Understanding and Overcoming Barriers to Using Mathematics in Science
Mathematics is an essential element of modern science. In many areas of science, however, math modeling is not part of the instructional tradition. In STEM fields such as the life sciences (biology and pre-health care), efforts to modify instruction to include more math have met with only moderate success. Many life science students resist using math in science, despite their success in math classes. In this project we explore previously unarticulated differences between the way math is used in math and science classes and the reasons behind students' difficulties. Success in the project will provide a better understanding of what needs to be done to help a larger fraction of life science students learn to use math productively.
The project's primary goal is to identify students' barriers to using math in science through a mix of quantitative and qualitative research. We will weave an instructional thread on mathematical modeling: readings, quiz and clicker questions, homework and exam questions to build studentsﾒ mathematical modeling skills in a variety of contexts. We are developing survey instruments to assess students' abilities to imbed math in scientific contexts. Our mathematical modeling thread will be implemented in an Introductory Physics for Life Sciences (IPLS) course, and the effect on studentsﾒ ability to use mathematics in biology assessed using our instruments.
Drawing on many sources, we have completed drafts of two instruments: a Mathematics Epistemic Game Survey (MEGS) for testing students' facility with translating math into science, and a Mathematics Expectations Survey (MAX) to probe students' attitudes towards the use of math in science. Our pre-test results identify many places where students struggle and provide guidance for creating interviews and we have completed more than a dozen so far. We analyze these results using the theoretical framework of Resources/Knowledge in Pieces, and students' expectations about what knowledge is relevant for solving a problem (epistemological resources and epistemological framing) are critical. Insights from the analysis of early data are providing the identification of a number of explicit problems that need to be addressed.
Through our surveys and interview results, we are identifying specific student expectations that life science students bring to science courses that inhibit them from learning to use math effectively. We expect to identify specific tools � epistemic games � that the students need to learn to use. These, together with our 'Mathematics in Science' instructional thread, should provide useful guidance to other instructional development groups attempting to improve students' integration of math into their scientific toolbox. Our assessment instruments should also be of broad value in multiple courses in the STEM curriculum.
Both the understanding of student difficulties with using math in science and the tools we build to help them could have powerful implications for the teaching of all sciences and engineering. There has been much interest in the community and we have already begun to get invitations to speak about the project and to interact with other groups researching similar questions (e.g., QUBES at NIMBios and MathBench).
None so far. (The project is in its 4th month)
Language of physics, language of math: Disciplinary culture and dynamic epistemology, E. F. Redish and E. Kuo, Science & Education, (2015-03-14) 30 pages. doi:10.1007/s11191-015-9749-7