An ontology-based Recommender System to Support Nursing Education and Training

The need of healthcare organization on highly knowledgeable and qualified human recourses to guarantee quality of performance is indispensable. A desired performance level is tailored with obtaining competences and job knowledge, as the major influential factors. This is especially critical due to high rate of changes in knowledge domains and technological infrastructure over time i.e. before or within employment of job holders and applicants. Therefore, applicants as well as employees and practitioners are also dealing with upgrading their level of job knowledge and qualifications. Adaptive Medical Profession Assessor (Acronym: Med-Assess) as a European funded project, proposes a knowledge based system for assessment of the competences and job knowledge of the applicant/employee to perform a certain job role in the domain of healthcare i.e. nursing and care giving to neuro-patients. In this context , recommendation of learning materials is an integral part. It subjects to the required training due to the lack of competence(s) for performing a specific nursing task(s). This paper presents the system architecture of Med-Assess, and discusses how the applied semantics i.e. ontologies and rules are developed. It especially presents the background in nursing education and training, and conceptually presents the design of the re-commender components.