An integrative review of computational methods for vocational curriculum, apprenticeship, labor market, and enrollment problems

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Ahmad Dardiri, Felix Andika Dwiyanto, Agung Bella Putra Utama

2020 International Journal of Advances in Intelligent Informatics Vol. 6 Issue 3 Article Cited by 4 Quartile

Abstract

Computational methods have been used extensively to solve problems in the education sector. This paper aims to explore the computational method's recent implementation in solving global Vocational education and training (VET) problems. The study used a systematic literature review to answer specific research questions by identifying, assessing, and interpreting all available research shreds of evidence. The result shows that researchers use the computational method to predict various cases in VET. The most popular methods are ANN and Naïve Bayes. It has significant potential to develop because VET has a very complex problem of (a) curriculum, (b) apprenticeship, (c) matching labor market, and (d) attracting enrollment. In the future, academics may have broad overviews of the use of the computational method in VET. A computer scientist may use this study to find more efficient and intelligent solutions for VET issues. © 2020, Universitas Ahmad Dahlan. All rights reserved.

Affiliations

Faculty of Engineering, Universitas Negeri Malang, Malang, Indonesia