Posts Tagged JRC

eTwinning: Seville

JRCI am just back from an expert workshop held at the European Commission’s Joint Research Centre (JRC) in Seville.

The EU has a very large database, covering 12 years, related to a European-wide project called etwinning. This project puts teachers in touch with each other across Europe so that they can share ideas and innovation, develop their professional and digital skills and, specifically, join together to develop and carry out projects involving their pupils. The database covers activity and interactions on that platform by many thousands of individual teachers.

The JRC is interested in using this dataset to generate actionable insights that can help teachers and learners across Europe. The expert workshop brought together researchers from across Europe to discuss different ways of doing this. The participants brought many different perspectives to the event – some had worked with the platform for years, some came from Ministries of Education, others had explored large educational datasets in the past or had organised large studies.

Together, we identified different questions that the database could help to answer, and discussed ways in which it could be related to external data sources.



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Research Evidence on the Use of Learning Analytics: Implications for Education Policy

Report coverThe final report on our study of learning analytics for European educational policy (LAEP) is now out.

Research Evidence on the Use of Learning Analytics: Implications for Education Policy brings together the findings of a literature review; case studies; an inventory of tools, policies and practices; and an expert workshop.

The report also provides an Action List for policymakers, practitioners, researchers and industry members to guide work in Europe.

Learning Analytics: Action List

Policy leadership and governance practices

  • Develop common visions of learning analytics that address strategic objectives and priorities
  • Develop a roadmap for learning analytics within Europe
  • Align learning analytics work with different sectors of education
  • Develop frameworks that enable the development of analytics
  • Assign responsibility for the development of learning analytics within Europe
  • Continuously work on reaching common understanding and developing new priorities

Institutional leadership and governance practices

  • Create organisational structures to support the use of learning analytics and help educational leaders to implement these changes
  • Develop practices that are appropriate to different contexts
  • Develop and employ ethical standards, including data protection

Collaboration and networking

  • Identify and build on work in related areas and other countries
  • Engage stakeholders throughout the process to create learning analytics that have useful features
  • Support collaboration with commercial organisations

Teaching and learning practices

  • Develop learning analytics that makes good use of pedagogy
  • Align analytics with assessment practices

Quality assessment and assurance practices

  • Develop a robust quality assurance process to ensure the validity and reliability of tools
  • Develop evaluation checklists for learning analytics tools

Capacity building

  • Identify the skills required in different areas
  • Train and support researchers and developers to work in this field
  • Train and support educators to use analytics to support achievement


  • Develop technologies that enable development of analytics
  • Adapt and employ interoperability standards

Other resources related to the LAEP project – including the LAEP Inventory of learning analytics tools, policies and practices – are available on Cloudworks.

The report is cited in the 2018 Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on the Digital Education Plan

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Big data for policy

JRC Building, SevilleOn 22 September, Adam Cooper and I (from the LAEP project) were invited to attend ‘Big Data for policy: how safe is it to surf the next Big Wave?‘ This workshop was organised by a section of the European Commission – the Information Society of the Joint Research Centre: Institute for Prospective Technological Studies (or the IS Unit of the JRC-IPTS – still quite a mouthful!)

The European Commission defined a new strategy on Big Data last year, with the aim of supporting and accelerating the transition towards a data-driven economy in Europe. This links up with other Euro strategies such as open data, cloud computing, high-performance computing and access to scientific data. The workshop in Seville was designed to present case studies of work in various sectors on Big Data, and to bring together the views of experts from industry, policy makers and academia.

The case studies came from countries around the world. I found three of them particularly interesting in terms of the scale and scope of what can be done with Big Data.

  • Big Data for Development: New Opportunities for Emerging Markets (Rohan Samarajiva, CEO LirneAsia, Sri Lanka). Rohan talked, among other things, about how mobile phone use can be employed as a gauge of population movement, and to identify different population groupings within Sri Lanka. He blogged about the event here, and his slides are here.
  • Setting the Scene: EUROSTAT (Albrecht Wirthmann, EUROSTAT). Among the things Albrecht talked about were projects on mobile phone data and flight reservation data as sources for tourism and population statistics. Mobile phone data appears to give a more reliable picture of who is where than, for example, accommodation statistics, ferry passenger data, household survey data or border control data. His presentation can be downloaded here.
  • Data for Development: An Emerging Opportunity (Nicolas De Cordes, Orange, France). Nicolas described work by Orange to reuse technical network management data, creating strongly anonymous data samples that can be used by researchers to help with countries’ development issues. This, for example, enables them to model the spread of diseases, optimising the location of hospitals to improve medical help. His presentation can be downloaded here.


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