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Best Practices for State Assessment Systems, Part I: Summary of a Workshop
criticisms of existing national, state, and local science standards—that they include too much material, do not establish clear priorities among the material included, and provide insufficient interpretation of how the ideas included should be applied. Efforts to reform science education have been driven by standards—and have yielded improvements in achievement—but existing standards do not generally provide a guide for the development of coherent curricula. They do not support students in developing an integrated understanding of key scientific ideas, she said, which has been identified as a key reason that U.S. students do not perform as well as many of their international peers (Schmidt, Wang, and McKnight, 2005). Stevens and her colleagues have developed a model for science standards that are based on current understanding of science learning in order to address some of these weaknesses. She described the model as well as a proposed process for developing such standards and a process for using such standards to develop assessments (Krajcik, Stevens, and Shin, 2009).
Stevens and her colleagues began with the recommendations in a National Research Council (2005) report on designing science assessment systems: standards need to describe performance expectations and proficiency levels in the context of a clear conceptual framework, and be built on sound models of student learning. They should be clear, detailed, and complete; reasonable in scope; and both rigorous and scientifically accurate. She briefly summarized the findings from research on learning in science that are particularly relevant to the development of standards.
Integrated understanding of science is built on a relatively small number of foundational ideas that are central across the scientific disciplines—such as the principle that the natural world is composed of a number of interrelated systems—referred to as “big ideas” (see also National Research Council, 1996, 2005; Stevens, Sutherland, and Krajcik, 2009). These are the sorts of ideas that allow both scientists and students to explain many sorts of observations and to identify connections among facts, concepts, models, and principles (National Research Council, 2005; Smith et al., 2006).
Understanding of the big ideas helps learners develop more detailed conceptual frameworks that, in turn, make it possible to undertake scientific tasks, such as solving problems, making predictions, observing patterns, and organizing and structuring new information. Learning complex ideas takes time and often happens as students work on tasks that force them to synthesize new observations with what they already knew. Students draw on a foundation of existing understanding and experiences as they gradually assemble bodies of factual knowledge and organize it according to their growing conceptual understanding.
The most important implication of these findings for standards is that they must be elaborated so that educators can connect them with instruction, instructional materials, and assessments, Stevens explained. That is, not only