Consultant (LRE Whitepaper)

Job Experience

Job Location

Expiration Date

24 Jul 2018

The Learning Resource Exchange Subcommittee (LRE Subcommittee) of European Schoolnet is a group of European Ministries of Education and other organizations.  The LRE Subcommittee promotes and supports the creation, discovery, exchange, and (re)use of Open Educational Resources (OER) and Open Educational Practices. It is open to regional and local education authorities and private for-profit and non-profit organizations that wish to utilise LRE services and take advantage of available benefits. Members participate in European and international projects investigating the impact and best practices of OERs.  To foster networking opportunities, the LRE Subcommittee collaborates closely with EdReNe, a network of European repository nodes and stakeholders dedicated to the development of recommendations and exchange of expertise. Together these two networks participate in face-to-face meetings and online seminars which provide opportunities for members to keep up-to-date on the latest developments in the field and learn about new and ongoing initiatives across Europe.

As part of its activities, the LRE Subcommittee wishes to work with an independent consultant who will help them identify and review best practices in the use of artificial intelligence (AI) and machine learning (ML) by educational portals and OER repositories in the context of K-12 education.

Description of Work:

This short piece of work will draw on the existing expertise of the consultant related to AI, ML, educational portals, data privacy, etc.  It will also require desk research exploring the ways state-of-the-art AI and ML are already being used or can be used by educational portals and learning resource repositories to better serve teachers and pupils (e.g., personalization).  Some possible questions to pursue are: What are the expected benefits? What are the risks and opportunities for public education actors?  What are the main pitfalls and how to avoid them?  What are the recommended best practices?  Optimally, the desk research will shed light on the interconnections between a number of issues relevant to ML, such as the potential problems with obtaining and reusing data from teachers and pupils in the context of GDPR, technical challenges posed by the acquisition of quality data or the identification of features in the data especially relevant for education.


The study is expected to produce the following outcomes:

  1. A 15-page whitepaper (not including the bibliography) summarizing the main results of the study and
  2. The presentation of these results by the consultant during an EdReNe webinar.

The whitepaper will cover the following:

  • A brief overview of the AI and ML techniques potentially relevant to K-12 education and more specifically to educational portal and repositories of OERs;
  • Examples of concrete applications of these techniques and their expected benefits for educational portals and repositories of OERs;
  • List of potential (educational, legal, organisational, technical, etc.) problems to expect when implementing these techniques and recommended ways to address them (ideally illustrated with examples of best practices);
  • A comprehensive bibliography referencing relevant readings and studies that can be used in further developments of these topics.

Two versions of the whitepaper will be produced:

  1. A complete draft will be produced two months after the start of the project to check that the work is aligned with the expectations of the Subcommittee;
  2. A final version will be delivered one month later that addresses the feedback received after the first draft.

Finally, the consultant will present the results of their work during a one-hour EdReNe webinar organized as soon as possible after the delivery of the final version of the whitepaper.

Fee: European Schoolnet can offer a fee of €3,000 for this work payable on completion of the EdReNe webinar.  In case the consultant cannot carry out the assignment in full, the fee will be revised accordingly.

Timetable for work: August – November 2018


David Massart:

Elena Shulman:

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