The graph construction competency model for biology (GCCM-Bio): A framework for instruction and assessment of graph construction
Biologists represent data in visual forms, such as graphs, to aid data analysis and communication. However, students struggle to construct effective graphs. Although some studies explore these difficulties, we lack a comprehensive framework of the knowledge and skills needed to construct graphs in biology. In the present article, we describe the development of the Graph Construction Competency Model for Biology (GCCM-Bio), a framework of the components and activities associated with graph construction. We identified four broad knowledge areas for graph construction in biology: data selection, data exploration, graph assembly, and graph reflection. Under each area, we identified activities undertaken when constructing graphs of biological data and refined the GCCM-Bio through focus groups with experts in biology and statistics education. We also ran a scoping literature review to verify that these activities were represented in the graphing literature. The GCCM-Bio could support instructors, curriculum developers, and researchers when designing instruction and assessment of biology graph construction.
Authors
- Elizabeth Suazo‐Flores (ORCID: https://orcid.org/0000-0001-6565-3879)
- Joel K. Abraham (ORCID: https://orcid.org/0000-0003-3999-5634)
- Anupriya Karippadath (ORCID: https://orcid.org/0009-0009-9666-375X)
- Susan Maruca
- Eli Meir (ORCID: https://orcid.org/0000-0002-1874-1750)
- Stephanie M. Gardner (ORCID: https://orcid.org/0000-0003-3988-343X)
- Alec Lamond
Institutions
- California State University, Fullerton (US)
- Vanderbilt University (US)
- Purdue University West Lafayette (US)
- University of North Dakota (US)
- SimBiotic Software (United States) (US)
Publication Details
- Journal
- BioScience
- Published
- 2025-06-20
- DOI
- https://doi.org/10.1093/biosci/biaf060
- Citations
- 2
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- National Science Foundation