Reliability and Construct Validity Assessment of the Student Competency Questionnaire among Final Year Diploma Students: A Statistical Analysis Approach

Authors

Keywords:

Students Competencies Reliability Validity Questionnaire Evaluation Cronbach’s Alpha

Abstract

The university strives to provide students a curriculum that is pertinent and taught by educators with exceptional delivery methods, in a stimulating and dynamic learning setting. The objective is for students to graduate from the institution as individuals who can positively impact society, establish businesses, and assume leadership roles in the professional realm. The objectives of this research are to develop the Student Competency Questionnaire (SCQ) and evaluate its reliability and validity. The evaluation followed classical test theory, focusing on reliability, construct validity, and content validity. A postal questionnaire containing 49 items was sent in October 2022 to a sample of 59 final-year diploma students from various programs. Three experts in education, statistical modeling, and decision-making evaluated the content validity of the scale. The Content Validity Index (CVI) for all constructs ranged from 0.96 to 1, exceeding the threshold of 0.70, indicating that the items are 'content valid.' Cronbach's alpha values showed a high level of internal consistency, all exceeding 0.90. Additionally, all items within each construct were highly related to one another, with correlations exceeding 0.30. This research demonstrates that the Pillar 1 education 5.0 @ UiTM frameworks effectively capture essential skills for students' academic and professional development, enhancing their employability. The focus on Personal, Adaptive, Digital, 21st Century, and Social competencies, along with student satisfaction, ensures students are equipped with diverse skills needed to thrive in dynamic environments. Overall, UiTM's approach prepares students for success in their future careers and personal lives.

Author Biography

Dr.Norhayati, UiTM

Dr. Norhayati Baharun      is an Associate Professor of Statistics, Universiti Teknologi MARA Perak Branch,Tapah Campus. She received her PhD in Statistics Education from the University of Wollongong Australia in 2012. Her career started as an academic from January 2000 to date at the Universiti Teknologi MARA that specialized in statistics. Other academic qualifications include both Master Degree and Bachelor Degree in Statistics from Universiti Sains Malaysia and Diploma in Statistics from Institute Teknologi MARA. Among her recent academic achievements include twelve on-going and completed research grants (local and international), four completed supervision of postgraduate studies, fifteen indexed journal publications, two academic and policy books, twenty-six refereed conference proceedings and book chapter publications, a recipient of 2013 UiTM Academic Award on Teaching, and fourteen innovation projects with two registered Intellectual Property Rights by RIBU, UiTM. She is also a certified Professional Technologist (Ts.) (Information & Computing Technology) of the Malaysia Board of Technologist (MBOT), a Fellow Member of the Royal Statistical Society (RSS), London, United Kingdom, a Professional Member of Association for Computing Machinery (ACM), New York, USA, and a Certified Neuro Linguistic Program (NLP) Coach of the Malaysia Neuro Linguistic Program Academy. Her research interests continue with current postgraduate students under her supervision in the area of decision science now expanding to a machine learning application.

Published

2024-11-27

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Section

Articles