2004 Denver Annual Meeting (November 7–10, 2004)

Paper No. 13
Presentation Time: 8:00 AM-12:00 PM


ROGERS, Amanda, Perkiomen School, PO Box 130, Pennsburg, PA 18073, SUSSMAN, Aviva, Los Alamos National Lab, PO Box 1663, Mail Stop D462, Los Alamos, NM 87545 and LIBARKIN, Julie, Department of Geological Sciences, Ohio Univ, Athens, OH 45701, arogers@perkiomen.org

Scientific literacy is an essential skill in today’s science and technology driven world. In 1996, the National Science Education Standards attempted to address the growing concern surrounding the poor quality of science education in America by providing criteria, standards, and goals which all schools are expected to follow and achieve in their science curricula. However, independently written children’s science story-books (which are often used as in-class supplementary materials and by parents and guardians in the home) are not addressed in the NSES publication. Thus, this investigation compliments the NSES by assessing and judging the quality of children’s science story-books by compiling and analyzing data on the terminology, illustrations, and demographics of thirty randomly selected children’s earth science story-books (for 4-8 year olds) published between 1979 and 2003. Our data suggests that the scientific quality of children’s science storybooks has generally increased through time. For example, there has been a dramatic increase in used and defined terminology, especially following publication of the NSES, implying that more information is being transmitted to children in recent books. On the otherhand, our data show that there is no increased amount of diversity in the time interval studied: white males are the most represented group. Our data and analysis may be used by teachers, parents, education researchers, authors and publishers in order to choose the best possible supplementary storybook for the earth science classes and to fill in gaps. Most importantly, the new method for quantitative data analysis of children’s science storybooks, which is introduced in this study, may be used in other fields. The importance of this method is that it easily links quantitative data to qualitative conclusions.