Universiti Teknologi Malaysia Institutional Repository

Structural classification of employability skills hierarchy using rasch analysis model

Olojuolawe,, S. R. and Mohd. Amin, N. F. and Latif, A. A. and Sani, H. A. (2019) Structural classification of employability skills hierarchy using rasch analysis model. International Journal of Recent Technology and Engineering, 8 (3). pp. 3581-3591. ISSN 2277-3878

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Official URL: http://dx.doi.org/10.35940/ijrte.C5302.098319

Abstract

This study considers the procedures for conducting item classification employing Raech Analysis Model. The knowledge of the hierarchy enables lecturers to organize their learning objective and also permits the students to measure their employability. The survey study employs exploratory sequential mixed methods. It was conducted to identify and give the hierarchy of the skills required by Electrical Technology students in Colleges of Education in Nigeria to be employable. The first phase involved 10 electrical experts from Industry and Colleges of Education who were purposely selected. The analysis of the findings obtained using Nvivo 12 led to the second phase which comprised of 104 respondents. The sample also consists of Electrical Technology expert in both Industry and Academics. In order to ensure that all items fit the Rasch Analysis Model, the fit statistics were performed to refine and remove all misfits item. Because, the item was ordinal and ranked, Partial Credit (Rasch) Model was involved in the treatment. A separation index of 3.28 and 5.28 was obtained for the technical and non-technical skills with a reliability of .91 and .97 respectively. The implication is that each group is unique and therefore, the most basic item at the bottom of the hierarchy must be learned before the next higher-order item.

Item Type:Article
Uncontrolled Keywords:hierarchy, rasch analysis, structural
Subjects:L Education > L Education (General)
Divisions:Education
ID Code:90930
Deposited By: Narimah Nawil
Deposited On:31 May 2021 13:21
Last Modified:31 May 2021 13:21

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