Academic journal article Journal of College Science Teaching

Infusion of Quantitative and Statistical Concepts into Biology Courses Does Not Improve Quantitative Literacy

Academic journal article Journal of College Science Teaching

Infusion of Quantitative and Statistical Concepts into Biology Courses Does Not Improve Quantitative Literacy

Article excerpt

For more than a decade, repeated calls have been made to increase the quantitative literacy of undergraduate science students, especially biology students (Brewer & Smith, 2011; National Research Council, 2003, 2009). Traditionally, biology majors have been required to take one or two semesters of calculus, and at some institutions, one semester of statistics. However, students are unlikely to transfer the quantitative skills that they learn in these mathematics and statistics classes to their biology classes, as students often consider them separate domains of knowledge (National Research Council, 2000). As a result, integration of quantitative skills directly in science courses or teaching mathematics courses using examples from appropriate science disciplines has been encouraged (Feser, Vasaly, & Herrera, 2013; Gross, 2004; Marsteller, 2010; Marsteller et al., 2010; Robeva & Laubenbacher, 2009).

Faculty might explicitly integrate biology and quantitative skills from mathematics and statistics when one of the learning goals of the course is quantitative skills and when quantitative skills are taught directly. This approach has been successful in a variety of contexts. For example, at some universities, life sciences calculus courses have been developed that teach calculus concepts in the context of biological examples (Duffus & Olifer, 2010; Eaton & Highlander, 2017; Usher et al., 2010). A similar approach has been used in statistics (Watkins, 2010). In addition, specific bio-math modules have been developed for integration into a variety of mathematics courses (Robeva, Davies, Hodge, & Enyedi, 2010). The opposite approach--explicitly integrating quantitative skills into biology courses through the use of modules designed to teach quantitative skills--also has been used (Colon-Berlingeri & Burrowes, 2011; Duffus & Olifer, 2010; Goldstein & Flynn, 2011; Hester, Buxner, Elfring, & Nagy, 2014; Hodgson, Keck, Patterson, & Maki, 2005; Hoffman, Leupen, Dowell, Kephart, & Leips, 2016; Madlung, Bremer, Himelblau, & Tullis, 2011; Metz, 2008; Robeva et al., 2010; Speth et al., 2010).

Although explicit integration of biology and quantitative skills results in increased quantitative literacy, whether implicit integration of these skills also leads to improved quantitative literacy is less clear. Many biology courses introduce or reinforce quantitative skills implicitly in a variety of ways ranging from the discussion of data and figures from the primary literature to the use of mathematical models to describe biological phenomena (e.g., population growth). However, the key quantitative concepts or skills may not be taught directly. The distinction between explicit and implicit teaching are often made in the teaching and learning of languages (Brown, 2014). For example, students can be explicitly taught the rules of grammar for a language, or they can implicitly learn the rules through examples. Evidence from the teaching and learning of second languages suggests that implicit learning along with explicit attention to errors is perhaps most effective (Ellis, 2017).

Whether implicit integration of quantitative skills is sufficient to improve students' quantitative literacy is unknown. To address this question, I explored changes in quantitative literacy over two semesters in two different courses in which these skills were taught implicitly. I examined statistical literacy in my upper level ecology course, as understanding ecological research depends heavily on an understanding of statistics. In contrast, I explored general quantitative literacy in my organismal biology course. Because my organismal biology course is targeted at sophomores, I place a greater emphasis on basic interpretation of graphs and tables from the primary literature with less emphasis on statistics.

Methods

Experiment 1: Statistical literacy in an ecology lecture course

Over the course of two semesters, I examined whether students in my upper level ecology course exhibited improved statistical literacy as a result of exposure to statistical concepts in class. …

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