Long Story Short

Pigg, Rachel M.; Rauschert, Emily S. J.; Yang, Shih-Ping

doi:10.1525/abt.2023.85.3.169

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…At the end of the semester, students are tested on their mastery of the learning outcomes related to statistics (Supporting File S4) using a summative, graded online problem set. This assignment consists of 20 scenariobased questions (19) that assess students' ability to select appropriate statistical tests and evaluate test results correctly.…”

Section: Students First Use Biostats Level 1 To Analyze a Simple Data...mentioning

confidence: 99%

A Customizable Inquiry-Based Statistics Teaching Application for Introductory Biology Students

Abolins-Abols,

Christian,

Masters

et al. 2024

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Building strong quantitative skills prepares undergraduate biology students for successful careers in science and medicine. While math and statistics anxiety can negatively impact student learning within biology classrooms, instructors may reduce this anxiety by steadily building student competency in quantitative reasoning through instructional scaffolding, applicationbased approaches, and simple computer program interfaces. However, few statistical programs exist that meet all needs of an inclusive, inquiry-based laboratory course. These needs include an open-source program, a simple interface, little required background knowledge in statistics for student users, and customizability to minimize cognitive load, align with course learning outcomes, and create desirable difficulty. To address these needs, we used the Shiny package in R to develop a custom statistical analysis application. Our "BioStats" app provides students with scaffolded learning experiences in applied statistics that promotes student agency and is customizable by the instructor. It introduces students to the strengths of the R interface, while eliminating the need for complex coding in the R programming language. It also prioritizes practical implementation of statistical analyses over learning statistical theory. To our knowledge, this is the first statistics teaching tool where students are presented basic statistics initially, more complex analyses as they advance, and includes an option to learn R statistical coding. The BioStats app interface yields a simplified introduction to applied statistics that is adaptable to many biology laboratory courses.

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Section: Students First Use Biostats Level 1 To Analyze a Simple Data...mentioning

confidence: 99%