Content area
This dissertation examined the vertical and horizontal content analysis of statistical content within current 8th-grade mathematics instructional materials to determine the extent to which students are provided with opportunity to learn high cognitive instances and the usage of the four phases of statistical problem-solving across two commercial publishers, one open educational resource, and one curriculum software supplement. All previous analyses of statistics education content textbooks have only examined textbooks from commercial publishers or those published by national governments. The horizontal content textbook analysis investigated the textbook's background information and overall structure. The vertical content textbook analysis examined the cognitive level of demand and the statistical problem-solving process phases for 8th-grade statistical instances. Two coders and I implemented Schreier’s eight Steps in Qualitative Content Analysis. The percentage of instances coded for analyzing data and interpreting data ranged from 87.6% for Bootstrap to 98.3% for Tuva. The percentage of instances coded for formulating a question and collecting data ranged from 1.3% for HMH (Into Math) to 12.5% for Bootstrap. Fewer statistical instances provided students the Opportunity to Learn from higher-level cognitively demanding tasks (e.g., procedures with connections and doing mathematics, 17.0% for Bootstrap, and 39.2% for Savvas (enVision Mathematics). The two commercial publishers provided more cognitively demanding instances than other K-8 statistics textbook content analysis studies. Recommendations for future research include standard domain breakdown for each cognitive level of demand, incorporating vertical and horizontal analysis with future content textbook analysis, and integrating statistical software into instructional materials.