Pregled bibliografske jedinice broj: 1024742
Formal model of student competencies in higher education and required skills in the job market
Formal model of student competencies in higher education and required skills in the job market // Proceedings of the 30th Central European Conference on Information and Intelligent Systems (CECIIS 2019) / Strahonja, Vjeran ; Hertweck, Dieter ; Kirinić, Valentina (ur.).
Varaždin: Faculty of Organization and Informatics, University of Zagreb, 2019. str. 43-49 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Formal model of student competencies in higher education and required skills in the job market
Autori
Fuzul, Ena ; Horvat, Marko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 30th Central European Conference on Information and Intelligent Systems (CECIIS 2019)
/ Strahonja, Vjeran ; Hertweck, Dieter ; Kirinić, Valentina - Varaždin : Faculty of Organization and Informatics, University of Zagreb, 2019, 43-49
Skup
30th Central European Conference on Information and Intelligent Systems (CECIIS 2019)
Mjesto i datum
Varaždin, Hrvatska, 02.10.2019. - 04.10.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Formal knowledge representation ; ontologies ; web scraping ; higher education curriculum ; learning analytics
Sažetak
Higher education is a system that educates, professionally directs and strives to deliver competitive students in the labor market. The study programme determines the set of competencies and knowledge that the student acquires during the course and each course is determined by the curriculum, learning outcomes, achievements, and other data. On the other hand, the real sector is dynamic, defining new jobs, competencies and employment criteria every day. The research presented in this paper aims to define a formal knowledge model for the presentation of student's competencies and match them to the criteria and requirements of the real sector. Using web scraping technologies, the data related to courses and job ads were retrieved. Afterwards they were grouped, categorised and matched using the Web Ontology Language language for further potential comparison of the best candidates and job positions. The results indicate the potential of automatised retrieval and classification of available course data using formal knowledge representation which could lead to a more efficient discovery of employees. The paper concludes with guidelines for further analysis and potential upgrades of the student evaluation process.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
