This research project responds to the changing nature of biological science, which has become less fragmented and more focused on models of complex interacting systems. The investigators will study a framework that they hypothesize is well-suited to facilitating students thinking about complex systems across the biological span from sub-cellular genetic processes to evolution and ecology.
The selected framework is Structure-Behavior-Function Theory (SBF), in which a system is represented by the component elements of its structure, the processes that these components perform, and the overall function or purpose of the system. The framework originated in the Artificial Intelligence literature, as an effective strategy for reasoning about designed systems such as electrical circuits. In this research, it will be applied to reasoning about topics such as genes, evolution, and ecology. The investigators will use SBF theory as a pedagogy as a well as an assessment system, in the context of several courses in introductory biology at Michigan State University for both life science majors and non-majors. Students will create, refine, and reason with diagrammatic representations of their own models of the topics they study, and investigators will build software to automate the coding of such representations and the ways they change over the course. The work of approximately 800 students will be analyzed to look for shifts in student reasoning at key points in the instruction, tracking learning trajectories over time. The assessment method will be validated by correlating the scores with those on other forms of parallel assessment, such as multiple-choice, short-answer, and diagrammatic questions.
Overall, the investigators will develop and evaluate a framework for analyzing student understanding, propose strategies for promoting systems thinking and metacognition, and advance research on learning about complex systems. The project is innovative in its application of SBF theory to the pedagogy, assessment, and analysis of introductory biology college courses, and also in its adaptation of software tools to automate the analysis of students models and associated reasoning.
