STUB Network: Statisticians and Biologists Improving Statistics Education in Introductory Biology

Abstract

Introductory biology courses typically incorporate data collection and analysis into laboratory assignments, and therefore teach some basic statistics. However, these curricula are generally developed without input from statisticians and are taught by instructors, often graduate students, with a range of experience using statistics but no training in statistics education. Given the importance of statistical thinking and other quantitative approaches in biology, the Statistical Thinking in Undergraduate Biology (STUB) network was established to facilitate coordination of best practices and assessment of statistical thinking in introductory biology students. As an example of the network’s benefits, we present a case study involving redesign of laboratory activities in an Introduction to Organismal Form and Function course. Changes include alignment of language with that used in statistics courses, more thorough instruction about experimental design and statistical tests, and use of an online simulation tool shown to improve understanding of statistical inference in statistics courses. These changes are supported by statistics faculty participating in the training of biology teaching assistants. An assessment in progress compares conceptual understanding and attitudes toward statistics before and after the redesigned lab activity; the assessment tool is being used throughout the STUB network, providing comparable data across institutions. This kind of cross‐disciplinary collaboration has the potential to improve statistical thinking in undergraduate biology students, better preparing them for advanced coursework and for careers in modern biology.Support or Funding InformationNSF Research Coordination Network‐Undergraduate Biology Education (RCN‐UBE)