Quantitative Modeling in Undergraduate Biology Courses: Teaching Approaches and Student Outcomes

University Of Nebraska-Lincoln, Lincoln NE

Investigators

Abstract

This project aims to serve the national interest in excellent undergraduate biology education that supports students’ quantitative reasoning skills. Toward this goal, the project will examine the effects of biology instructor practices on improving students' quantitative reasoning. As technology advances, scientists have increasingly relied on quantitative approaches to develop models and understandings of natural phenomena. Similarly, citizens need to be able to interpret quantitative information in their daily lives to make important decisions that support the health and well being of society. Several prominent national reports and educational standards have stressed the need for undergraduate biology education to put more emphasis on the development of quantitative skills. However, it remains unclear how instructors design lessons to target quantitative skills and which instructional strategies best support student development of those skills. Thus, the major goals of this project will be to investigate what types of practices faculty use to teach quantitative skills and to determine the extend to which different teaching strategies produce the intended student learning. With more information about what instructional practices are effective, faculty could make better choices about how to help students develop quantitative skills. This project has the potential to produce new insights into connections between instructional practices and student outcomes, while also cultivating and supporting a community of faculty committed to teaching quantitative skills in the life sciences. This project will investigate the development of quantitative modeling skills in undergraduate biology students. Quantitative modeling represents a complex process consisting of using mathematical processes, making interpretations of quantitative information, developing models that describe the given phenomena, and reflecting on the nature and purpose of these models. As technological advancements propel the collection and analysis of massive volumes of data, quantitative modeling has taken on an increasing role in helping researchers describe the dynamics underlying complex global problems. This project will use course observations, artifact analysis, and faculty interviews to characterize how faculty teach quantitative modeling, with emphasis on whether faculty tend to adopt certain groups of practices together. Students enrolled in the courses of participating faculty will complete an assessment, and their responses will be used to determine the interconnections between the different aspects of quantitative modeling. Finally, by measuring the teaching practices and students’ outcomes in biology courses across the country, the project will conduct a large-scale analysis of whether specific groups of teaching practices align with the development of particular aspects of quantitative modeling knowledge and skills. Once completed, this project will have gathered the evidence needed to identify teaching practices that can successfuly integrate quantitative literacy and quantitative biology into undergraduate biology courses. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.