Research

Investigating and improving undergraduate data analysis and graphing practices in biology

Current Project:

Investigating undergraduate students' evidentiary reasoning with self-made graphs. (2023-present) NSF # 1726180 (PI: Stephanie Gardner; Co-PIs: Joel Abraham, CSU-Fullerton and Eli Meir, SimBiotic Software).

I aim to understand and characterize students' evidentiary reasoning when interpreting graphs of biological data to evaluate predicted relationships and hypotheses. This includes constructing their own graph using a virtual assessment called GraphSmarts, reading and interpreting their graph, deciding whether the data support or refute a prediction, and providing evidence for their claim. I am looking for patterns and connections between their evidence/reasoning and different aspects of their self-made graphs to help inform undergraduate biology instruction in this area and add to biology education literature. This will help us identify certain areas where students may need more support and others that they may already have a strong understanding in graphing and evidentiary reasoning.

People:

Emily Hutton

Anupriya Karippadath (currently at Vanderbilt University)

Lauren Stoczynski (currently at Le Moyne College)

Relevant Publications:

Liu C, Dreger DL, Liu S, Samarapungavan A, Gardner SM, Clase KL & Pelaez N (2022) The Conceptual Analysis of Disciplinary Evidence (CADE) framework as a guide for evidentiary reasoning: A practical implementation in a Hardy-Weinberg Equilibrium (HWE) laboratory investigation, Journal of Biological Education, DOI: 10.1080/00219266.2022.2100450

Past Project:

Grappling with graphs: Researching and improving student graphing skills using an interactive digital graphing tool. (2017-2020) NSF # 1726180 (PI: Stephanie Gardner; Co-PIs: Joel Abraham, CSU-Fullerton and Eli Meir, SimBiotic Software).

Data analysis includes the creation of visual displays to facilitate the exploration of the data to help make meaning and identify potential trends in addition to communicating the findings for others to view. This project aims to make use of a digital graphing tool to reveal student thinking and practices in graphing as part of data analysis. The long-term goal is to develop a suite of digital learning modules to assist instructors and introductory students’ with learning of graphing in biology.

People:

Aakanksha Angra (currently at Georgia State University)
Nouran Amin (currently at Ball State University)
Emily Hutton
Elizabeth Suazo-Flores (currently at University of North Dakota)
Anupriya Karippadath (currently at Vanderbilt University)

Relevant Publications:

Gardner SM, Angra A, and Harsh JA (2023). Supporting Student Competencies in Graph Reading, Interpretation, Construction and Evaluation. CBE-Life Sciences Education. https://doi.org/10.1187/cbe.22-10-0207

Gardner SM, Angra A, Harsh JA. (2023) Evidence Based Teaching Guide: Graphing in Biology. CBE Life Science Education. Retrieved from https://lse.ascb.org/graphing-in-biology/

Gardner, S. M., Suazo-Flores, E., Maruca, S., Abraham, J. K., Karippadath, A., & Meir, E. (2021). Biology Undergraduate Students’ Graphing Practice in Digital Versus Pen and Paper Graphing Environments. Journal of Science Education and Technology, 1-16. doi:10.1007/s10956-020-09886-w

Angra, A., & Gardner, S. M. (2018). The Graph Rubric: Development of a Teaching, Learning, and Research Tool. CBE - Life Sciences Education, 17(4), 1-18. doi:10.1187/cbe.18-01-0007

Angra, A., & Gardner, S. M. (2017). Reflecting on Graphs: Attributes of Graph Choice and Construction Practices in Biology. CBE - Life Sciences Education, 16(3), 1-15. doi:10.1187/cbe.16-08-0245

Angra, A., & Gardner, S. M. (2016). Development of a Framework for Graph Choice and Construction. Advances in Physiology Education, 40(1), 123-128. doi:10.1152/advan.00152.2015