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A Cognitive Approach to Implementing Tree Thinking in High Schooland College Biology Curricula

Assessment Intervention Learning Policy Training


Chair Professor
Beth Shinn

Director of Graduate Studies
Professor Paul Dokecki

Director of Undergraduate Studies
Professor Brian Griffith

Administrative Officer
Sandy Strohl


Diagrams are ubiquitous in STEM fields. In biology, a type of hierarchical diagram called a cladogram is used to depict evolutionary histories among species or groups of species. These diagrams are the most important tool that contemporary scientists use to reason about evolutionary relationships. Cladograms provide a visualization of the products of macroevolutionary processes. Consequently, to understand cladograms is to understand macroevolution. Such understanding has been termed “tree thinking.” Recently, a number of researchers have argued that this approach must be incorporated into the evolution curriculum if any progress towards meaningful science literacy in this domain is to be made. The present proposal has three primary goals. The first goal is to identify and understand the cognitive and perceptual factors that influence high school and college students’ ability to understand and reason from cladograms. This information is critical for developing (a) effective curricula for teaching tree thinking and (b) assessments that will allow students to demonstrate their competence in this domain (therefore, their understanding of macroevolution). These studies will use standard experimental psychology methods in which cognitive and perceptual factors hypothesized to affect cladogram understanding and reasoning will be manipulated and effects on performance will be noted. Responses will include constructing cladograms, retrieving information from cladograms, and making inferences based on information provided in cladograms. Dependent measures will include accuracy, types of errors made, and types of evidence (reasoning) cited in support of one’s answer. Data analytic methods will include relevant parametric (e.g., ANOVA) and non-parametric (e.g., chi-square) statistical analyses. The second goal is to create novel curricula, where none currently exist, to teach tree thinking at the undergraduate and high school levels. At the undergraduate level, we will focus on students in an upper-level biology class (e.g., biology of arthropods). At the high school level, we will focus on basic biology taught to tenth graders. These two quite different levels of instruction will enable us to develop curriculum materials for a broad range of topics necessary for students to become fully competent at tree thinking. The final goal is to provide an initial implementation and assessment of our curricula in the aforementioned biology classes. To assess the impact of our instruction, students will complete a pretest prior to instruction and a posttest after instruction. The items for these tests will be selected from among the tasks used in the cognitive studies designed to accomplish our first goal. Data analytic methods will include relevant parametric (e.g., ANOVA) and non-parametric (e.g., chi-square) statistical analyses. The cognitive experiments involving college students will be conducted primarily at Vanderbilt University in Nashville, TN. These students are predominantly white and upper-middle to upper class. Based on our previous and current subject recruitment efforts, the sample will be largely female. Some data, particularly from students with stronger backgrounds in biology, may also be collected at Western Carolina University in Cullowhee, NC. These students mostly come from NC (90%), largely from rural counties; 90% are white. The curriculum implementation in an upper-level biology class will occur at Western Carolina University. The tenth-grade curriculum will be field-tested at a large (≈1200 students), academically rigorous county high school in rural western North Carolina. The students at this school are largely white.