SCIENCE EDUCATION AND QUANTITATIVE LITERACY

Jeff Witmer
Oberlin College

Newsletter for the Section on Statistical Education
Volume 3, Number 2 (Summer 1997)


The Quantitative Literacy program has successfully affected the teaching of many mathematics teachers around the country. Now ASA is working with science teachers to enhance science education through the use of statistical ideas. Following the pattern of the QL program, the Science Education and Quantitative Literacy (SEAQL) project involves high school science teachers, middle school science teachers, and statisticians as leaders of workshops aimed at enhancing the preparation of high school and middle school science teachers.

Science students routinely collect large amounts of data that are used to answer specific questions. In a typical science class, each student completes a procedure and determines some sort of answer, for example, the density of a substance. Rarely are class data compared to anything other than an accepted value, as found in a reference book. SEAQL seeks to foster genuine exploration of data in science laboratory activities that promote a view of science as exploration and modeling, rather than only as confirmation of facts that are already known. We advocate using boxplots, median-fit lines, and related tools in the analysis of science data in order to place emphasis on discovery.

Teachers using SEAQL ideas might have each student add his or her data to a class stem-leaf diagram, which is then turned into a boxplot. The class can then discuss the data, noting the median and deviations from the median, outliers, skewness, and other features. This helps the students develop an appreciation of inherent variation, measurement bias, and accuracy. Indeed, experience suggests that students are more inclined to try to be accurate in their measurements when they know that their data will end up as part of a class boxplot -- no one wants to be an outlier!

In SEAQL workshops teachers are taught data analysis techniques using the Exploring Data QL book and are given experience using these techniques with data that are generated during the workshop. During the workshops, which last between two and four weeks, we conduct science labs in biology, physics, chemistry, earth science, and general science that are, for the most part, familiar to the teachers. We then use QL ideas in analyzing the data.

Other aspects of the workshops include instruction in the use of graphing calculators and calculator-based-lab equipment, such as a temperature probe for gathering data during a heat of reaction experiment, discussion of non- standard labs that teachers have used with success, group projects in which participants gather and analyze data of their own choosing, time for teachers to prepare lesson plans as they consider how they will use SEAQL in their science classes, and brief consideration of statistical aspects of experimental design.

In 1994 the SEAQL project received an NSF grant that runs through 1997. The first SEAQL workshop was held in 1995 at Johns Hopkins University. Two workshops were held during the summer of 1996 -- one at John Carroll University in Cleveland and one at San Jose State University in San Jose. In 1997 we are conducting workshops at Wesleyan University in Middletown, CT, and again at John Carroll University in Cleveland. We conduct follow-up sessions with the workshop participants during the academic year. Participants have reported considerable success in using SEAQL ideas in their classes and are very enthusiastic.

For more information, please contact Cathy Crocker at the ASA office
(703-684-1221, ext. 146)
cathyc@amstat.org


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