The science lab: On opportunity for real statistical analyses in the schools


Book: 
American Statistical Association 1993 Proceedings of the Section on Statistical Education
Authors: 
Witmer, J. A.
Category: 
Pages: 
39-41
Year: 
1993
Publisher: 
American Statistical Association
Place: 
Alexandria, VA
Abstract: 

The Quantitative Literacy (QL) project has affected how statistics is viewed and taught by high school mathematics teachers. Each summer since 1987 the ASA Center for Statistics Education has organized QL workshops at various places around the country. This movement has been in concert with the National Council of Teachers of Mathematics movement to revamp mathematics instruction with their Curriculum and Development Standards. Quantitative Literacy is now a major part of the thinking of national and local leaders in mathematics education. Unfortunately, few science teachers have been affected by the QL project. While mathematics teachers introduce boxplots in their algebra classes, the science teachers in the same building have each student complete a laboratory exercise and turn in a report, without ever considering how the results of the various students differ. The middle school or high school science laboratory is an excellent place in which to use statistical ideas, but rarely does this happen. In 1990 ASA organized a planning meeting that led to the formation of the SEAQL (Science Education And Quantitative Literacy) task force. This group of statisticians and science teachers is promoting the use of statistics in school science courses by focusing on common laboratory experiments that involve data collection. The task force will host a leadership conference in November for science curriculum supervisors. At the conference the task force will demonstrate some SEAQL laboratory activities and convey the philosophy of using data analysis as a science teaching tool.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education