Effect of visualization on students’ understanding of probability concepts

drawing graphs on white board


Improving the quality and effectiveness of undergraduate education in STEM fields is crucial for preparing both a diverse workforce and a STEM-literate public that is ready to acknowledge and benefit from the advancement of science. STEM sectors of the economy are showing steady growth and careers in these fields are in demand.

The National Science Foundation (NSF) has recently awarded a $300,000 Improving Undergraduate STEM Education (IUSE) grant to Associate Professors Jeffrey Starns, Andrew Cohen (psychological and brain sciences) and Darrell Earnest (teacher education and curriculum studies). This team will develop and test an instructional program in probabilistic reasoning that is designed to help students overcome math challenges by linking mathematical concepts to an intuitive visualization.

Proper reasoning involves calibrating one’s level of confidence that a hypothesis is true to the strength of the evidence available to support the hypothesis. The equation known as Bayes Theorem achieves this calibration, but many students find the equation confusing.

The funded project will teach students a simple visual method that is analogous to Bayes Theorem and then use this method to help students develop a better understanding of how the equation works. The method will be adaptable to many math concepts, and is predicted to be particularly helpful for students who struggle with math.

The most direct application of this method will be for undergraduate statistics education. The multidisciplinary team of researchers seek to create innovative teaching practices using visual methods that promote deep conceptual understanding. A wide range of scientific fields rely on statistical methods, and increasingly Bayesian inference, to make research conclusions. Understanding the basic logic of these methods is critical for science literacy and graduate student success in STEM fields.

The instructional module based on this visualization technique will be tested against standard equation-based teaching methods in a classroom setting. Participants in the study will include both low- and high-scoring students on a test of general math abilities. Also, course materials used to implement the visual method will be made available to additional educators and researchers.

The NSF IUSE Program seeks to advance new approaches to teaching and learning that will improve STEM education for undergraduate students. By testing this new instructional module and sharing what they have learned, the research team of Starns, Cohen, and Earnest hope to guide future efforts to make difficult mathematical concepts more accessible to students.