Successful Integration of Data Science in Undergraduate Biostatistics Courses Using Cognitive Load Theory
| Autor: | Matthew W. Pennell, Diane S. Srivastava, Laura Melissa Guzman, Ellen Nikelski |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
Models Educational Control (management) Emotions Biostatistics computer.software_genre 010603 evolutionary biology 01 natural sciences General Biochemistry Genetics and Molecular Biology Article Education Software Cognition Surveys and Questionnaires Mathematics education ComputingMilieux_COMPUTERSANDEDUCATION Humans Learning Students Curriculum Motivation business.industry 4. Education 05 social sciences Data Science 050301 education Scripting language business 0503 education computer Cognitive load |
| Zdroj: | CBE Life Sciences Education |
| ISSN: | 1931-7913 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|