This use case consists in allowing the pooling of aggregated data in order to train artificial intelligence algorithms. This is a necessity for the public and private sectors, as well as for research.
This use case would allow to answer needs such as:
- To cross-reference the usage data of digital readers and build a model that would allow to detect school dropout very early, or on the contrary an interest that is not reflected in the assessments
- Facilitate the development of adaptive learning solutions, based on external data
- Impact studies by cross-referencing data from individuals throughout their lives (school, orientation, training, skills, career)
- Allows actors to cross data sets, for instance learning traces, that are currently fragmented
- Limits cold start problems
- Exploit unused data in a trusted environment
- Larger datasets to open up training possibilities for Machine Learning models
- Interoperability of educational data
Among its early adopters and data providers,Prometheus -X brings together a set of stakeholders committed to implementing this use case.
These organizations are: Pôle Emploi, INRIA, FUN MOOC, Insititut Mines Telecom, Université de Lille, MENJS, Openclassrooms, WebForce 3, Serious Factory, Weenoz, Digischool, numerous edtechs, ...