Improving student employability by utilising semantic analysis of course data

Dafoulas, George and Barn, Balbir and Zheng, Yongjun (2014) Improving student employability by utilising semantic analysis of course data. In: ICERI 2014 : 7th International Conference of Education, Research and Innovation.

Full text is not in this repository.

Abstract

This paper describes the development of a toolkit based on the semantic analysis of course data using the eXchanging Course Related Information – Course Advertising Profile (XCRI-CAP) information model. Based on the XCRI-CAP 1.2 standard, our research focused on providing the means for semantically comparing course descriptions and curriculum documentation. The paper provides an overview of how the JISC funded MUSAPI (Musket-Salami Project Integration) project resulted in the creation of a web service allowing (i) raising awareness regarding the architecture of job profiles and the employability terminology used in career services, (ii) identifying potential job opportunities for student graduates and/or university applicants, (iii) ranking ‘real’ job opportunities filtered according to a range of criteria and (iv) mapping job opportunities to courses in higher education institutions offering the necessary skills and knowledge.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 16061
Useful Links:
Depositing User: George Dafoulas
Date Deposited: 18 May 2015 16:15
Last Modified: 13 Oct 2016 14:34
URI: http://eprints.mdx.ac.uk/id/eprint/16061

Actions (login required)

Edit Item Edit Item