Title OntoHR - Ontology Based Competency Matching between the Vocational Education and the WoRkplace
Project Number 504151-LLP-1-2009-1-HU-LEONARDO-LMP
Project Type Development of Innovation
Country EU-Centralised Projects
The objective of the OntoHR project is to develop an HRM system that decreases the gap between higher vocational education and the labour market. The partnership is working together on an eLearning environment, which will be equipped to sample knowledge, skills and competences of VET students and match
it with the selection criteria of specific job roles in Europe.
Feedback will be provided on job role fit and complementing eLearning programmes.
According to the Bologna qualification structure different levels of education must prepare a student for particular organizational needs and prerequisites. Students finishing their studies at various levels of vocational education have to go through the organization’s Prior Learning Assessment, in which previous experience and qualifications are evaluated against entry requirements (skills and competencies) for the job role. The field of personnel selection has its roots in the notion that a candidates’ future job performance in a particular position may be predicted at the time of selection on the basis of relatively enduring and stable characteristics of that candidate.
Inferences that are made in personnel selection research can be classified into three approaches towards establishing the validity of predictor measures, namely 1) the content- related approach; 2) the criterion-related approach; and 3) the construct-related approach. Rather than attempting to assess the job performance domain in its entirety, either a predictor or a criterion measure is used to sample the performance domain. Broad educational qualifications are too crude for purposes of personnel selection. We therefore want create more specific qualification to job matching, with the overriding purpose of tackling the conversion of vocational education qualifications into job related competencies. To facilitate this, an ontology supported selection and training system will be built in line with relevant HRM and Knowledge Management (KM) theories, employing existing educational technology such as Content Management Systems and adaptive testing. This eLearning interface will be able to
• Map qualifications in vocational education to current and valid job roles
• Test and evaluate students on the basis of valid, labor market driven competencies
• Identify missing competencies and provide learning content needed to acquire them
• Address the weaknesses of particular VET curricula, and thereby provide ad-hoc support
This learning environment should be equipped to sample skills, competencies and knowledge of vocational education students. Based on this sampling we give an evaluation as to whether the selected individual meets the criteria of a given job profile of an existing company. The underlying HRM model with its ‘predictor measure’, ‘criterion measure’ and ‘underlying psychological construct domains’ also demonstrate an inferential mixture, which supports the validity of the predictor as a decision making tool pertaining to qualification–job role matches. These measures can be defined in terms of knowledge and competencies, which form the foundation of the educational ontology.
Our framework encompasses a Domain Ontology, a VET Ontology, a mapping engine, and an adaptive testing engine. The Domain Ontology comprises a global map of the organizational needs and competencies needed to carry out valued activities within a particular field (in this case Information Technology). Based on this ontology specific job roles will be identified. Subsequently, a detailed description of the essential skills and competencies, that are required for being selected for a certain position, are framed in terms of student/applicant VET qualifications.
The VET ontology describes what skills and competencies one needs to get a certain VE degree and also how these skills and competencies are constructed–for instance the factual knowledge they require–and their inter-relatedness. In order to benefit from the outputs of ontologies for training, selection and recruitment processes the Job role ontology must be embedded into an authoring environment, which will enable tutors to provide training according to the idiosyncratic needs of students. This authoring environment not only delivers learning content, but with its built-in test- and inference engine, reports the current eligibility of a particular student for the prerequisite skill and competencies of a given Job-role.
Information and Communication
Professional, Scientific and Technical Activities
Other Service Activities
program or curricula
procedure for the analysis and prognosis of the vocational training requirement
description of new occupation profiles
On the website one can access the OntoHR system (www.ontohr.eu), thus we put information there about how the system works and what is its technical/theoretical background.
The consortium produced 3 different versions of the system:
1, the full version - it takes around 2 hours,
2, IQ - measuring general mental ability
3, demo, showing what kind of tests we applied.
The way it works is that we are measuring 72 technical competencies in relation to a job (Information System Analyst). The measurement has 2 stages. 1, Job knowledge test, 2, general mental ability test.
Based on the combination of these two test results, the software should identify if the applicant meets the job requirements and pinpoints the missing competencies. The software also provides learning content for the missing competencies and also a pdf document detailing the results. The list of competencies can be tailored down to the needs of the organization. So one only evaluate those, which are necessary for the given job.
On the website one can find videos about the system and the evaluation, also aids for logging in and understanding our approach.