The Greenhouse Effect: Using Student-Generated Agricultural Data to Warm Up Students for Data-Based Decision Making
This article describes a collaborative project across multiple institutions to compare two versions of a regression activity: (a) a website version that collected student data through an online simulation with corresponding apps for visualization and (b) a traditional paper handout version that had...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-01-01
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| Series: | Journal of Statistics and Data Science Education |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/26939169.2024.2441672 |
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| Summary: | This article describes a collaborative project across multiple institutions to compare two versions of a regression activity: (a) a website version that collected student data through an online simulation with corresponding apps for visualization and (b) a traditional paper handout version that had a static dataset. This allowed us to evaluate the differences in student learning and attitudes when students have a stronger connection with the data through an interactive—and hopefully fun—data-collection process than they do when they are given a worksheet with a pre-collected dataset. While student and instructor responses indicated they liked the activity in both formats, the PreTest and PostTest results showed evidence of a higher gain in knowledge with the website version. Finally, we discuss how the website version connects with pedagogical strategies for the development of modern statistics and data science courses. |
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| ISSN: | 2693-9169 |