Students in every discipline in higher education take at least one course in statistics. Therefore, it is necessary to enhance students’ understanding of statistics and their achievement in such courses by considering several factors that might contribute to this enhancement. Students’ attitudes toward statistics are a critical factor that influences their performance in statistics courses, and thus an accurate measurement of attitudes is needed. The survey of attitudes toward statistics (SATS-36) is widely used in measuring attitudes toward statistics; thus, it is important to ensure that its items accurately assess this construct. Therefore, the purpose of the current study was to validate this survey when administered to a convenience sample of 423 university students. Using the Rasch rating scale model, the current study examined the dimensionality, item fit to the Rasch model, item and person reliabilities, functionality of response categories, and distribution of the SATS-36 items along the attitudes toward statistics continuum.
The findings revealed excellent item and person reliabilities (greater than 0.90) and the uni-dimensionality of the survey. Additionally, all items were closely aligned with the respondents, and the response categories were well-functioning as each category had more than 10 observations and outfit statistics were all low. However, some improvements were suggested. All items on the effect subscale and some others from different subscales need to be altered in content, deleting three items (two from the value subscale and one from the difficulty subscale) and adding more items to have a better distribution of items along the continuum. Finally, the number of response categories is recommended to be reduced to five instead of seven to have a more efficient rating scale. The findings of the current study imply that even though great care has been taken in the development of this survey, examining the quality of its items and the utility of its rating scale in new settings, and using different validation approaches is necessary.
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Article Type: Research Article
EURASIA J Math Sci Tech Ed, 2022, Volume 18, Issue 12, Article No: em2190
Publication date: 16 Nov 2022
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