Incorporating an Interactive Statistics Workshop into an Introductory Biology Course-Based Undergraduate Research Experience (CURE) Enhances Students’ Statistical Reasoning and Quantitative Literacy Skills

Abstract

Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students’ reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce.

An introductory biology research-rich laboratory course shows improvements in students’ research skills, confidence, and attitudes

“…Student performance on the E-EDAT and SRBCI also suggests areas for future improvement. While CURE section students improved their scores over the course of the semester, the scores are relatively low, though comparable to a similar group of introductory biology students [ 41 ]. Purposeful, repeated practice in different contexts in experimental design and statistical analysis targeting areas that have been previously established as difficult [ 18 – 21 , 42 ] is expected to result in improved learning.…”

A Hierarchical Mentoring Program Increases Confidence and Effectiveness in Data Analysis and Interpretation for Undergraduate Biology Students

“…Third, the length of the course/term was limiting, and we suggest 10 weeks at a minimum to accomplish the steps in the scientific process given in Table 1 . Courses with a more limited time allotment may be able to effect gains in statistical reasoning by incorporating a workshop like the one described by Olimpo et al. (2018) .…”

Improving Students’ Understanding of Biological Variation in Experimental Design and Analysis through a Short Model-Based Curricular Intervention

“…Part of the reason that students may have difficulty with using statistics and understanding variation in experimental design and analysis is that statistics is often taught separately from biology laboratory courses (Metz, 2008;Remsburg et al, 2014;Olimpo et al, 2018). Thus, the biological and statistical ideas about variation are separated by course structure.…”

“…Thus, the biological and statistical ideas about variation are separated by course structure. A few curricular interventions have been developed that are situated in biology laboratory and lecture courses (Metz, 2008;Colon-Berlilngeri and Burrowes, 2011;Remsburg et al, 2014;Marsan et al, 2016;Olimpo et al, 2018). These curricula tend to focus on building specific siloed skills in experimental design, interpretation of statistical representations, and/or statistical analysis of data.…”