X5gon stands for easily implemented freely available innovative technology elements that will converge currently scattered Open Educational Resources (OER) available in various modalities across Europe and the globe.
X5gon will combine content understanding, user modelling and quality assurance methods and tools to boost creating a homogenous network of (OER) sites and provides users (teachers, learners) with a common learning experience. X5gon will deploy open technologies for recommendation, learning analytics and learning personalisation services that will work across various OER sites, independent of languages, modalities, scientific domains, and cultural contexts.
It will develop services for convergence of OER media which includes full courses, course materials, modules, textbooks, streaming videos, tests, software, related events and any other tools, materials, or techniques used to support access to knowledge.
The solutions that will be offered to OER sites are fivefold:
- Cross-modal: technologies for multimodal content understanding;
- Cross-site: technologies to transparently accompany and analyse users across sites;
- Cross-domain: technologies for cross domain content analytics;
- Cross-language: technologies for cross lingual content recommendation;
- Cross-cultural: technologies for cross cultural learning personalisation.
X5gon is an analytic platform with open services, APIs and scripts supported with AI enabled technical pipeline to converge dispersed open educational resources (OER) media content to learners and users into a one-stop-shop data-driven learning environment.
The project will collect and index OER resources, track data of users and their progress and use that to drive an analytics engine driven by state-of-the-art machine learning that can improve recommendations through better understanding of users, their progress and goals, and hence their match with knowledge resources of all types. In addition X5gon will implement innovative models and methods for OER quality assessment and assurance, including trust networks between teachers for OER creation and exchange, automatic content validation and user experience.
The project will run a series of pilot case studies that enable the measurement of the broader goals of delivering a useful and enjoyable educational experience to learners in different domains, at different levels and from different cultures. The two exploitation scenarios are planned: (i) free use of services for OER, (ii) commercial exploitation of the multimodal, big data, real-time analytics pipeline.
Keywords: Open Educational Resources, machine learning, cross-site, cross-domain, cross-modal, cross-language, cross-cultural, cross-social, adaptive learning, policy making, web and information systems, database systems, communication networks, media, information society, accessibility, cultural studies, cultural diversity.
List of beneficiaries:
- University College London
- Institut Jozef Stefan
- Knowledge 4 All Foundation
- Universitat Politecnica de Valencia
- Université de Nantes
- Universitaet Osnabrueck
- Slovenian Post
- Ministry of Education of Slovenia