Download or read book Bayesian Networks in Educational Assessment written by Russell G. Almond and published by Springer. This book was released on 2015-03-10 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics. This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
Download or read book Bayesian Networks in Educational Assessment written by Russell G. Almond and published by Springer. This book was released on 2015-03-11 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics. This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
Download or read book Bayes Nets in Educational Assessment written by and published by . This book was released on 2000 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Download or read book Innovative Assessment for the 21st Century written by Valerie J. Shute and published by Springer Science & Business Media. This book was released on 2010-09-08 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s rapidly changing and information-rich world, students are not acquiring adequate knowledge and skills to prepare them for careers in mathematics, science, and technology with the traditional approach to assessment and instruction. New competencies (e.g., information communication and technology skills) are needed to deal successfully with the deluge of data. In order to accomplish this, new "educationally valuable" skills must be acknowledged and assessed. Toward this end, the skills we value and support for a society producing knowledge workers, not simply service workers, must be identified, together with methods for their measurement. Innovative Assessment for the 21st Century explores the faces of future assessment—and ask hard questions, such as: What would an assessment that captures all of the above attributes look like? Should it be standardized? What is the role of the professional teacher?
Download or read book Innovations in Bayesian Networks written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2008-10-02 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.
Download or read book Bayesian Psychometric Modeling written by Roy Levy and published by CRC Press. This book was released on 2017-07-28 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate—and sometimes conflicting—ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.
Download or read book User Modeling written by Anthony Jameson and published by Springer. This book was released on 1997-07-08 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: User modeling researchers look for ways of enabling interactive software systems to adapt to their users-by constructing, maintaining, and exploiting user models, which are representations of properties of individual users. User modeling has been found to enhance the effectiveness and/or usability of software systems in a wide variety of situations. Techniques for user modeling have been developed and evaluated by researchers in a number of fields, including artificial intelligence, education, psychology, linguistics, human-computer interaction, and information science. The biennial series of International Conferences on User Modeling provides a forum in which academic and industrial researchers from all of these fields can exchange their complementary insights on user modeling issues. The published proceedings of these conferences represent a major source of information about developments in this area.
Download or read book The Learning Sciences in Educational Assessment written by Jacqueline P. Leighton and published by Cambridge University Press. This book was released on 2011-06-13 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is mounting hope in the United States that federal legislation in the form of No Child Left Behind will improve educational outcomes. As titanic as the challenge appears to be, however, the solution could be at our fingertips. This volume identifies visual types of cognitive models in reading, science and mathematics for researchers, test developers, school administrators, policy makers and teachers. In the process of identifying these cognitive models, the book also explores methodological or translation issues to consider as decisions are made about how to generate psychologically informative and psychometrically viable large-scale assessments based on the learning sciences. Initiatives to overhaul educational systems in disrepair may begin with national policies, but the success of these policies will hinge on how well stakeholders begin to rethink what is possible with a keystone of the educational system: large-scale assessment.
Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R
Download or read book The History of Educational Measurement written by Brian E. Clauser and published by Taylor & Francis. This book was released on 2021-07-07 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The History of Educational Measurement collects essays on the most important topics in educational testing, measurement, and psychometrics. Authored by the field’s top scholars, this book offers unique historical viewpoints, from origins to modern applications, of formal testing programs and mental measurement theories. Topics as varied as large-scale testing, validity, item-response theory, federal involvement, and notable assessment controversies complete a survey of the field’s greatest challenges and most important achievements. Graduate students, researchers, industry professionals, and other stakeholders will find this volume relevant for years to come.
Download or read book Learning Bayesian Networks written by Richard E. Neapolitan and published by Prentice Hall. This book was released on 2004 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information. Some of the topics discussed include Pearl's message passing algorithm, Parameter Learning: 2 Alternatives, Parameter Learning r Alternatives, Bayesian Structure Learning, and Constraint-Based Learning. For expert systems developers and decision theorists.
Download or read book Knowing What Students Know written by National Research Council and published by National Academies Press. This book was released on 2001-10-27 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Sociocognitive Foundations of Educational Measurement written by Robert J. Mislevy and published by Routledge. This book was released on 2018-04-09 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several key developments challenge the field of educational measurement today: demands for tests at larger scales with higher stakes, an improved understanding of how people develop capabilities, and new technologies for interactive digital assessments. Sociocognitive Foundations of Educational Measurement integrates new developments in educational measurement and educational psychology in order to provide researchers, testing professionals, and students with an innovative sociocognitive perspective on assessment. This comprehensive volume begins with a broad explanation of the sociocognitive perspective and the foundations of assessment, then provides a series of focused applications to major topics such as assessment arguments, validity, fairness, interactive assessment, and a conception of "measurement" in educational assessment. Classical test theory, item response theory, categorical models, mixture models, cognitive diagnosis models, and Bayesian networks are explored from the resulting perspective. Ideal for specialists in these areas, graduate students, developers, and scholars in both educational measurement and fields that contribute to a sociocognitive perspective, this book consolidates nearly a decade of research into a fresh perspective on educational measurement.
Download or read book Introduction to Bayesian Networks written by Finn V. Jensen and published by Springer. This book was released on 1997-08-15 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains: Tool for building Bayesian networks -- Library of examples -- Library of proposed solutions to some exercises.
Download or read book Automated Scoring of Complex Tasks in Computer based Testing written by David M. Williamson and published by Psychology Press. This book was released on 2006 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first volume to provide the latest methods and examples of "best practices" in the design, implementation, and evaluation of automated scoring for complex assessments. The contributing authors, all noted leaders in the field, introduce each m
Download or read book Theoretical Issues of Using Simulations and Games in Educational Assessment written by Harold F. O'Neil and published by Routledge. This book was released on 2021-08-27 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting original studies and rich conceptual analyses, this volume reports on theoretical issues involved in the use of simulations and games in educational assessment. Chapters consider how technologies can be used to effectively assess, modify, and enhance learning and assessment in education and training. By highlighting theoretical issues arising from the use of games and simulations as assessment tools for selection and classification, training, and evaluation across educational and workplace contexts, the volume offers both broad conceptual views on assessment, as well as rich descriptions of various, context-specific applications. Through a focus that includes both quantitative and qualitative approaches, policy implications, meta-analysis, and constructs, the volume highlights commonalities and divergence in theoretical research being conducted in relation to K-12, post-secondary, and military education and assessment. In doing so, the collection enhances understanding of how games and simulations can intersect with the science of learning to improve educational outcomes. Given its rigorous and multidisciplinary approach, this book will prove an indispensable resource for researchers and scholars in the fields of educational assessment and evaluation, educational technology, military psychology, and educational psychology.
