This study investigates the efficacy of an integrated science and literacy approach at the upper-elementary level. Teachers in 94 fourth grade classrooms in one Southern state participated. Half of the teachers taught the treatment unit, an integrated science-literacy unit on light and energy designed using a curriculum model that engages students in reading text, writing notes and reports, conducting firsthand investigations, and frequent discussion of key concepts and processes to acquire inquiry skills and knowledge about science concepts, while the other half of the teachers taught a content-comparable science-only unit on light and energy (using materials provided by their districts) and provided their regular literacy instruction. Students in the treatment group made significantly greater gains on measures of science understanding, science vocabulary, and science writing. Students in both groups made comparable gains in science reading comprehension. ß 2012 Wiley Periodicals, Inc. J Res Sci Teach 49: 2012 It is widely acknowledged that robust science learning occurs most effectively through firsthand experience combined with ample opportunities for reflection and rich talk

The National Educational Longitudinal Study (NELS) database was used to examine student and school factors associated with students dropping out in different grades. Specifically, a hierarchical logistic model was used to address three issues. First, are early (middle school) and late (high school) dropouts equally affected by traditionally defined risk factors? Second, do school-level factors, after controlling for differences in enrollment, account for between-school differences in school dropout rates, and can these school factors mediate individual student risk factors? Third, what impact does early predicted risk have on the likelihood of dropping out late? Results showed that the mix of student risk factors changes between early and late dropouts, while family characteristics are more important for late dropouts. Consistent with previous research, the results also indicated that being held back is the single strongest predictor of dropping out and that its effect is consistent for both early and late dropouts. School factors can account for approximately two thirds of the differences in mean school dropout rates, but they do a poor job of mediating specific student risk factors. The results indicate as well that early predicted risk, at both the student level and the school level, significantly affects the odds of a student dropping out late.

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We examine the impact of teacher professional development on knowledge growth and subsequent knowledge retention. Specifically we use English Language Arts teacher content and pedagogy assessments to determine whether the California Professional Development Institutes significantly improve teacher content knowledge and whether teachers retain that knowledge six months after the institutes are completed. The results indicate that teachers vary significantly in pre-institute knowledge on the four assessed domains, demonstrate significant knowledge growth, but only retain about one half of what was gained during the institute. Further, pre-existing knowledge gaps are not systematically reduced and teacher perceptions of institute quality are not related to knowledge growth and knowledge retention. Current No Child Left Behind (NCLB) legislation requires that all students are taught by highly-qualified teachers (NCLB, 2001). The logic of NCLB and related state and district policies is straightforward; to make adequate progress towards proficiency in the core subjects of English language arts and mathematics, students need to receive instruction from teachers who are well-prepared to teach these subjects. Teacher professional development is widely viewed as the most promising intervention for improving teacher quality in U.S. public schools. Nearly every state and district provides inducements for teachers to participate in professional development and these are increasingly supplemented by federal programs such as Reading First. Districts often add requirements on top of these, either in the form of mandatory programs for all instructional staff, or by requiring time investment beyond state requirements. The

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A key question facing teacher evaluation systems is how to combine multiple measures of complex constructs into composite indicators of performance. We use data from the Measures of Effective Teaching (MET) study to investigate the measurement properties of composite indicators obtained under various conjunctive, disjunctive (or complementary), and weighted (or compensatory) models. We find that accuracy varies across models and cut-scores and that models with similar accuracy may yield different teacher classifications. Accuracy and consistency are greatest if composites are constructed to maximize reliability and lowest if they seek to optimally predict student test scores. We discuss the implications of the results for the validity of inferences about the performance of individual teachers, and more generally for the design of teacher evaluation systems.

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