ASSESSING STATISTICAL REASONING

By Joan Garfield. Statistics Education Research Journal, 2003

238 citations recorded by the source corpus.

This paper begins with a discussion of the nature of statistical reasoning, and then describes the development and validation of the Statistical Reasoning Assessment (SRA), an instrument consisting of 20 multiple-choice items involving probability and statistics concepts. Each item offers several choices of responses, both correct and incorrect, which include statements of reasoning explaining the rationale for a particular choice. Students are instructed to select the response that best matches their own thinking about each problem. The SRA provides 16 scores which indicate the level of students’ correct reasoning in eight different areas and the extent of their incorrect reasoning in eight related areas. Results are presented of a cross-cultural study using the SRA to compare the reasoning of males and females in two countries. First published May 2003 at Statistics Education Research Journal: Archives

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/57558bb7e7b922cb837f82852392057f0d596cfc

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Citations in the corpus

What Does Research Suggest About the Teaching and Learning of Introductory Statistics at the College Level? A Review of the Literature (2008, methodology): “Studies in this area that involved a training component and produced positive effects on overcoming misconceptions may be limited in their ability to generalize to educational settings (e.g., a statistics course) due to the artificial nature of the training in a lab setting.”
ASSESSING STUDENTS’ CONCEPTUAL UNDERSTANDING AFTER A FIRST COURSE IN STATISTICS (2007, background): “The Statistical Reasoning Assessment (SRA) was one attempt to develop and validate a measure of statistical reasoning, but it focuses heavily on probability, and lacks items related to data production, data collection, and statistical inference (Garfield, 2003).”
COGNITIVE AND NON-COGNITIVE FACTORS RELATED TO STUDENTS’ STATISTICS ACHIEVEMENT (2010, background): “Keywords: Statistics education research; Statistics attitudes; Statistics anxiety; Mathematical competence; Structural equation modeling”
The effect of distributed practice on students’ conceptual understanding of statistics (2011, background): “…was based on literature on comprehension (Olson and Biolsi 1991; McNamara et al. 1996), comprehension of statistics (Budé et al. 2009; Feltovich et al. 1993; Garfield 2003; Schau and Mattern 1997; Gijbels et al. 2005; Jonassen et al. 1993), and on our definition of conceptual understanding.”
Students’ misconceptions of statistical inference: A review of the empirical evidence from research on statistics education (2007, unknown): “2 Statistical reasoning assessment, see Garfield (2003).”
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 (2010, background): “In particular, research reports indicate that students are experiencing difficulties with introductory statistics, and emerge with a lack of understanding of core concepts, such as statistical variation (delMas & Liu, 2005), chance (Garfield, 2003), graphical representations of distributions (Bakker”
ATTITUDES AND ACHIEVEMENT IN STATISTICS: A META-ANALYSIS STUDY (2012, methodology): “Tempelaar et al. and Estrada and Batanero used the Statistical Reasoning Assessment (SRA) instrument (Garfield, 2003) and Stone et al. used the Statistics Concept Inventory (SCI) to measure students’ statistics achievement.”
How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics (2007, background): “…misconceptions and errors related to additional topics such as contingency tables (Batanero et al., 1996), sampling distributions (Yu & Behrens, 1995), significance tests (e.g. Falk & Greenbaum, 1995), and a variety of errors in statistical reasoning (e.g. Garfield, 2003; Tempelaar et al., 2006).”
STATISTICAL LITERACY: A COMPLEX HIERARCHICAL CONSTRUCT (2003, unknown): “These items were adapted from items used in previous research (Fischbein & Gazit, 1984; Garfield, 2003; Green 1982, 1983a; Jacobs, 1999; Konold & Higgins, 2002; Konold & Garfield, 1992; Nisbett, Krantz, Jepson, & Kunda, 1983; Pollatsek, Well, Konold, Hardiman, & Cobb, 1987; Tversky & Kahneman, 1983;”