Case-Based Learning for Teaching Statistical Collaboration: Development, Application, and Evaluation
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| Titel: | Case-Based Learning for Teaching Statistical Collaboration: Development, Application, and Evaluation |
|---|---|
| Autoren: | Mario Davidson, Regina Russell |
| Quelle: | Journal of Statistics and Data Science Education, Pp 1-24 (2025) |
| Verlagsinformationen: | Informa UK Limited, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | Consulting, LC8-6691, communication, facilitating classroom, statistical analysis plan, ethics, Probabilities. Mathematical statistics, Special aspects of education, QA273-280 |
| Beschreibung: | Case-based learning (CBL) is a highly effective approach in health professions education that remains underutilized in the field of statistics. To promote broader adoption, we have developed realistic cases designed to help learners practice critical thinking and devise appropriate solutions for complex scenarios. These cases, used in our graduate-level statistical collaboration course, incorporate social factors and real-world implications. The first case explores a newly graduated biostatistician navigating the challenges of meeting a client's expectations. The second focuses on a junior biostatistician developing a statistical analysis plan for a client with limited statistical knowledge. The third case, inspired by the development of the American Statistical Association's ethical guidelines, deliberates their need. Both training materials and fully developed cases are provided. We also discuss strategies for educators to create and facilitate similar cases. By engaging students in thoughtful consideration of these scenarios within a safe, structured environment, we encourage them to examine their assumptions and conclusions. This preparation equips them for real-world roles as consultants and team scientists. Additionally, student feedback from course evaluations and surveys indicates strong support for CBL, with the majority recommending its use in similar educational contexts. |
| Publikationsart: | Article |
| Sprache: | English |
| ISSN: | 2693-9169 |
| DOI: | 10.1080/26939169.2025.2525140 |
| Zugangs-URL: | https://doaj.org/article/2308683173d44edba900c06bef9b38ec |
| Rights: | CC BY |
| Dokumentencode: | edsair.doi.dedup.....fff4d35c7b5dc788e0c3d5343753a62d |
| Datenbank: | OpenAIRE |
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