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This book introduces theories and practices for using assessment data to enhance learning and instruction. Topics include reshaping the homework review process, iterative learning engineering, learning progressions, learning maps, score report designing, the use of psychosocial data, and the combination of adaptive testing and adaptive learning. In addition, studies proposing new methods and strategies, technical details about the collection and maintenance of process data, and examples illustrating proposed methods and software are included. Chapters 1, 4, 6, 8, and 9 discuss how to make valid interpretations of results and achieve more efficient instructions from various sources of data. Chapters 3 and 7 propose and evaluate new methods to promote students’ learning by using evidence-based iterative learning engineering and supporting the teachers’ use of assessment data, respectively. Chapter 2 provides technical details on the collection, storage, and security protection of process data. Chapter 5 introduces software for automating some aspects of developmental education and the use of predictive modeling. Chapter 10 describes the barriers to using psychosocial data for formative assessment purposes. Chapter 11 describes a conceptual framework for adaptive learning and testing and gives an example of a functional learning and assessment system. In summary, the book includes comprehensive perspectives of the recent development and challenges of using test data for formative assessment purposes. The chapters provide innovative theoretical frameworks, new perspectives on the use of data with technology, and how to build new methods based on existing theories. This book is a useful resource to researchers who are interested in using data and technology to inform decision making, facilitate instructional utility, and achieve better learning outcomes.
Thanks to initiatives like the Common Core and Race to the Top, accountability requirements continue to be a reality for educators. Yet many are still unsure of how to use data to make well-informed instructional decisions. The Data-Driven Classroom comes to the rescue with a systematic, universal process that shows teachers how to: examine student assessment results to identify a curricular or skill area to target for individual intervention or large-group instructional revision; develop, implement, and assess the effectiveness of the intervention or revision; and develop an action plan for future instructional cycles. Author Craig A. Mertler sheds light on how teachers can make sense of overwhelming standardized test reports while avoiding pitfalls like over-interpreting data. In these pages you will also find practical classroom examples and templates designed to guide teachers of all grade levels and subject areas through the comprehensive decision-making framework.
Based on rapid advances in what is known about how people learn and how to teach effectively, this important book examines the core concepts and central pedagogies that should be at the heart of any teacher education program. Stemming from the results of a commission sponsored by the National Academy of Education, Preparing Teachers for a Changing World recommends the creation of an informed teacher education curriculum with the common elements that represent state-of-the-art standards for the profession. Written for teacher educators in both traditional and alternative programs, university and school system leaders, teachers, staff development professionals, researchers, and educational policymakers, the book addresses the key foundational knowledge for teaching and discusses how to implement that knowledge within the classroom. Preparing Teachers for a Changing World recommends that, in addition to strong subject matter knowledge, all new teachers have a basic understanding of how people learn and develop, as well as how children acquire and use language, which is the currency of education. In addition, the book suggests that teaching professionals must be able to apply that knowledge in developing curriculum that attends to students' needs, the demands of the content, and the social purposes of education: in teaching specific subject matter to diverse students, in managing the classroom, assessing student performance, and using technology in the classroom.
Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.
The untold story of the root cause of America's education crisis--and the seemingly endless cycle of multigenerational poverty. It was only after years within the education reform movement that Natalie Wexler stumbled across a hidden explanation for our country's frustrating lack of progress when it comes to providing every child with a quality education. The problem wasn't one of the usual scapegoats: lazy teachers, shoddy facilities, lack of accountability. It was something no one was talking about: the elementary school curriculum's intense focus on decontextualized reading comprehension "skills" at the expense of actual knowledge. In the tradition of Dale Russakoff's The Prize and Dana Goldstein's The Teacher Wars, Wexler brings together history, research, and compelling characters to pull back the curtain on this fundamental flaw in our education system--one that fellow reformers, journalists, and policymakers have long overlooked, and of which the general public, including many parents, remains unaware. But The Knowledge Gap isn't just a story of what schools have gotten so wrong--it also follows innovative educators who are in the process of shedding their deeply ingrained habits, and describes the rewards that have come along: students who are not only excited to learn but are also acquiring the knowledge and vocabulary that will enable them to succeed. If we truly want to fix our education system and unlock the potential of our neediest children, we have no choice but to pay attention.
The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large-scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student’s learning and guide teacher’s instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.
This entry in the James H. Stronge Research-to-Practice Series focuses on specific strategies teachers can use to improve the quality of their instruction. Studies have shown teacher quality to be the top indicator of student achievement, with the effects of good teachers apparent even as students move on to successive grades. In this book, Grant, Hindman, and Stronge explore the relationship between teacher effectiveness and student learning. They provide a bridge between research-based theories and practical classroom applications. Templates, planning forms, and other reproducibles help teachers make a noticeable impact on student success using proven techniques and practices. Topics include tiered lessons, using assessment data, and much more.
In an age where the quality of teacher education programs has been called into question, it is more important than ever that teachers have a fundamental understanding of the principles of human learning, motivation, and development. Theory to Practice: Educational Psychology for Teachers and Teaching is a series for those who teach educational psychology in teacher education programs. At a time when educational psychology is at risk of becoming marginalized, it is imperative that we, as educators, “walk our talk” in serving as models of what effective instruction looks like. Each volume in the series draws upon the latest research to help instructors model fundamental principles of learning, motivation, and development to best prepare their students for the diverse, multidimensional, uncertain, and socially-embedded environments in which these future educators will teach. The inaugural volume, Teaching on Assessment, is centered on the role of assessment in teaching and learning. Each chapter translates current research on critical topics in assessment for educational psychology instructors and teacher educators to consider in their teaching of future teachers. Written for practitioners, the aim is to present contemporary issues and ideas that would help teachers engage in meaningful assessment practice. This volume is important not only because of the dwindling presence of assessment-related instructional content in teacher preparation programs, but also because the policy changes in the last two decades have transformed the meaning and use of assessment in K-12 classrooms. Praise for Teaching on Assessment "This thought-provoking book brings together perspectives from educational psychology and teacher education to examine how assessment can best support student motivation, engagement, and learning. In the volume, editors Nichols and Varier present a set of chapters written by leaders in the field to examine critical questions about how to best prepare teachers to make instructional decisions, understand assessment within the context of learning and motivation theory, and draw on assessment in ways which can meet the needs of diverse learners. Written in a highly accessible language and style, each chapter contains clear takeaway messages designed for educational psychologists, teacher educators, teachers, and pre-service teachers. This book is essential reading for anyone involved in teaching or developing our future teaching professionals." Lois R. Harris, Australian Catholic University "This impressive book provides a wealth of contemporary and engaging resources, ideas and perspectives that educational psychology instructors will find relevant for helping students understand the complexity of assessment decision-making as an essential component of instruction. Traditional assessment principles are integrated with contemporary educational psychology research that will enhance prospective teachers’ decision-making about classroom assessments that promote all students’ learning and motivation. It is unique in showing how to best leverage both formative and summative assessment to boost student engagement and achievement, enabling students to understand how to integrate practical classroom constraints and realities with current knowledge about self-regulation, intrinsic motivation, and other psychological constructs that assessment needs to consider. The chapters are written by established experts who are able to effectively balance presentation of research and theory with practical applications. Notably, the volume includes very important topics rarely emphasized in other assessment texts, including assessment literacy frameworks, diversity, equity, assessment strategies for students with special needs, and data-driven decision making. The book will be an excellent supplement for educational psychology classes or for assessment courses, introducing students to current thinking about how to effectively integrate assessment with instruction." James McMillan, Virginia Commonwealth University.
Education is a hot topic. From the stage of presidential debates to tonight's dinner table, it is an issue that most Americans are deeply concerned about. While there are many strategies for improving the educational process, we need a way to find out what works and what doesn't work as well. Educational assessment seeks to determine just how well students are learning and is an integral part of our quest for improved education. The nation is pinning greater expectations on educational assessment than ever before. We look to these assessment tools when documenting whether students and institutions are truly meeting education goals. But we must stop and ask a crucial question: What kind of assessment is most effective? At a time when traditional testing is subject to increasing criticism, research suggests that new, exciting approaches to assessment may be on the horizon. Advances in the sciences of how people learn and how to measure such learning offer the hope of developing new kinds of assessments-assessments that help students succeed in school by making as clear as possible the nature of their accomplishments and the progress of their learning. Knowing What Students Know essentially explains how expanding knowledge in the scientific fields of human learning and educational measurement can form the foundations of an improved approach to assessment. These advances suggest ways that the targets of assessment-what students know and how well they know it-as well as the methods used to make inferences about student learning can be made more valid and instructionally useful. Principles for designing and using these new kinds of assessments are presented, and examples are used to illustrate the principles. Implications for policy, practice, and research are also explored. With the promise of a productive research-based approach to assessment of student learning, Knowing What Students Know will be important to education administrators, assessment designers, teachers and teacher educators, and education advocates.
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling. Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis.