School, Family, and Community Partnerships


Book Description

Strengthen programs of family and community engagement to promote equity and increase student success! When schools, families, and communities collaborate and share responsibility for students′ education, more students succeed in school. Based on 30 years of research and fieldwork, the fourth edition of the bestseller School, Family, and Community Partnerships: Your Handbook for Action, presents tools and guidelines to help develop more effective and more equitable programs of family and community engagement. Written by a team of well-known experts, it provides a theory and framework of six types of involvement for action; up-to-date research on school, family, and community collaboration; and new materials for professional development and on-going technical assistance. Readers also will find: Examples of best practices on the six types of involvement from preschools, and elementary, middle, and high schools Checklists, templates, and evaluations to plan goal-linked partnership programs and assess progress CD-ROM with slides and notes for two presentations: A new awareness session to orient colleagues on the major components of a research-based partnership program, and a full One-Day Team Training Workshop to prepare school teams to develop their partnership programs. As a foundational text, this handbook demonstrates a proven approach to implement and sustain inclusive, goal-linked programs of partnership. It shows how a good partnership program is an essential component of good school organization and school improvement for student success. This book will help every district and all schools strengthen and continually improve their programs of family and community engagement.




All of Statistics


Book Description

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.




Assessment in Early Childhood Education


Book Description

For Assessment courses in Early Childhood Education. One of the most accessible and practical textbooks available on assessing young children from infancy through age 8. It provides the full range of types of assessment and how, when, and why to use them. An excellent introduction to assessing young children, Assessment in Early Childhood Education continues with the inclusion of all types of assessments that can be used with infants and young children. Key changes and updates to this edition include: updated and streamlined figures, examples, and models of assessment that aid pre-service teachers to learn how to apply the principles of quality assessments; new activities at the end of the chapters provide opportunities for students to apply their own performance activities to demonstrate understanding of chapter contents; the effects of No Child Left Behind have been updated; newly revised information on children from diverse cultures and languages and children with disabilities has been added; and information on new and current trends toward accountability are discussed, as well as the impact of high-stakes testing.




Testing in American Schools


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Instructor


Book Description







The Structuring of Organizations


Book Description

Synthesizes the empirical literature on organizationalstructuring to answer the question of how organizations structure themselves --how they resolve needed coordination and division of labor. Organizationalstructuring is defined as the sum total of the ways in which an organizationdivides and coordinates its labor into distinct tasks. Further analysis of theresearch literature is neededin order to builda conceptualframework that will fill in the significant gap left by not connecting adescription of structure to its context: how an organization actuallyfunctions. The results of the synthesis are five basic configurations (the SimpleStructure, the Machine Bureaucracy, the Professional Bureaucracy, theDivisionalized Form, and the Adhocracy) that serve as the fundamental elementsof structure in an organization. Five basic parts of the contemporaryorganization (the operating core, the strategic apex, the middle line, thetechnostructure, and the support staff), and five theories of how it functions(i.e., as a system characterized by formal authority, regulated flows, informalcommunication, work constellations, and ad hoc decision processes) aretheorized. Organizations function in complex and varying ways, due to differing flows -including flows of authority, work material, information, and decisionprocesses. These flows depend on the age, size, and environment of theorganization; additionally, technology plays a key role because of itsimportance in structuring the operating core. Finally, design parameters aredescribed - based on the above five basic parts and five theories - that areused as a means of coordination and division of labor in designingorganizational structures, in order to establish stable patterns of behavior.(CJC).




The Bilingual Advantage


Book Description

Using novel methodological approaches and new data, The Bilingual Advantage draws together researchers from education, economics, sociology, anthropology and linguistics to examine the economic and employment benefits of bilingualism in the US labor market, countering past research that shows no such benefits exist.




Linear Models in Statistics


Book Description

The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.