This dissertation examines the patterns and types of mistakes students make on a large-scale mathematics assessment, and puts these patterns into perspective based on the textbook used and the specific content covered in a student's classroom. In order to investigate the nature of these patterns, I employ a method of analysis originally designed for modeling the social interactions/networks of actors attending different events. Once these patterns are defined, I assign content, process and skill codes to each item, following the methods of the Rule Space Method, and identify different "Knowledge States" for each position of items and students within a school. These Knowledge States are compared within schools using the same textbooks, and between schools using different texts. The analyses carried out in separate phases, addresses two main hypotheses. The first phase identifies the different Knowledge States for each school in 4 districts, each using a unique textbook and/or curriculum; all aligned to the State of Michigan's Grade-Level-Content-Expectations. Hypothesis I suggests that the positions of items and students in each school are meaningful, and not likely to occur by chance alone. In order to examine Hypothesis I, I examine the statistical significance of the KliqueFinder algorithm's results, and then provide an analysis of the distractors chosen by all students within this sample, and compare these to the results for each school and textbook combination. The second phase addresses Hypothesis II, which the Knowledge States are consistent across schools using the same textbooks, and different between schools using different texts. I provide descriptive analyses for each school related to the reported content coverage and textbook use, specifically the use of textbooks specifically designed to align with National and individual state standards. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]