The third edition of this esteemed guide delves into the methodology of data collection and the synthesis of exam scores. It provides comprehensive insights on equalizing, scaling, and moderating results, along with practical advice on designing, administering, and marking standardized tests. This revised edition enhances understanding of effective assessment practices, making it an invaluable resource for educators and assessment professionals.
Educational Measurement has been the bible in its field since the first edition was published by ACE in 1951. The importance fo this fourth edition of Educational Measurement is to extensiely update and extend the topics treated in the preious three editions. As such, the fourth edition documents progress in the field and provides critical guidance to the efforts of new generations of researchers and practitioners. Edited by Robert Brennan and jointly sponsored by the American Council on Education (ACE) and the National Council on Measurement in Education, the fourth edition provides in-depth treatments of critical measurement topics, and the chapter authors are acknowledged experts in their respective fields. Educational measurement researchers and practitioners will find this text essential, and those interested in statistics, psychology, business, and economics should also find this work to be of very strong interest. Topics covered are divided into three subject theory and g
Generalizability theory offers an extensive conceptual framework and a powerful set of statistical procedures for characterizing and quantifying the fallibility of measurements. Robert Brennan, the author, has written the most comprehensive and up-to-date treatment of generalizability theory. The book provides a synthesis of those parts of the statistical literature that are directly applicable to generalizability theory. The principal intended audience is measurement practitioners and graduate students in the behavioral and social sciences, although a few examples and references are provided from other fields. Readers will benefit from some familiarity with classical test theory and analysis of variance, but the treatment of most topics does not presume specific background.