USING CONTENT ANALYSIS TO INVESTIGATE THE TREATMENT OF SPATIAL AND TEMPORAL SCALE IN K-8 SCIENCE STANDARDS AND TEXTBOOKS

Content analysis is a suite of methods that can be used to systematically code and analyze both text and images. Depending upon the study’s aims, researchers may be interested in extracting manifest (explicit) and/or latent (implied) content. Quantitative content analysis derives a coding scheme from existing theory rather than having it emerge from the data. Some coding categories in qualitative content analysis are generated from a theoretical framework, while others may emerge from the data itself. Methodological decisions such as the nature of the coding scheme, how codes are defined, and what constitutes a coding unit all impact conclusions that can be drawn from the use of content analysis. Analyzing images creates an additional set of issues for a study’s design.

The authors report on a study in progress that is using content analysis to investigate how ideas about spatial and temporal scale (a crosscutting concept in the Next Generation Science Standards) are infused into state science standards and textbooks for K-8 classrooms in California, Texas, and Florida, which combined educate approximately 30% of all school age children in the US. State science standards and textbooks are useful sources of data for GER because they are significant determiners of the topics taught and the time devoted to them in K-12 science classrooms in the US. Content analysis has been used to examine textbooks for a variety of reasons, such as the treatment of the NOS in high school science textbooks (Abd-El-Khalick, 2016) or the extent to which introductory undergraduate geology textbooks emphasize similar vocabulary words (Kortz & Caulkins, 2015). Science standards and textbook chapters dealing with astronomy, surface and tectonic processes, and weather and climate are examined to determine if and how spatial and temporal scalar concepts related to these topics are infused into curricular materials and performance expectations. The authors discuss methodological decision making around the coding scheme, defining codes, determination of coding units, challenges related to the analysis of images, and issues related to reliability and validity.