Although statistics education research has focused on students’ learning and conceptual understanding of statistics, researchers have only recently begun investigating students’ perceptions of statistics. The term perception describes the overlap between cognitive and non-cognitive factors. In this mixed-methods study, undergraduate students provided their perceptions of statistics and completed the Survey of Students’ Attitudes Toward Statistics-36 (SATS-36). The qualitative data suggest students had basic knowledge of what the word statistics meant, but with varying depths of understanding and conceptualization of statistics. Quantitative analysis also examined the relationship between students’ perceptions of statistics and attitudes toward statistics. We found no significant difference in mean pre- or post-SATS scores across conceptualization and content knowledge categories. The implications of these findings for education and research are discussed.
First published November 2012 at Statistics Education Research Journal: Archives
The Survey of Attitudes Toward Statistics (SATS) is a widely used family of instruments for measuring attitude constructs in statistics education. Since the development of the SATS instruments, there has been an evolution in the understanding of validity in the field of educational measurement emphasizing validation as an on-going process. While a 2012 review of statistics education attitude instruments noted that the SATS family had the most validity evidence, two types of challenges to the use of these instruments have emerged: challenges to the interpretations of scale scores and challenges using the SATS instruments in populations other than undergraduate students enrolled in introductory statistics courses. A synthesis of the literature and empirical results are used to document these challenges.
It is common in agricultural research to have experimental units that consist of multiple observational units. For instance, treatments may be applied to pens of animals, pens being the experimental units, while weights are measured on individual animals, the observational units. If there are a small number of experimental units, the power of statistical tests for treatment effects can be small regardless of the number of observational units. We show that it is possible to increase the power of such statistical tests by taking advantage of prior knowledge of the intrac1ass correlation. Our assertion is that such prior knowledge is often available although infrequently used. We present several simple methods for taking advantage of this prior knowledge and show that the power of tests based on these methods can be substantially greater than the power of conventional tests especially when the number of experimental units is small.
The Student Survey of Motivational Attitudes toward Statistics is a new instrument designed to measure affective outcomes in statistics education. This instrument is grounded in the established Expectancy-Value Theory of motivation and is being developed using a rigorous process. This paper provides an overview of the four pilot studies that have been conducted during the survey development process. Additionally, a description of the methods used for analyzing the data and the way the results are used to holistically make decisions about revisions to the survey is included. Brief confirmatory factor analysis results are included from two pilot studies to demonstrate that substantial progress has been made on the development. Once finalized (Spring 2023), the survey will be made freely available.
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