Modeling Tree-Thinking: Measuring Evolutionary Relatedness Understanding and Examining the Interaction of Factors that Influence Tree-Thinking

Texas State University - San Marcos, San Marcos TX

Investigators

Abstract

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Phylogenetic trees are common diagrams in biology that depict organisms and their evolutionary history. As evolution is considered a fundamental topic that underpins much of biology, understanding these tree diagrams is critical. The ability to read such trees is often referred to as "tree-thinking" in the literature. Undergraduate students often find tree-thinking very difficult. This study is designed to examine factors that influence tree-thinking such as mental rotation and understanding of evolution. At present, little is known about the ways these factors interact and the ways in which students' everyday ideas about grouping organisms affect tree-thinking. This project aims to develop assessments of student thinking. Researchers and educators can use the knowledge gained from this study to design better interventions. The goals of this study are to (A) create an evidence-based assessment measuring multiple conceptions of evolutionary relatedness, (B) model the different factors that may influence tree-thinking, and (C) explore the ways in which undergraduate students scan tree diagrams. The assessment will be created based on the findings of the primary investigator's dissertation work. Data fit will be determined with data from over 200 participants at two undergraduate institutions. Validity will be determined using expert judgement, confirmatory factor analysis, and response process testing. Reliability will be determined by examining internal consistency and test-retest reliability. Modeling will be conducted at the same institutions with the aforementioned instrument as well as other instruments measuring factors such as spatial reasoning, evolution acceptance, evolution understanding, and tree-reading and manipulation abilities. Several models will be evaluated using structural equation modeling and later compared with model evaluation metrics such as Akaike Information Criterion. The final phase of this study will be exploratory where students from the aforementioned courses are grouped using latent profile analysis. Representatives from each group will conduct tree-thinking tasks while being monitored by eye-tracking equipment. Students' scanpaths will be examined with respect to their tree-thinking abilities. This study is designed to develop assessments of student thinking that relate to evolutionary relatedness that can be used for research purposes or in educational settings that can better explain the factors that influence tree-thinking. The project responds to the STEM Education Postdoctoral Research Fellowship (STEM Ed PRF) program that aims to enhance the research knowledge, skills, and practices of recent doctorates in STEM, STEM education, education, and related disciplines to advance their preparation to engage in fundamental and applied research that advances knowledge within the field. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.