Thomas M. Smith – författare

In Systems for Instructional Improvement, Paul Cobb and his colleagues draw on their extensive research to propose a series of specific, empirically grounded recommendations that together constitute a theory of action for advancing instruction at scale. The authors outline the elements of a coherent instructional system; describe productive practices for school leaders in supporting teachers’ growth; and discuss the role of district leaders in developing school-level capacity for instructional improvement.Based on the findings of an eight-year research-practice partnership with four large urban districts investigating their efforts to enhance middle school math instruction, the authors seek to bridge the gap between the literature on improving teaching and learning and the literature on policy and leadership. They look at the entire education system and make recommendations on improvement efforts with a focus on student learning and teachers’ instructional vision. In particular, the authors offer insights on the interplay among various supports for teacher learning, including pullout professional development, coaching, collaborative inquiry, the most instructionally productive uses of principals’ time, and the tensions that tend to emerge at the district level. They provide a guide for district-level leaders in organizing their work to support significant teacher learning.Systems for Instructional Improvement provides an invaluable resource for school and district leaders, while outlining a clearly focused agenda for future research.

Spatial and temporal averaging of observational data is widely used in many problems of meteorology, hydrology and related sciences. Several averaging methods have been proposed by various scientists and are used on a regular basis to obtain data averaged in space orfand in time, to yield data which are less influenced by random factors than initial point data are. The significance of averaging meteorological fields has substantially increased nowadays in connection with the problem of global climate change. However important as such change may be, it is very small as compared with the natural variability of atmospheric fields. An accurate averaging is absolutely necessary in order to discover a small climate change signal on the background of strong natural variability that acts as a random noise in this context. It is highly desirable not only to determine the averaged values themselves, but also to estimate the accuracy with which these values are known. To evaluate the accuracy of averaging is not a simple task mainly because the initial point values are not independent from each other, and interconnections between them substantially influence the averaging accuracy.

Elements of Ecology continues to explain ecological processes clearly and concisely, with a greater emphasis on the relevance of ecology to everyday life and the human impact on ecosystems. This dramatically revised edition discusses issues of human ecology throughout the text and provides a greater variety of opportunities for students to learn, practice, and develop quantitative and analytical skills. Current research examples and other content updates are supported by more than 200 redesigned, full-color illustrations, graphs, and tables.

 

The full text downloaded to your computer

With eBooks you can:

search for key concepts, words and phrases make highlights and notes as you study share your notes with friends

eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps.

Upon purchase, you''ll gain instant access to this eBook.

Time limit

The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

In Systems for Instructional Improvement, Paul Cobb and his colleagues draw on their extensive research to propose a series of specific, empirically grounded recommendations that together constitute a theory of action for advancing instruction at scale. The authors outline the elements of a coherent instructional system; describe productive practices for school leaders in supporting teachers’ growth; and discuss the role of district leaders in developing school-level capacity for instructional improvement. Based on the findings of an eight-year research-practice partnership with four large urban districts investigating their efforts to enhance middle school math instruction, the authors seek to bridge the gap between the literature on improving teaching and learning and the literature on policy and leadership. They look at the entire education system and make recommendations on improvement efforts with a focus on student learning and teachers’ instructional vision. In particular, the authors offer insights on the interplay among various supports for teacher learning, including pullout professional development, coaching, collaborative inquiry, the most instructionally productive uses of principals’ time, and the tensions that tend to emerge at the district level. They provide a guide for district-level leaders in organizing their work to support significant teacher learning. Systems for Instructional Improvement provides an invaluable resource for school and district leaders, while outlining a clearly focused agenda for future research.

In Systems for Instructional Improvement, Paul Cobb and his colleagues draw on their extensive research to propose a series of specific, empirically grounded recommendations that together constitute a theory of action for advancing instruction at scale. The authors outline the elements of a coherent instructional system; describe productive practices for school leaders in supporting teachers’ growth; and discuss the role of district leaders in developing school-level capacity for instructional improvement. Based on the findings of an eight-year research-practice partnership with four large urban districts investigating their efforts to enhance middle school math instruction, the authors seek to bridge the gap between the literature on improving teaching and learning and the literature on policy and leadership. They look at the entire education system and make recommendations on improvement efforts with a focus on student learning and teachers’ instructional vision. In particular, the authors offer insights on the interplay among various supports for teacher learning, including pullout professional development, coaching, collaborative inquiry, the most instructionally productive uses of principals’ time, and the tensions that tend to emerge at the district level. They provide a guide for district-level leaders in organizing their work to support significant teacher learning. Systems for Instructional Improvement provides an invaluable resource for school and district leaders, while outlining a clearly focused agenda for future research.

Spatial and temporal averaging of observational data is widely used in many problems of meteorology, hydrology and related sciences. Several averaging methods have been proposed by various scientists and are used on a regular basis to obtain data averaged in space orfand in time, to yield data which are less influenced by random factors than initial point data are. The significance of averaging meteorological fields has substantially increased nowadays in connection with the problem of global climate change. However important as such change may be, it is very small as compared with the natural variability of atmospheric fields. An accurate averaging is absolutely necessary in order to discover a small climate change signal on the background of strong natural variability that acts as a random noise in this context. It is highly desirable not only to determine the averaged values themselves, but also to estimate the accuracy with which these values are known. To evaluate the accuracy of averaging is not a simple task mainly because the initial point values are not independent from each other, and interconnections between them substantially influence the averaging accuracy.