Measurement Model of Mathematics Intervention Based on the Learning Style of Students with Learning Disability (MIMGAP) Using Exploratory Factor Analysis (EFA)

Abstract

Factor analysis is a statistical technique that has been widely used in psychology and social sciences, including the field of special education. The purpose of this study is to help researchers, educators, and students to understand the nature of exploratory factor analysis (EFA), specifically from the perspective of special education involving students with learning disability in mathematics. All items and factors identified through the EFA were used as inputs for the measurement model in second-generation structural equation modelling (SEM) techniques. This article presents five steps of exploratory factor analysis using SPSS, namely data examination technique, factor analysis, factor extraction, factor rotation and factor loading cutoff method. Pre-tests were conducted on 112 respondents, and items were analysed through Principal Component Analysis (PCA) using SPSS 26. Furthermore, the suitability of the data for EFA was measured through KMO and Bartlett’s Sphericity tests. Based on the parallel analysis, four constructs were extracted for further investigation. This study demonstrates alternative guidance for students and researchers in intensively reviewing and re-testing items until satisfactory results are obtained. This study is also expected to help answer questions, fulfil objectives, determine analysis methods, and write research reports on children with learning disability.