Clustering the Attitudes towards Statistics and Technology among Medical Post Graduate Students

Introduction: Rapid development of statistics and its application in various sciences along with the growing advances in data manipulation and representation with modern computer technologies accentuate the need for replacing traditional methods in statistics education with modern ones. This study is primarily concerned with measuring the psychometric properties of the Persian version of Students Attitudes toward Statistics and Technology Scale (SASTSc) to obtain a tool for assessing attitudes in educational settings.

Methods: The reliability analysis was undertaken on 192 medical students, 21 Ph.D. students and 171 M.Sc. students who passed or were taking vital statistics course at Ahwaz Jundi Shapour University of medical sciences. SASTSc was adapted based on internationally accepted guidelines for translation and cultural adaptation. The psychometric properties of the Persian version of SASTSc were analyzed using confirmatory factor analysis and internal consistency. To find the attitudes of participated, homogeneous groups were also identified using cluster analysis based on the principal components derived from factor analysis.

Findings: Most medical students showed positive attitudes to learning statistics by technology. The average score of five dimensions of the questionnaire was above 3, indicating students’ positive attitude toward using technology in teaching statistics. Confirmatory factor analysis validated the five-factor structure (statistics cognitive competence, technology cognitive competence, usefulness of technology in statistics, attitudes to the worth and usefulness of statistics and emotion concerning statistics). The comparative fit index was above the cutoff point of 0.80 (CFI=0.851) and the Non-Normed Fit Index was also acceptable (NNFI=0.74). The Root Mean-Square Error of Approximation (RMSEA) equaled 0.081, indicating that the model is a good fit. Cronbach’s α was 0.892 for the whole scale, confirming the scale’s reliability.

Conclusion: The current research provides some evidence for appropriate metric properties of the Persian version of SASTSc. Confirmatory factor analysis validates the five-factor structure of the scale. SASTSc can be used as a valid and reliable tool to determine the opinions of the students in relation to learning statistics with technology in Iranian educational settings.