Utilising the potential of job postings for auditing learning outcomes and improving graduates' chances on the labour market

Abstract

The objective of the paper was to outline the possibility of utilising information from online job postings and text-mining analyses to identify mismatches and gaps between learning outcomes prepared by universities, and the knowledge and skills that employers need. The study uses job advertisement contents and learning outcomes documents from universities. We analysed both data sets using word importance classification, cluster analysis and hierarchical clustering. Word importance classification presented the mismatches in a quantitative and diagram format. Cluster analysis and hierarchical clustering provided information on how to correct the detected gaps and mismatches. The study empirically corroborates that the method we put forward for analysing both sources (LOs and job ads) helps identify and assess the significance of gaps and mismatches in the approaches to knowledge and skills adopted by universities and employers. Consequently, the method can be helpful during the auditing process and while implementing market-oriented curriculum changes.