Improving student employability by utilising semantic analysis of course data
Dafoulas, George 
ORCID: https://orcid.org/0000-0003-2638-8771, Barn, Balbir ORCID: https://orcid.org/0000-0002-7251-5033 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.
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[Conference or Workshop Item]
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: | 27 Sep 2019 16:05 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/16061 |
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