Association for Biology Laboratory Education

Statistics and Data Visualization in CUREs
    

Ania A. Majewska

Advances in Biology Laboratory Education, 2026, Volume 46

https://doi.org/10.37590/able.v46.extabs29

Supplemental Materials: https://doi.org/10.37590/able.v46.sup29

Abstract

Course-based undergraduate research experiences (CUREs) often require students to analyze and visualize data gathered during the course, yet teaching these skills is challenging. This workshop introduces instructors to DataClassroom.com, a web-app that bridges the gap between basic spreadsheet tools and advanced programming languages, and can be used to engage students in data analysis, visualization and interpretation of results. Instructors can scaffold activities aligning with CURE learning objectives, or with desired statistical tests, such as t-tests. Proper data formatting is essential: analysis requires “tidy format” data where each variable forms a column and each observation forms a row. Data files can be imported and shared among users within instructor-created classes. The formatting requirement provides opportunities to discuss best practices for data entry and management, including consistent naming conventions and formatting. The platform’s graphing capabilities enable discussions about selecting appropriate visualizations for specific data types. DataClassroom.com generates high-quality, customizable graphs and statistical outputs that students can use in their project reports. Overall, DataClassroom.com offers valuable support for instructors seeking to incorporate data literacy into their courses.

Keywords:  data analysis, data literacy, figures, quantitative skills

University of Manitoba (2025)