Informing the Practice of Teaching Using Formative and Interim Assessment


Book Description

This book focuses on interim and formative assessments as distinguished from the more usual interest in summative assessment. I was particularly interested in seeing what the experts have to say about a full system of assessment. This book has particular interest in what information a teacher, a school or even a state could collect that monitors the progress of a student as he or she learns. The authors were asked to think about assessing the effects of teaching and learning throughout the student’s participation in the curriculum. This book is the product of a conference by the Maryland Assessment Research Center for Education Success (MARCES) with funding from the Maryland State Department of Education.




The Cambridge Handbook of Instructional Feedback


Book Description

This book brings together leading scholars from around the world to provide their most influential thinking on instructional feedback. The chapters range from academic, in-depth reviews of the research on instructional feedback to a case study on how feedback altered the life-course of one author. Furthermore, it features critical subject areas - including mathematics, science, music, and even animal training - and focuses on working at various developmental levels of learners. The affective, non-cognitive aspects of feedback are also targeted; such as how learners react emotionally to receiving feedback. The exploration of the theoretical underpinnings of how feedback changes the course of instruction leads to practical advice on how to give such feedback effectively in a variety of diverse contexts. Anyone interested in researching instructional feedback, or providing it in their class or course, will discover why, when, and where instructional feedback is effective and how best to provide it.




How to Make Decisions with Different Kinds of Student Assessment Data


Book Description

In How to Make Decisions with Different Kinds of Student Assessment Data, best-selling author Susan M. Brookhart helps teachers and administrators understand the critical elements and nuances of assessment data and how that information can best be used to inform improvement efforts in the school or district. Readers will learn— * What different kinds of data can—and cannot—tell us about student learning; * What different analyses reveal about changes in student achievement; * How to interpret, use, and share relevant data; and * How to create a model to go from problem to solution in a data-based decision-making process. With easy-to-understand explanations, supplemented by examples and scenarios from actual schools, this book offers a path to better understanding, more accurate interpretation of assessment results, and—most important—more effective use of data to improve teaching and learning.




Classroom Assessment and Educational Measurement


Book Description

Classroom Assessment and Educational Measurement explores the ways in which the theory and practice of both educational measurement and the assessment of student learning in classroom settings mutually inform one another. Chapters by assessment and measurement experts consider the nature of classroom assessment information, from student achievement to affective and socio-emotional attributes; how teachers interpret and work with assessment results; and emerging issues in assessment such as digital technologies and diversity/inclusion. This book uniquely considers the limitations of applying large-scale educational measurement theory to classroom assessment and the adaptations necessary to make this transfer useful. Researchers, graduate students, industry professionals, and policymakers will come away with an essential understanding of how the classroom assessment context is essential to broadening contemporary educational measurement perspectives. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.




Teaching Middle Years


Book Description

Teaching Middle Years has established itself as the most respected Australian text to focus on the adolescent years of schooling. Recognition of the educational importance of this age group continues to grow as research reveals the benefits of programs designed especially for young people's needs. This third edition provides a systematic overview of the philosophy, principles and key issues in middle schooling, together with a new depth of focus on the emotional problems and behavioural challenges in working with students. The editors explore in detail two key areas in middle years pedagogy - differentiation and engagement - and there are new chapters on achieving effective transition, the importance of physical activity in adolescence, and how to develop cooperative and collaborative learning. Featuring contributions from leading experts in the field, and fully revised and updated to reflect the latest research, Teaching Middle Years will assist both pre-service and in-service teachers to bring out the very best in their students. Praise for the first edition: 'Teaching Middle Years gives the reader many ideas and examples based on sound research. It's an excellent coverage of the current thinking in this critical area of education.'- from Teacher: The National Education Magazine 'Offers educators a combination of theoretical constructions based on Australian and international research and practical suggestions for teaching middle years students based on the proven good practices of many effective middle years teachers.' - from the Australian Journal of Middle Schooling 'This book should be required reading for every middle school leader who strives to better understand and facilitate middle level learning and achievement.' - from Choice: Current Reviews for Academic Libraries




Enhancing Effective Instruction and Learning Using Assessment Data


Book Description

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.







Children′s Errors in Mathematics


Book Description

This practical and popular guide to children’s common errors and misconceptions in primary mathematics is an essential tool for teachers and trainees. It supports them in planning for and tackling potential errors and enhances their understanding of the difficulties encountered in mathematical development. This fourth edition explores how a Growth Mindset approach works alongside an awareness of children′s errors and how mistakes themselves are powerful learning tools. This edition includes 50 new identifiable misconceptions children have of mathematics. The text also considers the role of the teacher in understanding and addressing children’s common mathematical misconceptions. Key features: Linked to the new National Curriculum and covers every objective Provides an essential tool for planning primary mathematics lessons Explores how common misconceptions can be anticipated and addressed




Environmental and Sustainability Education (ESE) in the English-Speaking Caribbean


Book Description

This book offers readers a diversity of perspectives, experiences and practical examples from various facets of Environmental and Sustainability Education (ESE) that can propel practice, further research and inform decision-making in the region, thus making for more cogent and effective ESE. The Caribbean region is comprised of what is said to be the largest number of Small Island Developing States (SIDS), together with the non-island nations of Belize, Guyana, and Suriname. Although diverse with respect to governance, size, topography, and income, the Caribbean region has a common set of geographic and socio-economic characteristics that make it vulnerable to environmental hazards, economic challenges and social instability. Further to these particular vulnerabilities are various phenomena that pose critical sustainability challenges, two of which are climate change and crime and violence. Consequently, responsive and relevant ESE is needed to address these issues through knowledge enhancement, attitudinal change, skills development and behaviour change. As we seek solutions, this text brings together various empirical and theoretical contributions focused primarily on the English-speaking Caribbean region, that explore a number of areas such as ESE pedagogy, teacher education, values education and progress evaluation. This volume will be a key resource for educators, policymakers, scholars and advanced students of ESE, as well as those interested in protecting our planet. It was originally published as a special issue of Environmental Education Research.




Machine Learning, Natural Language Processing, and Psychometrics


Book Description

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.