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Climate change is a major concern to undergraduate students. Understanding climate change relies on an understanding of polar regions. However, courses on polar regions are rare at undergraduate institutions. Polar ENgagement through GUided INquiry (PENGUIN) modules were designed to give students experience with polar research in a variety of standard courses, including physics, computer science, physical chemistry, and economics, through using course-specific and computational tools to analyze polar data. Here, we present a new PENGUIN module taught in a statistics class, in which students apply statistical tools to ice core data to reconstruct past temperature records. Quantitative student responses on pre- and post-surveys were collected in a quasi-experimental context to assess student knowledge gains for a test group of 91 students and a control group of 73 students (who did not complete the module). Test-group students made statistically significant increases of 25 to 46% on all six statistics questions, with a normalized gain of 56%. By contrast, control group statistics knowledge gains ranged from −4 to 25%, with statistically significant increases for only three questions and a normalized gain of 22%. For polar research questions, the test group demonstrated increases in correct responses to polar research questions (11 to 31%), with statistically significant improvements (p < .05) of 22-31% on 3 of 6 polar research questions. These findings support the conclusion that PENGUIN modules can successfully teach course concepts while increasing polar literacy.
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When the Data Drive the Learning
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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- PAR ID:
- 10359337
- Date Published:
- Journal Name:
- Proceedings of the 2021 International Association for Statistical Education Satellite Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.52041/iase.fjrqt
