A smart, AI-based digital further education space for elderly care by means of personalised recommendation systems
Innovation competition INVITE of the Federal Ministry of Education and Research (BMBF)
September 2021 – August 2024
WBsmart deals with an AI-based digital training space for elderly care by means of personalised recommendation systems to address priority III of the INVITE call for proposals with regard to the development and testing of teaching and learning offers supported by artificial intelligence (AI). The AI is implemented as a recommendation system in the form of personalised learning recommendations based on a semantic knowledge graph and stored job and skill profiles. The development and testing is being carried out in an interdisciplinary joint project consisting of two chairs at the University of Siegen (Knowledge-Based Systems and Knowledge Management: WBS; Vocational and Business Education: BWP) as well as the Learning and Skill Analytics group at the TIB. As an associated partner and field access, the Gemeinnützige Gesellschaft der Franziskanerinnen zu Olpe mbH (GFO) is involved with its employees in the business area of elderly care.
The field of elderly care is particularly affected by digitalisation - due to the increasing necessity of using digital elements and tools, special challenges arise in the context of digitalisation processes: Within the framework of the research project Weiterbildung Inklusiv (Buchmann 2019), an ambivalent acceptance of technology (ATA) was identified in the field, through which large differences in terms of technology use (consumerist or cosmopolitan) and technology acceptance or technology resistance can be demonstrated. In order to deal with this phenomenon, it is necessary to develop adaptive online offers that are based on vocational education and training science, that are both demand- and application-oriented as well as digital, secure and innovative, and that enable a flexible modular composition of course offers and learning content by the learners. For this purpose, the participatory development of a digital and AI-supported further education space together with the employees of the elderly care (learners) is purposed in order to provide adaptive learning and needs-based support in the learning process for employees and career changers, supported by an algorithmic explainability of the AI. In this way, the trustworthiness of the digital vocational training and the algorithmic procedure used are comprehensible and transparent for the learners. An interdisciplinary approach is pursued with which digital, AI-based learning is interlinked via a learning platform and within the framework of accompanying mentoring. Microlearning and Open Educational Resources (OER) are planned as teaching and learning offers.
As part of the further development of the TIB's AI-based OER learning platform, a participatory approach is being pursued so that the target group is directly involved in the development of needs, the skills to be acquired and the expansion of competences in the sense of a subject-oriented setting (user-centred design). In this way, the need for continuous further training (e.g. fire protection, dementia, etc.) and functional further training (caregiver, living area management, care service management, facility management, etc.) can be provided digitally, innovatively, securely and smartly for employees of elderly care. Using various spaces for collaborative work (e.g. think space) and workshops, curricula and didactic concepts will be developed, which will form the basis for the expansion of the AI platform and its interface as well as the accompanying mentoring during the tool-based learning. An iterative and agile approach will be followed so that further improvements will be incorporated into the platform on the basis of the first trial phase. The extension of the platform will be implemented and tested in the form of an open system for other occupational fields and additional competences. In this respect, the project has a particular innovative content both in terms of content (see 4.1) and interdisciplinary collaboration (see 5.1).