical action and encompass the multiple concerns indicated above: technical, operational, business, policy, and governance.
The workshop organisers believe that process of data sharing, and the reasons for doing so, are not to be understood purely theoretical point of view. Consequently, the workshop will seek to promote a user-centric perspective along-side the prime facie perspective of “data sharing”.
Key Questions to be addressed with respect to learning analytics data sharing:
- What do we, as a community, believe is feasible? (and what evidence is available)
- What would a practical roadmap for progress look like?
There are many facets to discuss, including:
- Scope – what kind of data is it most beneficial to share, and for what educational purpose?
- Technical architectures for data sharing.
- Interoperability and standards.
- Ethical aspects of data sharing and privacy (some LACE articles on privacy).
- Sustainability of collaborative initiatives or shared infrastructure.
- Business models for data-driven services.
The workshop seeks to exploit the opportunity of the co-location of the i-KNOW and ECTEL conferences to address both the semantic web community and the TEL community to enable a fruitful discourse around educational data sharing between both communities.
This workshop should be of interest to a spectrum of stakeholders within these communities:
- Researchers who wish to bring their results forward to a critical debate centred on real-world feasibility or want to understand which problems are in need of their attention.
- Research leaders who want to develop scalable, sustainable, and efficient multi-lateral collaborations based on learning data.
- Data entrepreneurs seeking the next opportunity to develop a product or service based around learning data.
- Policy-makers developing strategies, and investment planning for the common good.
Join us in Graz for the 1st Learning Analytics Data Sharing Workshop (LADS14), part of the Ninth European Conference on Technology Enhanced Learning, EC-TEL 2014. To be held on Tuesday morning, 16.09.2014.
Late news: after lunch, there will be an additional workshop on roadmapping actions to support the European Learning Analytics community.
Morning Session – Data Sharing, LADS14
|09:00-10:00||Welcome and introduction.Presentation of examples:
– summary of data sharing examples collated by the LACE project (a working paper is available – pdf)
– the EMMA project talking about MOOCs, data, and analytics (supporting paper by Tammets & Brouns – pdf- and slides)
– Learning Analytics with DEEDS Simulator, benefits and challenges of data sharing (slides on slideshare)
Open floor discussion of examples.
|10:30-12:30||Presentation on strategies for dealing with privacy by Tore Hoel (slides on slideshare).Group work to explore:
– desirable ideas for the future of learning analytics where data sharing would have a role
– obstacles to progress
– ways of avoiding or overcoming the obstaclesPlenary: communicating group work and discussion
Afternoon Session – Developing the European Learning Analytics community
|13:30-15:30||Welcome and introduction.Group discussion of roadmaps of action to support the development of the Learning Analytics community, covering:
– workplace learning and development
– higher education
|15:45-17:30||Plenary presentation of roadmaps and discussion of actions to strengthen the European Learning Analytics community.|
|17:30||End of Workshops|
- Adam Cooper, University of Bolton, UK.
(corresponding chair, email firstname.lastname@example.org)
- Tore Hoel, Oslo and Akershus University College, NO.
- Hendrik Drachsler, Open University Nederlands, NL.
After the Workshop
The LACE project will synthesise the outcomes from the workshop as a tentative feasibility analysis and roadmap to complete the online resource. We will be continuing to work on the topic of interoperability and data sharing for learning analytics after the workshop – LACE is funded to March 2016 – through a series of online and face-to-face events and publications.
LACE is grateful to the EC-TEL programme committee for the opportunity to run a workshop at EC-TEL 2014.