WHAT ABOUT THE JOB MARKET: SPATIAL BASED JOB MONITORING AS A SUPPORT FUNCTION FOR CURRICULAR DECISIONS
WU Vienna (AUSTRIA)
About this paper:
Appears in: INTED2011 Proceedings
Publication year: 2011
Conference name: 5th International Technology, Education and Development Conference
Dates: 7-9 March, 2011
Location: Valencia, Spain
Abstract:Seeing educational institutions under a stakeholder approach, where students, their parents, teachers, graduates, companies and others like the society as such are defined to have a stakeholder role, curricular decisions have to fulfill a diverse range of goals. Different aims can be complementary as well as contradictory and can have different importance for different groups.
However, one of these goals seems to be complementary for all groups and have at least some importance for all literature defined stakeholder groups. This well known, but also highly debated goal can be subsumed under the term “employability”. To fit the requirements of the job market after graduation is more or less important for all the groups stated above.
Several studies used job announcement as source to identify demand for skills and competences as well as personal characteristics in a certain occupational field. We follow their assumption that job ads can be used as a proxy for employability, but add next to skills and personal characteristics other signals, according to the well known signaling theory of Spence. (He argues that graduation in itself is a signal sent from the graduate to the job market.)
To analyze the regional distribution of skills, we collect online data (i.e. online job announcements) with web harvesting techniques and analyze the regional distribution of jobs and (selected) contained skills/competences, personal characteristics and signal related terms. We use certain packages of the statistical software R which support text mining and spatial analysis functionalities as well as standard multivariate statistical analysis.
Keywords: Job announcement, employability, skill monitoring, spatial analysis, text mining.