X5oerfeed: The project will deploy a technological pipeline for content understanding that is based on http://exploredu.ijs.si, http://eventregistry.org services developed by JSI, video lectures segmentation and translations services developed by UPV https://ttp.mllp.upv.es/ .
X5analytics: The project will 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. The work will be based on the existing services developed by UCL, JSI and NA.
X5recommend: enabling cross-site and cross-lingual recommendation. Quality assurance of OER materials and services is of paramount importance for wider OER adoption. X5gon will combine various models and methods to assure appropriate mechanisms to rate and assess the quality of materials. This will include automatic methods based on use analytics and user grading, existing peer review models at sites, combined ranking as well as trust network support to create communities of trust between teacher and users. The last have been demonstrated as very efficient in the two H2020 large pilot projects Open Discovery Space (http://opendiscoveryspace.eu/) and Inspiring Science Education (http://inspiringscience.eu/).