Development and Validation of a Scale for Measuring Instructors' Attitudes toward Concept-Based or Reform-Oriented Teaching of Introductory Statistics in the Health and Behavioral Sciences
By R. Hassad. 2010
3,973 citations recorded by the source corpus.
Despite more than a decade of reform efforts, students continue to experience difficulty understanding and applying statistical concepts. The predominant focus of reform has been on content, pedagogy, technology and assessment, with little attention to instructor characteristics. However, there is strong theoretical and empirical evidence that instructors' attitudes impact the quality of teaching and learning. The objective of this study was to develop and initially validate a scale to measure instructors' attitudes toward reform-oriented (or concept-based) teaching of introductory statistics in the health and behavioral sciences, at the tertiary level. This scale will be referred to as FATS (Faculty Attitudes Toward Statistics). Data were obtained from 227 instructors (USA and international), and analyzed using factor analysis, multidimensional scaling and hierarchical cluster analysis. The overall scale consists of five sub-scales with a total of 25 items, and an overall alpha of 0.89. Construct validity was established. Specifically, the overall scale, and subscales (except perceived difficulty) plausibly differentiated between low-reform and high-reform practice instructors. Statistically significant differences in attitude were observed with respect to age, but not gender, employment status, membership status in professional organizations, ethnicity, highest academic qualification, and degree concentration. This scale can be considered a reliable and valid measure of instructors' attitudes toward reform-oriented (concept-based or constructivist) teaching of introductory statistics in the health and behavioral sciences at the tertiary level. These five dimensions influence instructors' attitudes. Additional studies are required to confirm these structural and psychometric properties.
View Paper: https://www.semanticscholar.org/paper/8a29d603e6de4e7aedb89e45e30da94f50796bac
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- C. Rudolph
- H. Zacher
- Chieh-Peng Lin
- Hongwei He
- R. Rauvola
- Jon D. Elhai
- Kristi N. Lavigne
- Marco S. DiRenzo
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