Assessing tree thinking and its role in understanding evolution

Authors: Sam Donovan

Abstract: Understanding evolution involves knowing something about both the mechanisms involved in evolutionary change and the history of life on earth. Most introductory biology curricula emphasize models of evolutionary change but do little to explicitly address historical reconstruction. The phylogenetics instruction there is generally emphasizes tree building or the genealogical relationships among particular groups of organisms (e.g., the primate phylogeny). Familiarity with the broad consequences of descent with modification can provide an important framework for organizing biological knowledge. The assessments described here address a variety of "tree-thinking" understandings and skills including reading and comparing tree topologies, using the information in trees to understand biological patterns, and relating evolutionary concepts to tree diagrams. The goal of developing these assessments was to articulate a range of learning outcomes related to the use of tree diagrams in evolutionary biology, provide feedback for faculty and students about their understanding, and to guide curriculum development that adopts a more sophisticated and systematic approach to teaching about this important aspect of understanding the reasoning involved in doing evolutionary biology.

Tree figures in texts: A framework for unpacking their educational potential

Authors: Sam Donovan, Laura Wilcox

web poster [119 KB GIF]    full poster [3.1 MB PDF]

Abstract: Tree figures play at least two important roles in introductory biology texts. They describe relationships between groups of organisms, often in the form of phylogenetic trees. Additionally, they provide a context for displaying various evolutionary patterns and concepts within a descent with modification framework. In both of these roles the "message" carried in tree figures depends on understanding a variety of mathematical, graphical and disciplinary conventions for "reading" trees. Interpreting tree figures is further complicated by the use of different tree types and the inclusion of extra-topological information. This poster presents a framework for characterizing tree figures in a way that highlights the biological information embedded in these representations. A preliminary analysis of figures from several introductory texts is used to demonstrate the information richness and conceptual complexity of the tree representations. Educational implications related to the importance of, and strategies for, helping students develop tree reading skills are also discussed.

Not losing the forest for the trees: Learning to compare trees and assess support for phylogenetic hypotheses

Authors: Sam Donovan, David Hornack

web poster [54 kb GIF]     full poster [4.9 MB PDF]

Abstract: Too often, particularly in the context of evolution education, trees are treated as true phylogenies rather than hypotheses. Concomitant with this overemphasis on reifying a single tree, the emergence of molecular data is sometimes treated as a panacea for resolving phylogenetic disputes. An alternative approach to evolution education involves engaging students with some of the complexity involved in using multiple data sources to build trees and infer phylogenies. This poster presents a set of teaching resources built around the 17 data sets included in the Whippo-1 collection on the position of Cetacea in the Artiodactyla phylogeny (Gatesy, et al. 1999). The activities can be used to address general issues of tree reading, comparisons of trees to identify areas of congruence and conflict, details of using different types of molecular data, and as a launching point for more extended investigations of phylogenetic questions.

BEDROCK's problem spaces: Educational resources for evolutionary bioinformatics.

Authors: Sam Donovan, John Jungck, Tony Weisstein, Ethel Stanley, Rama Viswanathan, Tia Johnson, John Greenler, Stacey Kiser, Amanda Everse, Kihachiro Umezaki, David Hornack

Abstract: This poster introduces a collection of on-line educational resources that are part of the NSF funded BEDROCK Bioinformatics Education Project. We use the idea of a problem space to describe a way of organizing diverse kinds of resources to support collaboration and student inquiry. While individual problem spaces are built around diverse areas such as viral epidemiology, species conservation, protein structure analysis, and invasive species phylogeography they all share several features. Each problem space is designed to engage students and faculty in collaborative research like problem solving. This involves, in part, identifying open research questions, rich data sets and access to a variety of research quality tools. The problem spaces also share an emphasis on the importance of adopting an evolutionary perspective when working with the comparative analysis of molecular data. Additional information can be found online at http://bioquest.org/bedrock/problem_spaces/.

Bioinformatics problem solving: An introduction to bioinformatics education

Authors: Sam Donovan, Ethel Stanley, Kathleen Greene

Abstract:Computational molecular biology is redefining what it means to do biological research. The analysis of molecular sequence and structure data has opened new doors into both basic research (e.g., mechanisms for evolutionary change, gene identification) and into applications of biotechnology to solve real-world problems (e.g., in agriculture, conservation, health and medicine). This poster is an introduction to some of the molecular biology of hemoglobin and how analysis of this important protein can be used to study phenomena across biochemistry, physiology, population genetics and evolution.

Evolution as a Basis for Bioinformatics Education

Authors: John R. Jungck, John Greenler, and Sam Donovan

Abstract:With the extraordinary number of opportunities available to scientists with expertise in bioinformatics, numerous institutions are developing curricula for both undergraduate and graduate students. These curricula tend to foreground mathematics and computer science in bioinformatics education and thus many students major in these two disciplines with a minimal exposure to biology. Unfortunately, these programs have to date ignored any deep education in evolutionary biology. BioQUEST has a long history of trying to help undergraduates learn long term strategies of research by working on open-ended problems with powerful professional tools with a consistent learner-centered pedagogical philosophy: problem posing, problem solving, and persuading peers. In this case, we (http://www.bioquest.org/bioinformatics) have combined the use of a powerful bioinformatics package, Biology Workbench, (http://workbench.sdsc.edu) developed at the supercomputer centers at the University of Illinois and the University of California San Diego, with typologies of evolutionary problem solving that we have developed to differentiate between spatial, temporal, and genealogical hypotheses or between evolutionary, genetic, and developmental biological levels of analysis.