We contributed equally to this effort and thank Michele Gregoire-Gill for reading an earlier version of this chapter and providing invaluable feedback.

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Scientific literacy reflects "a broad and functional understanding of science for general education purposes" (DeBoer, 2000, p. 594). Herein, we present the ongoing development of the Scientific Literacy Assessment (SLA), a work-in-progress measure to assess middle school students' (ages 11-14) scientific literacy. The SLA includes a selected response measure of students' demonstrated scientific literacy (SLA-D) and a motivation and beliefs scale based on existing measures of self-efficacy, subjective task value, and personal epistemology for science (SLA-MB). Our theoretical conceptualization of scientific literacy guided the development of our measure. We provide details from three studies: Pilot Study 1 (n = 124) and Pilot Study 2 (n = 220) describe the development of the SLA-D by conducting iterative item analyses of the student responses, think-aloud interviews with six students, and external expert feedback on the items in the SLA-D. Study 3 describes the testing of our prototype measure (n = 264). We present a validity argument including reliability evidence that supports the use of the current version of the SLA to provide evaluation of middle school students' scientific literacy. Our resulting SLA includes the SLA-D in two versions, each with 26 items and the SLA-MB with 25 items across three scales: value of science, scientific literacy self-efficacy, and personal epistemology. C 2014 Wiley Periodicals, Inc. Sci Ed 98:549-580, 2014

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The authors examined knowledge, interest, and strategic processing profiles within special education for 4 educational communities. Participants included undergraduates not majoring in special education and undergraduates, graduate students, and faculty from special education. Cluster analysis tested whether participants would exhibit the knowledge, interest, and strategic processing profiles expected for individuals at various stages of expertise. The Model of Domain Learning (MDL) was the theoretical framework for data interpretation. Results provided strong support for the MDL. Specifically, 4 clusters emerged from the data. Clusters (i.e., Acclimation, Early Competence, Mid-Competence, and Proficiency) were statistically distinct with regard to the external criterion, domain-specific analogical reasoning, and in relation to clustering variables. Implications for developmental models of expertise and for educational practice are considered.