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Creators/Authors contains: "Higgins, T."

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  1. ; ; ; (, International Association for Statistical Education)
    Jones, E M (Ed.)
    Accepted Manuscript Full Text Available
  2. ; ; ; (, International Association for Statistical Education)
    Jones, E M (Ed.)
    Accepted Manuscript Full Text Available
  3. ; ; ; (, International Association for Statistics Education)
    We examine how developers of data science curricula determine what makes a pedagogically effective dataset enabling 10–14 year-old students (“middle school” in the United States) to engage in the data investigation cycle by posing their own questions about relationships among variables. We describe strategies for curating existing datasets to address goals for learning about data, and for optimizing the use of these datasets once they are curated. We investigate how data science educators can transform existing datasets into ones appropriate for students with little data experience, drawing on our experience working with several publicly available datasets, which students explored in CODAP (the Common Online Data Analysis Platform). 
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  4. ; ; ; ; (, Proceedings of the 2021 International Association for Statistical Education Satellite Conference)
    What happens when a diverse group of youth ages 11 through 14 are introduced to data science using authentic, public, multivariate data in an out-of-school context assuming no special prerequisite knowledge? We designed three 10-hour Data Club modules in which real-world data and the questions students asked of such data drove the learning process. Each module was grounded in a topic that youth connected with at a personal level. Youth learned how to use a free online data platform that made it easy to rearrange, group, filter, and graph data. Within the progression of the module, we used youths’ own questions, data moves, and data visualizations to engage them in critical inquiry and foster productive habits of mind for working with data. Our goal was for youth to emerge from the Data Clubs experience feeling empowered to interact with, ask questions of, and reason about and from data. 
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    Full Text Available