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 Statistical Guidelines New Developments in Statistical Methods and Psychometric Tools written by Pietro Cipresso and published by Frontiers Media SA. This book was released on 2022-03-25 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cognitive Diagnostic Assessment for Learning written by Peida Zhan and published by Frontiers Media SA. This book was released on 2022-01-19 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Measuring Improvements in Learning Outcomes Best Practices to Assess the Value Added of Schools written by OECD and published by OECD Publishing. This book was released on 2008-10-27 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This groundbreaking report provides examples of best practices in value-added modelling for measuring school performance.
Download or read book The CIPP Evaluation Model written by Daniel L. Stufflebeam and published by Guilford Publications. This book was released on 2017-03-07 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book's chapters provide background on how and why the CIPP (Context, Input, Process, Product) Model was developed; a detailed presentation of the model; an explanation of the key role of an evaluation-oriented leader, who can decide what and when to evaluate; detailed presentations on evaluation design, budgeting, and contracting; procedures and tools for collecting, analyzing, and reporting evaluation information; and procedures for conducting standards-based meta-evaluations (evaluations of evaluations). These topics are interspersed with illustrative evaluation cases in such areas as education, housing, and military personnel evaluation"--
Download or read book A Practitioner s Guide to Growth Models written by Katherine Castellano and published by . This book was released on 2013-03-01 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Practitioner's Guide to Growth Models
Download or read book Intelligent Data Analysis for COVID 19 Pandemic written by M. Niranjanamurthy and published by Springer Nature. This book was released on 2021-06-22 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.
Download or read book Multivariate Generalized Linear Mixed Models Using R written by Damon Mark Berridge and published by CRC Press. This book was released on 2011-04-25 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model estimation, and endogenous variables, along with SabreR commands and examples. Improve Your Longitudinal Study In medical and social science research, MGLMMs help disentangle state dependence from incidental parameters. Focusing on these sophisticated data analysis techniques, this book explains the statistical theory and modeling involved in longitudinal studies. Many examples throughout the text illustrate the analysis of real-world data sets. Exercises, solutions, and other material are available on a supporting website.
Download or read book Applied Categorical and Count Data Analysis written by Wan Tang and published by CRC Press. This book was released on 2023-04-06 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments. The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies. Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields. Features: Describes the basic ideas underlying each concept and model Includes R, SAS, SPSS and Stata programming codes for all the examples Features significantly expanded Chapters 4, 5, and 8 (Chapters 4-6, and 9 in the second edition Expands discussion for subtle issues in longitudinal and clustered data analysis such as time varying covariates and comparison of generalized linear mixed-effect models with GEE
Download or read book Current Index to Journals in Education written by and published by . This book was released on 1998-04 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Back to the Future On the Road Towards Precision Psychiatry written by Brisa S. Fernandes and published by Frontiers Media SA. This book was released on 2020-04-24 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Download or read book Inflammation and Fibrosis in the Gastrointestinal Tract and Liver Mechanisms and Targets written by Ralf Weiskirchen and published by Frontiers Media SA. This book was released on 2023-04-04 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multidimensional Item Response Theory written by M.D. Reckase and published by Springer Science & Business Media. This book was released on 2009-07-07 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing
Download or read book DEEP LEARNING FOR DATA MINING UNVEILING COMPLEX PATTERNS WITH NEURAL NETWORKS written by Mr. Dayakar Babu Kancherla and published by Xoffencerpublication. This book was released on 2024-05-15 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is a topic that is currently trending in the research world and has captured the attention of a wide variety of sectors in our everyday lives. As a result of the enormous amount of data, there is an imminent requirement to transform big data into information and data that can be used. Controlling production, conducting scientific research, designing engineering projects, managing businesses, and conducting market research are all examples of the knowledge that may be gained from using applications. The process of data mining is thought to have emerged as a consequence of the proliferation of datasets and the development of information technologies. In the process of designing following techniques, the evolutionary routes that have been seen in database industries are taken into consideration. These techniques include the development of datasets, the collection of data, and the supervision of databases for the purpose of data storage and retrieval in order to achieve effective data analysis for improved understanding. Beginning in the year 1960, the information technologies and databases have undergone a methodical evolution, transitioning from simple and traditional processing models to more complex and prevalent database models. Since 1970, the analysis and design of database models have accompanied the invention of relational databases, data organizing methods, indexing, and data modeling tools. This has contributed to the development of these tools. Additionally, the consumers were able to obtain instantaneous access to the data through the utilization of user interfaces, query processing, and query languages. To put it another way, data mining is a method that is utilized for the purpose of extracting knowledge from large databases. Taking into consideration a variety of fields, such as information retrieval, databases, machine learning, and statistics, has led to the development of the products and functionalities that are currently used in data mining. When it comes to the Knowledge Discovery in Databases (KDDs) process, other areas of computer science have encountered a significant problem that is associated with graphics and multimedia systems. Knowledge discovery and discovery (KDD) is a term that refers to the total process of gaining meaningful knowledge from data. KDD is designed to demonstrate the results of the KDD process in a substantial manner.
Download or read book SARS CoV 2 Virology epidemiology diagnosis pathogenesis and control written by Severino Jefferson Ribeiro Da Silva and published by Frontiers Media SA. This book was released on 2024-04-22 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2011-04-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.
