Literaturnachweis - Detailanzeige
| Autor/inn/en | Guzman, Laura Melissa; Pennell, Matthew W.; Nikelski, Ellen; Srivastava, Diane S. |
|---|---|
| Titel | Successful Integration of Data Science in Undergraduate Biostatistics Courses Using Cognitive Load Theory |
| Quelle | In: CBE - Life Sciences Education, 18 (2019) 4, Artikel 49 (10 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1931-7913 |
| Schlagwörter | Undergraduate Study; Statistics; Biology; College Science; College Mathematics; Data; Integrated Activities; Cognitive Processes; Difficulty Level; Assignments; Instructional Effectiveness; Programming Languages; Foreign Countries; Computer Science Education; Student Attitudes; Undergraduate Students; Canada (Vancouver) |
| Abstract | Biostatistics courses are integral to many undergraduate biology programs. Such courses have often been taught using point-and-click software, but these programs are now seldom used by researchers or professional biologists. Instead, biology professionals typically use programming languages, such as R, which are better suited to analyzing complex data sets. However, teaching biostatistics and programming simultaneously has the potential to overload the students and hinder their learning. We sought to mitigate this overload by using cognitive load theory (CLT) to develop assignments for two biostatistics courses. We evaluated the effectiveness of these assignments by comparing student cohorts who were taught R using these assignments (n = 146) with those who were taught R through example scripts or were instructed on a point-and-click software program (control, n = 181). We surveyed all cohorts and analyzed statistical and programming ability through students' lab reports or final exams. Students who learned R through our assignments rated their programming ability higher and were more likely to put the usage of R as a skill in their curricula vitae. We also found that the treatment students were more motivated, less frustrated, and less stressed when using R. These results suggest that we can use CLT to teach challenging material. (As Provided). |
| Anmerkungen | American Society for Cell Biology. 8120 Woodmont Avenue Suite 750, Bethesda, MD 20814-2762. Tel: 301-347-9300; Fax: 301-347-9310; e-mail: ascbinfo@ascb.org; Website: http://www.ascb.org |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2020/1/01 |
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