The highlights, activities and outputs of the UNESCO Chair on Open Technologies for Open Educational Resources and Open Learning at the Jožef Stefan Institute (Slovenia) during its first 4 years of formal activities (November 2014 – November 2018) are listed below as major accomplishments.

Relevant major research results:

• Strategic projects 2014-2018: transLectures^[1], MediaMixer^[2], Xlike[3], Xlime[4], TraMOOC[5], MOVING[6]
• Strategic projects 2018-2022 funded by the Government of Slovenia and European Commission: X5GON[7], CLEOPATRA[8], CogLo[9], DataBench[10], TheyBuyForYou[11], MicroHE[12]
• Addition of 5000 new OER based academic videos on VideoLectures.Net, a WSA 2009 and 2013 award winning video library currently including content from 1105 events, 15617 authors, 21269 lectures (some 24658 videos in total).

Relevant major capacity building results:

• ​2^nd World Open Educational Resources (OER) in Ljubljana, Slovenia, on 18–20 September 2017, co-organized by UNESCO and the Government of Slovenia. This event marked five years since the World OER Congress was held in Paris in June 2012. Organized by UNESCO and the Slovenian Ministry of Education, Science and Sport in close collaboration with the Commonwealth of Learning, Creative Commons, the Slovenian National Commission for UNESCO and the Chair with the generous support of The William and Flora Hewlett Foundation.
• 21 satellite events at the Congress facilitated and co-funded by the Chair
• The Chair organized in synergy with numerous partners a series of 20+ events in relevance to UNESCO’s strategic objectives, covering core UNESCO actions.

Relevant major educational result:

• Open Education for a Better World is a half-year on-line mentoring program in which students from very different backgrounds and different parts of the world developed 14 OER projects aligned with the UN SDG agenda.

Relevant major policy results:

• The Ljubljana OER Action Plan: The plan presents 41 recommended actions to mainstream open-licensed resources to help all Member States to build Knowledge Societies and achieve the 2030 Sustainable Development Goal 4 on “quality and lifelong education.”
• The Ministerial Statement: The statement is endorsed by 20 Ministers and their designated representatives of Bangladesh, Barbados, Bulgaria, Czech Republic, Costa Rica, Croatia, Kiribati, Lao People’s Democratic Republic, Lithuania, Malta, Mauritius, Mauritania, Mozambique, Palestine, Romania, Serbia, Slovakia, Slovenia, South Africa and the United Arab Emirates.
• The Dynamic Coalition on OER: Formation of a Dynamic Coalition of National Governments in OER and Open Education to propose, construct and operate a dynamic coalition of countries devoted to research, develop, deploy and exchange OER and Open Education solutions, practices and policies.
• The Slovenian Case in OER – From Commitment to Action: National policy document is now in a website format intended to showcase other governments at the Congress how Slovenia is coping with the idea of opening up education. We have identified 5 major areas across all fields of education.

Relevant major technological result:

• Global Infrastructure for OER promises to deliver the first building blocks for an open and artificial intelligence powered infrastructure to easily connect all global OER sites/siloses and provide a digestion pipeline for understanding content including by th use of machine translation, reasoning, recommendation, automatic curation, personalisation and aggregation of OER. It will result in providing technology services benefiting teachers, learners, researchers, policy makers and technologists.

Upcoming relevant results:

• UNESCO Recommendation on Open Educational Resources (OER), leading the draft text formulation further to the adoption of Resolution 44 ‘Desirability of a standard-setting instrument on international collaboration in the field of Open Educational Resources (OER)’ at the 39th Session of the UNESCO General Conference
• Setting up the Category 2 Centre on Artificial Intelligence Under the Auspices of UNESCO

[1] transLectures FP7 ICT Project – FP7-ICT-287755-STREP – Language technologies – website : http://translectures.eu/

[2] MediaMixer FP7 ICT Project – FP7-ICT-318101-CSA- Intelligent Information Management website : http://mediamixer.eu/

[3] Xlike FP7 ICT Project – FP7 -ICT-288342- STREP – Cross Lingual Knowledge Extraction (2012-2014) http://www.xlike.org/

[4] Xlime FP7 ICT Project – STREP, FP7-ICT-2013-10 – crossLingual crossMedia knowledge extraction (2014-2017)

[5] TraMOOC H2020 Project – Innovation Action, Translation for Massive Open Online Courses (2014-2018) http://tramooc.eu/

[6] MOVING H2020 Project – INSO-4-2015 – Training towards a society of data-savvy information professionals to enable open leadership innovation, http://moving-project.eu

[7] X5gon H2020 Project – ICT-19-2017 – X5GON: Cross Modal, Cross Cultural, Cross Lingual, Cross Domain, and Cross Site Global OER Network, http://x5gon.org/

[8] CLEOPATRA – H2020-MSCA-ITN-2018 – Cross-lingual Event-centric Open Analytics Research Academy

[9] CogLo – Future COGnitive Logistics Operations through Social Internet of Things

[10] DataBench – Evidence Based Big Data Benchmarking to Improve Business Performance

[11] TheyBuyForYou – Enabling procurement data value chains for economic development, demand management, competitive markets and vendor intelligence

[12] MicroHE – Support Future Learning Excellence through Micro-Credentialing in Higher Education, Erasmus+, EACEA/41/2016 – Forward-Looking Cooperation Projects

The Chair is based on the Institute Jozef Stefan which is a research rather than an educational institution, so in terms of education, no traditional certificates were provided. However, it does deliver training programme on three levels:

• Course in Open Education Design for practitioners in partnership with the University in Nova Gorica. Designed as a 5-day course, the participants become familiar with open education design processes, methods and tools in OER and based on the Open Education for a Better World mentoring programme delivering OER projects across the world.
• Via the MicroHE – Support Future Learning Excellence through Micro-Credentialing in Higher Education which specific objective is to examine the scope for and impact of micro-credentials – a form of short-cycle tertiary qualification – in Higher Education and deliver these certificates over a blockchain solution for open and online learning via the educational repository Vidoelectures.Net.
• Open Education for a Better World is a tuition-free international online mentoring programme launced by the Chair and University of Nova Gorica, to unlock the potential of open education in achieving the UN’s Sustainable Development Goals (SDG). It’s a half year-long mentoring programme for students from all backgrounds, regions and continents with the potential and desire to employ Open Educational Resources to solve large scale and relevant problems important in relation to today’s global landscape. The programme with over 40 mentors takes place over half a calendar year, starting from January, through to July 2018.  All mentoring sessions and events take place online and comprise of one final end-of-year, that is designed to help students finalise their work. OE4BW mentees will be expected to attend the final event.

There are currently 14 projects that are part of the first batch of the Programme, which students and mentors are actively finalising:

• Control of Diabetic Retinopathy
• Why infrastructure matters?
• Computer Automation
• Realizing traditional built heritage for sustainability
• Learning Design for Post-Secondary Courses using SDGs and OER
• Creating dynamic online courses
• Open Education Resources (OER) for Statistic and Probability in Pacific
• Archive in Fine Arts and Literature
• Professional Development through Collaborative Learning and Open Education Practices for Language Education
• Use of OER in Teaching and Learning
• Virtualização: Atividades Culturais Como Complemento Da Educação
• Booklets for midwifery students in Low and Medium Resources Countries
• Catalyzing Change: Diversity, Equity, and Inclusion in a Global Perspective
• Mliteracy

Some years ago the teacher would prepare her new class by using a textbook, searching through her library, or the library close to her home, perhaps discussing with her close colleagues and taking advantage of her own personal experience.

The advent of Internet has changed that, like many other things. In 2017 the teacher is going to use the internet as a set of textbooks, a huge library and her colleagues now live at the other end of the planet.

But this apparent richness is of little use if the right resources are too hard to find. How does one know that a video is useful without watching it? How can one believe that the lecture given by an unknown is correct? How do we discover the resource we need between thousands of others? And how do we find the resource which is open and we can therefore freely redistribute to our students?

To these difficulties we can add another one: how can we build a new resource in such a way that we am allowed to share it with others? With an answer to this question the teacher ceases to be a mere consumer and becomes a creator.

These questions are economic, political, pedagogical. But also technological: where are the tools enabling the teacher to make full use of free knowledge?

Furthermore, we would like these tools and the process itself to take place with no added cost: the challenge is that building open educational resources and using them should be as simple and as cost-free as possible.

The issues raised here are backed by many institutions: Unesco, the OECD,…, and many countries who signed the Paris 2012 declaration.

The Unesco Chair on Technologies for the Training of Teachers by Open Educational Resources, supported by the Nantes University Foundation, aims at contributing to this challenge.

The Chair will build its activities upon Unesco’s international dimension and the research cooperation maintained over the years with many actors. The Chair will benefit from the favourable ecosystem one can find in Nantes on these questions and more particularly of its research teams (LS2N, CREN,…) as well as the projects these are involved in (Class’Code, Labex CominLabs, …).

Computational Thinking

Whereas coding, programming, computing are the popular words used to express the competences to be acquires at an early age in order to be able to not be dependent in the information society, it is now becoming understood that the knowledge is less computer oriented and closer to problem solving activities. Computational thinking (in French, Pensée Informatique) is the set of processes one uses to solve a problem through representing the data as information, algorithmically solving the associated problem and restituting the result through some device. It is now strongly argued that it is a paradigm to be acquired at school.

We are at the threshold of an era when much of our productivity and prosperity will be derived from the systems and machines we create. We are accustomed now to technology developing fast, but that pace will increase and AI will drive much of that acceleration. The impacts on society and the economy will be profound, although the exact nature of those impacts is uncertain. We are convinced that because of the UK’s current and historical strengths in this area UCL is in a strong position to lead rather than follow in both the development of the technology and its deployment in all sectors of industry, education and government.

Artificial Intelligence describes a set of advanced general purpose digital technologies that enable machines to do highly complex tasks effectively. AI is not really any single thing – it is a set of rich sub-disciplines and methods, vision, perception, speech and dialogue, decisions and planning, robotics and so on. We have to consider all these different disciplines and methods in seeking real solutions in delivering value to human beings and organizations. AI was viewed as a set of associated technologies and techniques that can be used to complement traditional approaches, human intelligence and analytics and/or other techniques.

Key factors have combined to increase the importance of the AI Chair in recent years:

• New and larger volumes of data
• Supply of experts with the specific high level skills
• Availability of increasingly powerful computing capacity.

This is UNESCO’s single such Chair with this remit. It’s not copying other Chairs, but has a unique remit and identity, which will complement other UNESCO Chairs in the area of Data Science, Analytics and data and open technologies for Open Educational Resources. It has a clear interdisciplinary and intersectoral dimension: it transcends several of UNESCO’s programmes: education, communication and information, freedom of expression (fake news), media development and universal access to information and knowledge, and especially science for peace and sustainable development.

The Chair is established at the University College London in the United Kingdom (UCL), London’s leading multidisciplinary university, with 11000 staff, 35000 students and an annual income of over £1bn. University College London in general, and John Shawe-Taylor in particular is already a leading party in a European and a global network of partners collaborating in Artificial Intelligence (AI). This includes Knowledge 4 All Foundation Ltd. (K4A), together with a selection of a number of top ranked research institutions involved in European FP7 and H2020 research projects and consortiums from projects such as NeuroCOLT, PASCAL, PASCAL 2, KerMIT, CompLACS and most recently the X5GON, based on institutions consortiums.

Present the potential of AI for SDGs

Starting with 2 case studies in education and health: defining sustainable processes and structures (governance, access, business models, licensing, etc.) as well as developing a suitable software infrastructure (APIs and tools to aggregate existing tools and algorithms and to make them easily deployable in applications, as well as to access data and computing resources). Collect data from available data sources to create an infrastructure to ingest, process, analyze, aggregate and enrich specific-domain data, for specific SDG challenges. This infrastructure will scale to large amounts of data, starting from the education based project (in the millions of OER audio, video and animation, curricula, syllabi, lecture notes, assignments, tests, projects, courses, course materials, modules, textbooks, tests and datasets) that will form the basis for the algorithms to mine, represent, reason upon and use this diversity of information. This would be society agnostic, but would include the countries which are already OER adopters. As argued before, the core partnership lies with research institutes and partially universities. They are in the countries listed above. Not all countries, however, are represented in our network. While they still can be included in individual projects or as object of study, and certainly in the dissemination activities. In addition, it will also provide a test bed for other researchers outside the AI domain who might be interested in accessing the data processed and produced in the project. Access to the data sets and its metadata will be provided via a Web-based API, which will furthermore allow publishing new data sources.

Place the issue of AI for SDGs on the national, regional and international agenda

To identify options to harness the potential of rapid technological change and innovation towards achieving the Sustainable Development Goals with the use of AI. Collect information on, gain insight in, and identify the major characteristics (both similarities and distinctions) of AI developments at the national (and regional) level in a series of contexts that may be considered representative for the full spectrum of data science as well as for the variety in societies (e.g., The Netherlands, UK, Spain, Turkey, India, China, South Africa, Nigeria, Brazil, USA, Canada, Australia, New Zealand, and Commonwealth states). The core partnership for this objective lies with already established connections with Computer Science departments and Data partners,

Mobilizing an AI community

Including researchers, businesses and start-ups to provide access to knowledge, algorithms and tools for achieving SDGs. The increasing capability and use of machine learning, the rising creation of augmented reality content, and the changing capabilities and uses of smartphones have broad potential to contribute towards the SDGs.

Evaluate the critical success and failure factors

Among the national/regional AI case studies in relation to the variety of contexts, convert these into a context dependent multi-facetted framework of best conditions and guidelines for implementing an AI strategy at the national (or regional) level, and derive a set of AI scenarios fit for specific contexts. Analyze the educational, economic and societal impact of the national / regional AI case studies, advise on new requirements for machine learning and educational environments, and develop context dependent business models, explicitly taking into account societal benefits.

 Disseminate and share the broad AI knowledge

That has been created and derived in the project, more specifically provide good and bad practices, underline the contextual dependence, and give guidance and basic support to new national (or regional) AI initiatives. With instruments as visiting professorships, joint research projects, scholarships for PhD students the project will provide opportunities and support to the capacity building of partners in different regions.

AI Research – research activities on AI for SDGs – enabled artificial intelligence applications with definition of case studies:

The two initial case studies are SDG3 and SDG4 where two projects are running; X5GON and Malaria Diagnosis. Artificial Intelligence technologies are being developed and “marketed” for educational and healthcare use since decades but a large implementation gap exists. There is a slow adoption rate of technologies in education, because of mismatch between real needs and supply. The lack of use of technologies is particularly affecting the primary and secondary education. There is a need for building the evidence base for more effective learning with technology. This will go hand in hand with tools and processes for collecting, storing, exploring and reasoning on large-scale educational data We will collect “big data” from students’ technology supported learning activities, transforming the data into information and producing, recommending actions aimed at improving learning outcomes.

Prototype development, installation and deployment of state-of-the-art AI tools and technologies:

Prototypes to measure feedback and analysis of contexts, processes and environments. In order to have feasible research data, a real-life and functional ICT based network. AI is expected to contribute to advances in the data collected that will deliver the smart tools and analytical techniques required to generate actionable information from large and diverse datasets.

Dissemination and demonstration

Development of AI platform, joint or single business plan, exploitation of results, investigate service models, clustering and liaison, active community building and standard means of dissemination (presentations, publications, events, meetings, data exchange). The main visibility objectives of this project are to make scientific, industrial and educational communities aware of the project and its results; to disseminate project activities and results in related fields or application sectors. Additionally, to build a community around both AI project results and actively maintain a communication channel to its members. The project will follow a dissemination and community building strategy and will ensure that the technology deployed and data collected and created within the project are available beyond the end of the project. It will actively communicate with communities outside of the project, collect their feedback and involve them in the software development and research activities.

Exchange of research staff

Supervision, training of PhD and other research staff interested in computer science and technical aspects of AI. We recognize the need for researchers to work with large-scale data and we encourage them to develop collaborations with users to facilitate this exchange. We also encourage them to explore alternative routes to access sufficient computational resources (e.g. use of commercial clouds). However, the Chair will not try to imitate industry, and will focus on AI opportunities not yet identified by industry or not yet commercially viable.

Networking

Sharing and promoting best practices, case studies, prototypes and research results. Here we define two types of research projects. The first type (Type A) reflects the research program of the AI Chair and therefore has its focus in AI and for SDG3 online learning for OER and SDG4 healthcare, underpinned by advanced knowledge and context technologies. These research projects will be supervised under the AI Chair. The second category (Type B) is a set of ongoing H2020, Erasmus+ research projects involving University College London in a variety of AI related subjects these include: learning and adaptation; sensory understanding and interaction; reasoning and planning; optimisation of procedures and parameters; autonomy; creativity; and extracting knowledge and predictions from large, diverse digital data. These applications of AI systems are very diverse, ranging from understanding healthcare data to autonomous and adaptive robotic systems, to smart supply chains, video game design and content creation, and will be connected to the AI Chair in order to enhance synergy with UNESCO Chair in Analytics and Data Science in the overall AI research agenda at University College London. The AI Chair is fully involved in these (Type B) research projects. In the first year and part of the second year the research activities (Type A) will build on ongoing H2020 research projects (Type B). At the same time University College London will bid and develop new research projects under the Horizon 2020 research program and the research program of the AI Chair and in collaboration with the other partners listed in c. partnerships/networking (Type A).

The Chair will address the topic of AI in two specific scenarios to indeed contribute with real-life case studies to showcase AI as a feasible approach towards meeting initially two and expanding to other SDGs.

Sustainable Development Goal 3: Good Health and Well-being

Machine learning is already contributing to improved diagnoses and treatment of diseases. Quicker accurate malaria diagnosis will enable faster delivery of clinical services to facilitate International Development Goals for the sub-Saharan African region and other regions of the World affected with malaria. The funding will be used to carry-out engineering (robotics), computational research (computer vision and machine learning) and digital health clinical research (pediatric infectious diseases) to design, implement, deploy and test a fully automated system capable of tackling the challenges posed by human-operated light-microscopy currently used in the diagnosis of malaria. The funded research aims to overcome these diagnostic challenges by replacing human-expert optical-microscopy with a robotic automated computer-expert system that assesses similar digital-optical-microscopy representations of the disease. The Fast, Accurate and Scalable Malaria (FASt-Mal) diagnosis system harnesses the power of state-of-the-art machine learning approaches to support clinical decision making. Driven by AI in each step, this allows for constant improvement and scalability. Improved smartphone processing also has potential to enable diagnostics “on-the-go” or in remote areas. As smartphone penetration increases, access to mobile diagnostics will expand, magnifying the effect of the improvements in smartphone processing enabling these innovations.

Sustainable Development Goal 4: Quality Education

Developments in machine learning can raise educational standards through improved educational apps, digital engagement, and personalised learning. The X5gon: Cross Modal, Cross Cultural, Cross Lingual, Cross Domain, and Cross Site Global OER Network project leverages AI to deliver personalized learning. This solution will adapt to the user’s needs and learn how to make ongoing customized recommendations and suggestions through a truly interactive and impactful learning experience. This new AI-driven platform will deliver OER content from everywhere, for the students and teachers need at the right time and place. X5GON will develop innovative services for large scale learning content understanding, large scale user modelling and real-time learning personalization with a main processing pipeline dealing with big data analytics in near to real time setting. X5GON analytics pipeline is not only relevant for OER but can be easily applied in other domains as well. The term Open Educational Resources has been introduced by UNESCO in 2002, and adopted OER as a strategy to meet its objectives in education.

Artificial Intelligence and Computer Science based on the research results and applications from fields :

• Machine Learning
• Deep Learning
• Big-Data
• Data-Mining
• Text-Mining
• Web-Mining
• Multimedia Mining
• Semantic Technologies
• Social Network Analysis
• Language Technologies
• Natural Language Processing
• Multi-lingual
• Cross-lingual Technologies
• Scalable, Real-time Data Analysis
• Data Visualization
• Knowledge Management
• Knowledge Reasoning
• Cognitive Systems.

Project Leader:
John Shawe-Taylor
Professor of Computational Statistics and Machine Learning
Director, Centre for Computational Statistics and Machine Learning (CSML)
Head of Department of Computer Science

University College London
Gower Street
London WC1E 6BT
United Kingdom
Office: 5.13
Tel: +44 (0)20 7679 7680 (Direct Dial)
Internal: 37680
Fax: +44 (0)20 7387 1397
Email: J.Shawe-Taylor@cs.ucl.ac.uk
Website: http://www0.cs.ucl.ac.uk/staff/J.Shawe-Taylor/

Contact Person:
Charlotte Penny
Role: Manager, Centre for Virtual Environments, Interaction and Visualisation
University College London
Dept. of Computer Science
66-72 Gower Street
London WC1E 6EA
United Kingdom
Tel: +44 (0)20 3108 7150 (Direct Dial)
Internal: 57150
Email: C.Penny@cs.ucl.ac.uk
Website: http://www.cs.ucl.ac.uk/people/C.Penny.html/