Introduction
International Mathematics and Science Study (TIMSS) and the Program for International Student Assessment (PISA)—resulting in a sample of 4,491 items overall. Our analysis produced a conceptual framework with two broad categories: items that required declarative knowledge about science and items that did not require declarative knowledge about science. That is, while a substantial majority (about 86 percent) of the items assessed students’ understanding of scientific concepts, generalizations, and principles, the remaining items only required students read and understand provided scientific information, analyze and interpret data, or utilize mathematics skills and procedures within the context of science without calling on any external scientific knowledge. Items that required knowledge of scientific concepts, generalizations, and principles fell into five distinct content categories: (1) physical science, (2) life science, (3) earth and space science, (4) engineering and technology, and (5) scientific investigation. While reading comprehension, data analysis, and mathematics were also sometimes called for in these items, we grouped all items that required declarative science knowledge together, regardless of the other skills involved. Among the content categories, earth and space science, physical science, and life science each encompassed a substantial portion of the items, while engineering and technology and scientific investigation items were relatively infrequent. To a greater extent than mathematics or ELA items, science items required students to know and recall specific content rather than determine what knowledge or procedures to apply to a given problem or reason through provided information. We divided the items that did not require declarative science knowledge into three categories: data analysis, calculation using formulas, and reading comprehension. While these items typically appeared within a scientific context, they did not require students have any specific scientific knowledge outside of information provided in the item itself. Among these items, data analysis (involving the interpretation or creation of data sets and displays) was the most frequently needed skill. Reading comprehension items, which asked students to understand and interpret text, illustrations, and models (not including data displays), were the second-most frequent, with items involving mathematics calculations or concepts being the least frequent. Given the relative homogeneity of science item formats and the fact that most require specific scientific knowledge, success on large-scale science assessments depends primarily on ensuring students know the most critical content at each grade level.
What You Will Find in This Book In the book’s six chapters, you will find discussions of the nature and impact of largescale assessments and actions you can take to mitigate the potential negative effects of those assessments on students. In particular, we focus on how teachers can make students aware of the idiosyncrasies of standardized test items by exposing them to similar items on classroom assessments. Thus, you can use test items to deepen students’ understanding of the content as well as prepare them to demonstrate that knowledge on large-scale tests. You will also find a detailed analysis of our findings for ELA, mathematics, and science.
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