ASSESSING STUDENTS’ CONCEPTUAL UNDERSTANDING AFTER A FIRST COURSE IN STATISTICS
By R. delMas, Joan Garfield, A. Ooms, B. Chance. 2007
334 citations recorded by the source corpus.
This paper describes the development of the CAOS test, designed to measure students’ conceptual understanding of important statistical ideas, across three years of revision and testing, content validation, and realiability analysis. Results are reported from a large scale class testing and item responses are compared from pretest to posttest in order to learn more about areas in which students demonstrated improved performance from beginning to end of the course, as well as areas that showed no improvement or decreased performance. Items that showed an increase in students’ misconceptions about particular statistical concepts were also examined. The paper concludes with a discussion of implications for students’ understanding of different statistical topics, followed by suggestions for further research.
Subfields: Education, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/34237c83fe369995a8493ccfd334068d86d21a65
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In Education
In Statistics and Probability
Citations in the corpus
- Development and Assessment of a Preliminary Randomization-Based Introductory Statistics Curriculum (2011, methodology): “In essence, instead of a course that emphasizes the logic of statistical inference, students get a course that emphasizes a series of asymptotic tests with complicated conditions (Cobb 2007).”
- Interactive Learning Online at Public Universities: Evidence from a Six-Campus Randomized Trial. (2014, methodology): “In a study of 763 students at 20 institutions located in 14 states, the average increase was nine percentage points (delMas et al., 2007).”
- Measuring Skewness: A Forgotten Statistic? (2011, background): “Even with the ability to verbally describe a distribution from a visual display, researchers have found (delMas et al. 2007) that students cannot translate their understanding of shape when asked to compare numerical statistics such as the mean and median.”