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Bayesian Networks In Educational Assessment

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Bayesian Networks In Educational Assessment

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Author : Russell G. Almond
language : en
Publisher: Springer
Release Date : 2015-03-10

Bayesian Networks In Educational Assessment written by Russell G. Almond and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-10 with Social Science categories.

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.

Bayesian Networks In Educational Assessment

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Author : Russell G. Almond
language : en
Publisher: Springer
Release Date : 2015-03-11

Bayes Nets In Educational Assessment

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Author :
language : en
Publisher:
Release Date : 2000

Bayes Nets In Educational Assessment written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Educational evaluation categories.

Bayesian Networks

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Author : Olivier Pourret
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-30

Bayesian Networks written by Olivier Pourret and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-30 with Mathematics categories.

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.

Bayesian Psychometric Modeling

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Author : Roy Levy
language : en
Publisher: CRC Press
Release Date : 2017-07-28

Bayesian Psychometric Modeling written by Roy Levy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Mathematics categories.

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.

Learning Bayesian Networks

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Author : Richard E. Neapolitan
language : en
Publisher: Prentice Hall
Release Date : 2004

Learning Bayesian Networks written by Richard E. Neapolitan and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.

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.

Bayesian Networks

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Author : Marco Scutari
language : en
Publisher: CRC Press
Release Date : 2021-07-28

Bayesian Networks written by Marco Scutari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-28 with Computers categories.

Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss side by side the underlying theory and its application using R code. The examples start from the simplest notions and gradually increase in complexity. In particular, this new edition contains significant new material on topics from modern machine-learning practice: dynamic networks, networks with heterogeneous variables, and model validation. The first three chapters explain the whole process of Bayesian network modelling, from structure learning to parameter learning to inference. These chapters cover discrete, Gaussian, and conditional Gaussian Bayesian networks. The following two chapters delve into dynamic networks (to model temporal data) and into networks including arbitrary random variables (using Stan). The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R packages and other software implementing Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein-signalling network published in Science and a probabilistic graphical model for predicting the composition of different body parts. Covering theoretical and practical aspects of Bayesian networks, this book provides you with an introductory overview of the field. It gives you a clear, practical understanding of the key points behind this modelling approach and, at the same time, it makes you familiar with the most relevant packages used to implement real-world analyses in R. The examples covered in the book span several application fields, data-driven models and expert systems, probabilistic and causal perspectives, thus giving you a starting point to work in a variety of scenarios. Online supplementary materials include the data sets and the code used in the book, which will all be made available from https://www.bnlearn.com/book-crc-2ed/

Innovations In Bayesian Networks

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Author : Dawn E. Holmes
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-02

Innovations In Bayesian Networks written by Dawn E. Holmes and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-02 with Mathematics categories.

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.

Games As Stealth Assessments

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Author : McCreery, Michael P.
language : en
Publisher: IGI Global
Release Date : 2023-11-01

Games As Stealth Assessments written by McCreery, Michael P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-01 with Education categories.

In the world of assessment, traditional methods often fall short, providing limited insight into individuals' skills and abilities while being susceptible to response biases. Recognizing these shortcomings, researchers have delved into the realm of stealth assessments, a novel approach that embeds traditional measurement techniques within a game-based environment. By seamlessly integrating assessment into gameplay, stealth assessments offer a contextually rich and unobtrusive method of data collection, allowing for a comprehensive understanding of the constructs being assessed. Games as Stealth Assessments unveils the promising field of stealth assessment, exploring its design considerations, research methods, and practical applications. Drawing upon a foundation of psychometrically-sound assessment practices, this book delves into the intersection of thoughtful game design and empirical support for the use of stealth assessments. It justifies the adoption of stealth assessments in academic disciplines such as mathematics, science, and literacy, as well as in the assessment of psychological constructs like aggression, social skills, and self-regulation.

Innovative Approaches For Learning And Knowledge Sharing

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Author : Wolfgang Nejdl
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-22

Innovative Approaches For Learning And Knowledge Sharing written by Wolfgang Nejdl and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-22 with Education categories.

This book constitutes the refereed proceedings of the First European Conference on Technology Enhanced Learning, EC-TEL 2006. The book presents 32 revised full papers, 13 revised short papers and 31 poster papers together with 2 keynote talks. Topics addressed include collaborative learning, personalized learning, multimedia content, semantic web, metadata and learning, workplace learning, learning repositories and infrastructures for learning, as well as experience reports, assessment, and case studies, and more.

Bayesian Networks In Educational Assessment

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