Bioscience research has become increasingly quantitative as researchers take advantage of large data sets generated by high-throughput technologies, long term and large scale data collection, and increased computational power to tackle more complex biological problems. As a result, quantitative skills are among the core competencies for career success in biology and thus, have an important place in all bioscience curricula (NRC, 2003; AAAS & NSF, 2011; College Board, 2012; AAMC-HHMI, 2009). Despite this, most bioscience courses do not yet emphasize the key role of quantitative skills in biological practice. In part, this is because there is no disciplinary expectation or “norm” for quantitative approaches within bioscience courses, and in addition, different sub-disciplines within biology emphasize different quantitative skills.
The current structure of teaching biology and mathematics as isolated, independent knowledge domains creates a limitation among students and faculty to identify and understand the intersection between mathematical and biological concepts. This limitation is a major challenge to seamlessly integrating quantitative skills into the pedagogical approaches in biology courses (Usher et al., 2010). Successful use of quantitative skills requires quantitative reasoning (QR). QR encompasses the ability to think about biological problems quantitatively, identify and apply appropriate math skills, and analyze the validity of quantitative results in the biological context (Mayes et al., 2013). The applied nature of QR makes it imperative to include disciplinary context to address specific real world problems (NICHE, 2015). Thus, application of mathematical ideas within biology is comparable to a language barrier, although it is actually the manifestation of an expert’s disciplinary way of thinking about problems (Redish and Kuo, 2014). Often, this means that biology faculty are, in general, poorly prepared to teach mathematical concepts beyond the ones familiar to them, and mathematics faculty are ill-equipped to teach their subject content in a biological context (Blumberg et al., 2005; Usher et al., 2010; Feser et al., 2013). This lack of pedagogical content knowledge - the understanding of both content and instructional methods that allows faculty to effectively teach students (Shulman, 1986; NASEM, 2015) - is a major barrier to incorporating more quantitative skills in their courses.
As mastery of quantitative skills becomes more critical to success in biosciences, all students are impacted. Unfortunately, for students at community colleges (CCs), quantitative skills can create an insurmountable barrier. The impact on CC students is enormous and cannot be overlooked, considering the vast numbers and demographics of students at CCs. There are over 1000 CCs across the US enrolling over 12.2 million students - about 41% of all undergraduates in the US (AACC, 2017). A large portion of STEM students from underrepresented groups start college level education at CCs: 49% of Black students and over 50% of Hispanic students first enroll in community colleges (Shapiro et al., 2017). The number of science and engineering associate degrees awarded by CCs doubled between 2000 and 2012, to around 85,000 (AACC, 2015). A report from NSF (2016) noted that 47% of all recent science and engineering graduates, and 12.5% of doctoral degree recipients, attended CC at some point in their education underscoring the importance of addressing this issue in CCs.
At the CC level, 59% of students starting at a CC enrolled in at least one remedial math class, compared to 33% at four-year colleges (Chen & Simone, 2016). Only about one quarter of students who are required to take remedial courses go on to earn a degree or a certificate within 8.5 years (Attewell et al., 2006) due to a variety of factors. Currently, the most common method for identifying and addressing students’ remedial needs is through a placement test. Based on their performance in the placement test, students may be required to pass up to three pre-college-level math courses, none of which count toward their degree. There is compelling evidence to highlight that placement exams are not just inaccurate, but can be detrimental to students’ persistence and success in postsecondary studies (Scott-Clayton & Stacey, 2015). For example, students may only lack a subset of required skills to complete the test but are expected to take entire course to meet the remediation requirements. Another important consideration for these students is the drain on resources, namely time and money. Taking remedial classes delays students from starting STEM sequences. Furthermore, 58% of CC students received financial aid in 2011 (AACC, 2017). For these students, less financial aid is available to be applied toward college-level credits because federal financial aid is limited to covering a set amount of credits to ensure continued progress toward a degree. Therefore, students in remedial courses are investing time and money in earning credits that do not count toward their degree, while moving them closer to their financial aid cap. Thus, students who avoid science courses due to the additional expense for mathematics requirements at the introductory level are lost from the “pipeline” of diverse STEM practitioners needed to retain the US leadership in science and technology (PCAST, 2012; National Academies, 2010).
It is important to recognize that all students taking college-level biology classes for the first time are challenged to apply their math skills at various levels of competency. Despite the variation in their overall mathematical competency levels, each student would, thus, undoubtedly benefit from opportunities to refresh or deepen their quantitative skills. Routing students out of science due to a lack of proficiency in mathematical skills at the start of their higher education experience is a waste of human capital. This translates to supporting biology faculty by providing additional teaching resources and professional development opportunities, to incorporate more quantitative biology in the curriculum (NRC, 2003; Fawcett & Higginson, 2012).
Faculty must find ways to integrate quantitative skills into their course structures or they risk simply reinforcing the perception that math skills are distinct from biology skills, and therefore not particularly critical to success in the course and the discipline. CC faculty, in particular, face some of the greatest challenges in incorporating quantitative skills, yet these faculty are in a position to have an immediate impact on the makeup of the future STEM workforce. CC faculty work with students from diverse backgrounds, with varied preparation and educational goals, and who are often new to the higher education experience. CC faculty themselves bring a mix of backgrounds and experience to the classroom. Of all the CC faculty, about 41% hold a PhD degree and 37% hold Masters degrees (NCES b, 2008). CC faculty are from both traditional academic research backgrounds and industry, often teaching part time while working in their field. Although, there are high numbers of contingent/part-time faculty at CCs, these faculty often bring practical experience to the classroom and many have long term teaching relationships with their institutions. Full time CC faculty have substantially more teaching experience than most four-year faculty (NCES a, 2008); however, they are further removed from advances in the field, and specifically from learning and practicing new quantitative biology methods.
This network is designed to specifically address the needs of a diverse community college biology faculty, including access to high-quality quantitative biology educational materials appropriate for two year courses, and professional development opportunities to improve their pedagogical content knowledge.