which it is presented, and whether an assessment task or situation is functioning as a test of near, far, or zero transfer.

Knowledge is often embedded in particular social and cultural contexts, including the context of the classroom, and it encompasses understandings about the meaning of specific practices such as question asking and answering. Assessments need to examine how well students engage in communicative practices appropriate to a domain of knowledge and skill, what they understand about those practices, and how well they use the tools appropriate to that domain.

By considering context and development as co-emerging, school-based assessment can be directed toward the intersection of classroom contexts and individual cognition. Equitable assessment, then, relies on the creation of opportunities for growth and development. Without systematic attention to opportunity, the results of assessment simply recapitulate existing patterns of distribution of resources, both financial and social. Questions must therefore be raised about the validity of inferences that can be drawn from assessments of individual student achievement, using criteria for reasoning and argumentation defined in mathematics and science standards documents. It is uncertain what can be inferred in the absence of clear documentation of students’ opportunities to participate in forms of practice valued by disciplines such as mathematics and science—an issue that is addressed later in this volume.

INTEGRATION OF MODELS OF COGNITION AND LEARNING WITH INSTRUCTION AND ASSESSMENT

By building on findings about cognition, learning, and the development of expertise, researchers have produced models to describe the thinking processes, reasoning strategies, and conceptual understandings of students at various stages of competency. This work has tended to focus on the nature of knowledge and performance in specific domains of mathematics, science, or history. These models can be used to diagnose student understanding, determine next steps in instruction, and design assessments (Baker, 1997).

Detailed models of cognition and learning in specific curricular areas can be used to formulate a set of criteria that are valuable for evaluating the progress of any individual or group, as well as for informing teaching and learning. In other words, a well-developed and empirically validated model of thinking and learning in an academic domain can be used to design and select assessment tasks that support the analysis of various kinds of student performance. Such a model can also serve as the basis for rubrics for evaluating and scoring pupils’ work, with discriminating features of expertise



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