The vocational training environment in Germany includes a tremendous multitude of courses. As such, it is challenging to find the best matching offer as an individual learner. Ideally, the selected training program should closely match my respective interests, abilities, learning goals, and current life context. An enhanced matching can not only increase learning motivation but also perceived self-efficacy and learning success.
The project KIPerWeb intends to apply AI technologies to match training offers to individual learners. The vision is to establish an automated dialogue in which learners can communicate their individual preferences and state of learning, whereupon they receive an automated recommendation for a matching training program. Additionally, the project intends to modularize trainings such that it becomes possible to recommend a finely matching combination of modules. To achieve these goals, the project intends to include both methods of statistical AI as well as symbolic AI.
The project lead is the Forschungsinstitut Betriebliche Bildung (f-bb). DFKI provides all of the AI modules for the project and is involved in the integration of AI modules in the systems of the project partners, namely the Bildungswerk der Niedersächsischen Wirtschaft (BNW), the oncampus GmbH, and the Provadis Partner für Bildung und Beratung GmbH. The Institut für betriebliche Bildung (IFBB) organizes a network of training providers in the form of a community of practice.
Forschungsinstitut Betriebliche Bildung (f-bb) Berufliche Fortbildungszentren der Bayerischen Wirtschaft (bfz) gGmbH Bildungswerk der Niedersächsischen Wirtschaft (BNW) oncampus GmbH Provadis Partner für Bildung und Beratung GmbH