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Anna Fergusson; Maxine Pfannkuch – Journal of Statistics and Data Science Education, 2024
Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…
Descriptors: High School Students, Statistics Education, Thinking Skills, Computer Science Education
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Reinhart, Alex; Evans, Ciaran; Luby, Amanda; Orellana, Josue; Meyer, Mikaela; Wieczorek, Jerzy; Elliott, Peter; Burckhardt, Philipp; Nugent, Rebecca – Journal of Statistics and Data Science Education, 2022
Think-aloud interviews have been a valuable but underused tool in statistics education research. Think-alouds, in which students narrate their reasoning in real time while solving problems, differ in important ways from other types of cognitive interviews and related education research methods. Beyond the uses already found in the statistics…
Descriptors: Protocol Analysis, Statistics Education, Mathematical Logic, Thinking Skills
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Woodard, Victoria; Lee, Hollylynne – Journal of Statistics and Data Science Education, 2021
As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…
Descriptors: College Students, Statistics Education, Statistical Analysis, Computation
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Peng, Roger D.; Chen, Athena; Bridgeford, Eric; Leek, Jeffrey T.; Hicks, Stephanie C. – Journal of Statistics and Data Science Education, 2021
Teaching data analysis by providing students with real-world problems and datasets allows students to integrate a variety of skills in a situation that mirrors how data analysis actually works. However, whole data analyses may obscure the individual skills of data analytic practice that are generalizable across data analyses. One such skill is the…
Descriptors: Data Analysis, Statistics Education, Teaching Methods, Graduate Students
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Zieffler, Andrew; Justice, Nicola; delMas, Robert; Huberty, Michael D. – Journal of Statistics and Data Science Education, 2021
Statistical modeling continues to gain prominence in the secondary curriculum, and recent recommendations to emphasize data science and computational thinking may soon position algorithmic models into the school curriculum. Many teachers' preparation for and experiences teaching statistical modeling have focused on probabilistic models.…
Descriptors: Mathematical Models, Thinking Skills, Teaching Methods, Statistics Education
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Adams, Bryan; Baller, Daniel; Jonas, Bryan; Joseph, Anny-Claude; Cummiskey, Kevin – Journal of Statistics and Data Science Education, 2021
Since the publishing of Nolan and Temple Lang's "Computing in the Statistics Curriculum" in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop…
Descriptors: Multivariate Analysis, Statistics Education, Teaching Methods, Thinking Skills