Dr. Gábor Kismihók
Innovation competition INVITE of the Federal Ministry of Education and Research (BMBF)
1 May 2021 – 30 April 2024
The aim is to digitally support individual learning processes of professional nursing staff; to make learning environments more needs-oriented; to promote access to continuing vocational education and training; and to provide more targeted support for the applicability of professional development measures.
The promotion of continuing vocational education and training is a vital approach to meeting the future need for skilled workers and the requirements of needs-based provision in professional nursing. At the same time, the workforce is becoming more diverse. This presents in-house training staff and HR development with new and additional challenges. With this in mind, ADAPT will further develop existing in-house training platforms in the field of nursing into a digital continuing education support system.
A learning environment based on artificial intelligence (AI) is to be created alongside the development, testing and evaluation of adaptive teaching and learning concepts. The aim is to digitally support individual learning processes of professional nursing staff; to make learning environments more needs-oriented; to promote access to continuing vocational education and training; and to provide more targeted support for the applicability of professional development measures. This procedure will optimise the coordination between individual learning needs, operational reorganisation requirements and professional development measures in the nursing context.
Besides facilitating the creation of personalised learning content, ADAPT will also enable the education and learning process to be geared more closely to individual learning requirements and objectives. As a result, the project implements the Al-supported promotion of the user-centredness of continuing vocational education and training, while simultaneously promoting the work process-related matching of learning content and professional practice. This will increase the reach of professional development measures in nursing and enhance employees’ willingness to participate in continuing education. Structural and staff measures to promote continuing vocational education and training are linked in operational practice in such a way that vocational competence is promoted by means of personalised professional development measures, also improving the sustainability of staff development measures. In addition, application-related knowledge is created for institutions to implement AI-based continuing education spaces. A participatory research and technology design approach is used to implement ADAPT.
- Institute for Work and Technology (IAT), Westphalian University of Applied Sciences / Ruhr University Bochum, research focus “Work and change”, Gelsenkirchen
- APZ MKK – Alten- und Pflegezentren des Main-Kinzig-Kreises, Rodenbach
- Pädagogische Hochschule Freiburg University of Education, Department of Vocational Education and Training for Health and Sustainability, Institute of Vocational and Business Education, Freiburg
- TIB – Leibniz Information Centre for Science and Technology, Learning and Skills Analytics Research Group, Hannover
- BiG – Bildungsinstitut im Gesundheitswesen, Essen
- maxQ/IFTP im bfw – Unternehmen für Bildung, Erkrath