Exploring Factor Structures Of A Thinking Questionnaire
DOI:
https://doi.org/10.33102/uij.vol31no.199Keywords:
factor analysis, , factor structure, Principal Component Analysis (PCA), thinking questionnaireAbstract
The purpose of this study was to investigate the construct validity of a thinking questionnaire through Factor Analysis over a Malaysian university students’ sample. The questionnaire is a 5 point Likert scale survey ranging from Strongly Agree, Agree, Neutral, Disagree and Strongly Disagree, intended to measure students’ self-reflection on their thinking upon their Invention Project. A total of 350 undergraduate students from various faculties participated in this study. Principal Component Analysis was used because the primary purpose was to identify and compute composite thinking scores for the factors underlying the Thinking questionnaire. The five factor solution, which explained 52.4% of the variance was chosen because of the ‘levelling off’ of eigenvalues on the scree plot after five factors, and was also confirmed by the Monte Carlo Parallel Analysis which indicated smaller values of the 5 factors compared to the eigenvalues displayed in the SPSS.
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