AI Summary & Key Takeaways
AI InsightAccording to the findings, the researchmodel could provide complete measurement invariance.
📌 3 Key Takeaways
Abstract
Measurement invariance analyses are carried out in order to findevidence for the structural validity of the measurement tools used in the field ofeducational sciences and psychology. The purpose of this research is to examinethe measurement invariance of Science Motivation and Self-Efficacy Modelconstructed by Instrumental Motivation to Learn Science and Science Self-Efficacy subscales found in the PISA 2015 Student Questionnaire across differentgroups in the Turkish sample survey. The analysis was carried out with the dataobtained from 4583 students that met the analysis assumptions. The measurementinvariance of the model in terms of gender and statistical regional groups wasexamined by the structural equation modeling (SEM) technique. Firstly, the datawas examined to determine whether the assumptions for the analyses were met.Then, measurement models were verified by performing confirmatory factoranalysis (CFA). The measurement invariance across genders and statistical regionswas tested by multi-group confirmatory factor analysis (MGCFA). UnweightedLeast Squares (ULS) method was used as the estimation method in CFA andMGCFA stages. In order to make final decisions about the stage of measurementinvariance models hold, Comparative Fit Index (CFI) was used. The results of thestudy show that the research model ensures all stages of invariance across gendergroups and regions. Science Motivation and Self-Efficacy Model illustrates that itis valid to make comparisons between scores of male and female students orstudents from different regions of Turkey. According to the findings, the researchmodel could provide complete measurement invariance.