The objective of this project is to generate support for the widely held but
seldom investigated belief that job related training contributes to job
knowledge and therewith job performance, thereby forging a link between
educational institutions and the labour market. The Job knowledge data will form
the input of the ontology based selection system. The project contributes to our
understanding of how intelligent algorithms may be used to ameliorate
(mis)matches between person’s abilities and job demands.
The methods include quantitative literature review and practitioner interviews to investigate the conditions under which organizations are better off training their incumbents’ job knowledge or hiring new employees with such job knowledge; collection of qualitative job knowledge data for a particular job through interviews with job incumbents and HR managers; additional qualitative data from vacancies and job related documentation. Data will be content analysed in order to yield the job knowledge dimensions that are key to job performance in this job. Multisource and multiwave surveys will be employed for psychometric validation and to investigate temporal dynamism in the co-development of job knowledge and job performance over time.
This PhD is part of the Eduworks project