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For the first time, the story of how and why we have plumbed the mysteries of reading, and why it matters today. Reading is perhaps the essential practice of modern civilization. For centuries, it has been seen as key to both personal fulfillment and social progress, and millions today depend on it to participate fully in our society. Yet, at its heart, reading is a surprisingly elusive practice. This book tells for the first time the story of how American scientists and others have sought to understand reading, and, by understanding it, to improve how people do it. Starting around 1900, researchers—convinced of the urgent need to comprehend a practice central to industrial democracy—began to devise instruments and experiments to investigate what happened to people when they read. They traced how a good reader’s eyes moved across a page of printed characters, and they asked how their mind apprehended meanings as they did so. In schools across the country, millions of Americans learned to read through the application of this science of reading. At the same time, workers fanned out across the land to extend the science of reading into the social realm, mapping the very geography of information for the first time. Their pioneering efforts revealed that the nation’s most pressing problems were rooted in drastic informational inequities, between North and South, city and country, and white and Black—and they suggested ways to tackle those problems. Today, much of how we experience our information society reflects the influence of these enterprises. This book explains both how the science of reading shaped our age and why, with so-called reading wars still plaguing schools across the nation, it remains bitterly contested.

Provides an overview of state-of-the-art research on the science of reading, revised and updated throughout The Science of Reading presents the most recent advances in the study of reading and related skills. Bringing together contributions from a multidisciplinary team of experts, this comprehensive volume reviews theoretical approaches, stage models of reading, cross-linguistic studies of reading, reading instruction, the neurobiology of reading, and more. Divided into six parts, the book explores word recognition processes in skilled reading, learning to read and spell, reading comprehension and its development, reading and writing in different languages, developmental and acquired reading disorders, and the social, biological, and environmental factors of literacy. The second edition of The Science of Reading is extensively revised to reflect contemporary theoretical insights and methodological advances. Two entirely new chapters on co-occurrence and complexity are accompanied by reviews of recent findings and discussion of future trends and research directions. Updated chapters cover the development of reading and language in preschools, the social correlates of reading, experimental research on sentence processing, learning to read in alphabetic orthographies, comorbidities that occur frequently with dyslexia, and other central topics. Demonstrates how different knowledge sources underpin reading processes using a wide range of methodologies Presents critical appraisals of theoretical and computational models of word recognition and evidence-based research on reading intervention Reviews evidence on skilled visual word recognition, the role of phonology, methods for identifying dyslexia, and the molecular genetics of reading and language Highlights the importance of language as a foundation for literacy and as a risk factor for developmental dyslexia and other reading disorders Discusses learning to read in different types of writing systems, with a language impairment, and in variations of the home literacy environment Describes the role of contemporary analytical tools such as dominance analysis and quantile regression in modelling the development of reading and comprehension Part of the acclaimed Wiley Blackwell Handbooks of Developmental Psychology series, the second edition of The Science of Reading: A Handbook remains an invaluable resource for advanced students, researchers, and specialist educators looking for an up-to-date overview of the field.

The PISA 2003 Assessment Framework presents the conceptual underpinning of the PISA 2003 assessments. Within each assessment area, the volume defines the content that students need to acquire, the processes that need to be performed and the contexts in which knowledge and skills are applied.

High-interest, nonfiction articles help students learn about science and social studies topics while developing skills in reading comprehension. Each story is followed by questions that cover main idea, details, vocabulary, and critical reasoning. The format is similar to that of standardized tests, so as students progress through the book s units, they are preparing for success in testing.

Why is metacognition gaining recognition, both in education generally and in science learning in particular? What does metacognition contribute to the theory and practice of science learning? Metacognition in Science Education discusses emerging topics at the intersection of metacognition with the teaching and learning of science concepts, and with higher order thinking more generally. The book provides readers with a background on metacognition and analyses the latest developments in the field. It also gives an account of best-practice methodology. Expanding on the theoretical underpinnings of metacognition, and written by world leaders in metacognitive research, the chapters present cutting-edge studies on how various forms of metacognitive instruction enhance understanding and thinking in science classrooms. The editors strive for conceptual coherency in the various definitions of metacognition that appear in the book, and show that the study of metacognition is not an end in itself. Rather, it is integral to other important constructs, such as self-regulation, literacy, the teaching of thinking strategies, motivation, meta-strategies, conceptual understanding, reflection, and critical thinking. The book testifies to a growing recognition of the potential value of metacognition to science learning. It will motivate science educators in different educational contexts to incorporate this topic into their ongoing research and practice.

Improve student outcomes in reading and literacy with the latest edition of this bestselling text The newly revised Third Edition of Reading for Understanding: How Reading Apprenticeship Improves Disciplinary Learning in Secondary and College Classrooms is the latest iteration of the best-selling, landmark book in the field of adolescent literacy. The book contains strategies for boosting the reading independence of middle, secondary, and college students. Research conducted by NSF, IES, and OIIhas validated the model taught in Reading for Understanding, demonstrating its effectiveness in raising students’ reading achievement levels. The authors teach a clear and concise instructional framework for students at all learning levels, from those with special learning needs to those taking honors and Advanced Placement courses. The book also includes: A direct correlation to disciplinary literacy, making the book an even more valuable resource in a wide range of classrooms Explanation of the social and personal dimensions for building a foundation for engaged learning Discussions of the value of setting aside dedicated class time for independent, silent reading With collaboration tips that go beyond the classroom and advice on building a cognitive “reading toolbox,” Reading for Understanding is an indispensable resource for teachers at the Grade 6 and up, literacy coaches, reading teachers, community college instructors, and other school leaders.

New essays on Kant's complex work, considering its place in his oeuvre and in the history of science.

This book establishes a new theoretical and practical framework for multimodal disciplinary literacy (MDL) fused with the subject-specific science pedagogies of senior high school biology, chemistry and physics. It builds a compatible alignment of multiple representation and representation construction approaches to science pedagogy with the social semiotic, systemic functional linguistic-based approaches to explicit teaching of disciplinary literacy. The early part of the book explicates the transdisciplinary negotiated theoretical underpinning of the MDL framework, followed by the research-informed repertoire of learning experiences that are then articulated into a comprehensive framework of options for the planning of classroom work. Practical adoption and adaptation of the framework in biology, chemistry and physics classrooms are detailed in separate chapters. The latter chapters indicate the impact of the collaborative research on teachers' professional learning and students’ multimodal disciplinary literacy engagement, concluding with proposals for accommodating emerging developments in MDL in an ever-changing digital communication world. The MDL framework is designed to enable teachers to develop all students' disciplinary literacy competencies. This book will be of interest to researchers, teacher educators and postgraduate students in the field of science education. It will also have appeal to those in literacy education and social semiotics. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Statistical models attempt to describe and quantify relationships between variables. In the models presented in this chapter, there is a response variable (sometimes called dependent variable) and at least one predictor variable (sometimes called independent or explanatory variable). When investigating a possible cause-and-effect type of relationship, the response variable is the putative effect and the predictors are the hypothesized causes. Typically, there is a main predictor variable of interest; other predictors in the model are called covariates. Unknown covariates or other independent variables not controlled in an experiment or analysis can affect the dependent or outcome variable and mislead the conclusions made from the inquiry (Bock, Velleman, & De Veaux, 2009). A p value (p) measures the statistical significance of the observed relationship; given the model, p is the probability that a relationship is seen by mere chance. The smaller the p value, the more confident we can be that the pattern seen in the data 2 is not random. In the type of models examined here, the R measures the prop- tion of the variation in the response variable that is explained by the predictors 2 specified in the model; if R is close to 1, then almost all the variation in the response variable has been explained. This measure is also known as the multiple correlation coefficient. Statistical studies can be grouped into two types: experimental and observational.