Structural Classification of Employability Skills Hierarchy using Rasch Analysis Model
Sunday Rufus Olojuolawe1, Nor Bt Mohd Amin Fadila2, Adibah Abdul Latif3, Habibu Aminu Sani4, Haruna Garba Wase5

1Sunday Rufus Olojuolawe*, department of Technical Education, College of Education, Ikere-Ekiti, Nigeria.
2Nor Bt Mohd Amin Fadila, department of Technical and Engineering Education, Universiti Teknologi, Johor, Malaysia.
3Adibah Abdul Latif, department of educational foundation, Universiti Teknologi, Johor, Malaysia.
4Habibu Aminu Sani, department of Office Technology and Management, Nuhu Bamalli Polytechnic, Zaria.
5Haruna Garba Wase, department of Public Administration, Nuhu Bamalli Polytechnic, Zaria. 

Manuscript received on 1 August 2019. | Revised Manuscript received on 8 August 2019. | Manuscript published on 30 September 2019. | PP: 3581-3591 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5302098319/2019©BEIESP | DOI: 10.35940/ijrte.C5302.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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.
Keywords: Employability Skills, Hierarchy, Rasch Analysis, Structural.

Scope of the Article: Classification