AI for education project ending in the Horizon 2020 programme, but work still continues
The project has developed a commoditized set of tools and systems that enable the ingestion of OER material into the X5GON registry including semantic cross-lingual indexing of materials, automatic transcription and translation of recordings, assessment of how engaging the material is, and potentially how it might sequence with other OERs.
Further, methods for automatically estimating the knowledge of users based on their track record of viewing different OERs enables the system to recommend content that is likely to engage and prove useful for learners and teachers.
For example, a moodle plug-in can provide such recommendations at the level of a particular course, while the X5learn system can make recommendations to individual learners based on their earlier viewing experience.
The project has actively engaged with OER sites and developed systems to assist with the incorporation of OERs into the X5GON registry significantly growing the number of sites and materials that are indexed by the X5gon tools.