Isaac I. Bejar - Böcker

If one were to conduct an analysis of any profession the "ability to think analogically" is more than likely to be one of the requirements for success, be it an architectural studio, a research laboratory, a legal office, or a nuclear plant. Cognitive scientists are aware of the prominence of analogical reasoning in all forms of reasoning and learning, and have devoted substantial effort to ascer­ taining its nature. Test builders, like cognitive scientists, are aware of the cen­ trality of analogical reasoning and figure, correctly, that a test that samples a student's ability to think analogically may well be a good predictor of success in a variety of fields. This book is the result of a project to investigate analogical reasoning from both an individual differences and a cognitive perspective. The book is directed to both researchers and practitioners concerned with the nature and measurement of analogical reasoning. Cognitive scientists, linguists, psycholinguists, and natural language researchers will find the seman­ tic taxonomy and accompanying empirical results food for thought. Test devel­ opers will fmd it reassuring that performance on verbal analogy items is not just a reflection of the size of a person's vocabulary, and that tests can be designed according to principles, rather than assembled to satisfy a set of statistical speci­ fications. Psychometricians will find that content and response modelling can go together and that there are distinct benefits in approaching psychometric re­ sponse modelling from that integrative perspective.

Presents a cogent overview of current developments in achievement testing, with a look at applications. Examines differences between the random sampling model and the latent trait model.

The editors of this volume suggest that there are missing elements in the conceptualization upon which standard test theory is based. Those elements are models for just how people know what they know and do what they can do, and the ways in which they increase these capacities. Different models are useful for different purposes; therefore, broader or alternative student models may be appropriate. The chapters in this volume consider a variety of directions in which standard test theory might be extended. Topics covered include: the role of test theory in light of recent work in cognitive and educational psychology, test design, student modeling, test analysis, and the integration of assessment and instruction.

The use of computers and the Internet in the testing community has expanded the opportunity for innovative testing. Until now, there was no one source that reviewed the latest methods of automated scoring for complex assessments. This is the first volume to provide that coverage, along with examples of "best practices" in the design, implementation, and evaluation of automated complex assessment. The contributing authors, all noted leaders in the field, introduce each method in the context of actual applications in real assessments so as to provide a realistic view of current industry practices. Evidence Centered Design, an innovative approach to assessment design, is used as the book's conceptual framework. The chapters review both well known methods for automated scoring such as rule-based logic, regression-based, and IRT systems, as well as more recent procedures such as Bayesian and neural networks. The concluding chapters compare and contrast the various methods and provide a vision for the future. Each chapter features a discussion of the philosophical and practical approaches of the method, the associated implications for validity, reliability, and implementation, and the calculations and processes of each technique. Intended for researchers, practitioners, and advanced students in educational testing and measurement, psychometrics, cognitive science, technical training and assessment, diagnostic, licensing, and certification exams, and expert systems, the book also serves as a resource in advanced courses in educational measurement or psychometrics.

The use of computers and the Internet in the testing community has expanded the opportunity for innovative testing. Until now, there was no one source that reviewed the latest methods of automated scoring for complex assessments. This is the first volume to provide that coverage, along with examples of "best practices" in the design, implementation, and evaluation of automated complex assessment. The contributing authors, all noted leaders in the field, introduce each method in the context of actual applications in real assessments so as to provide a realistic view of current industry practices. Evidence Centered Design, an innovative approach to assessment design, is used as the book's conceptual framework. The chapters review both well known methods for automated scoring such as rule-based logic, regression-based, and IRT systems, as well as more recent procedures such as Bayesian and neural networks. The concluding chapters compare and contrast the various methods and provide a vision for the future. Each chapter features a discussion of the philosophical and practical approaches of the method, the associated implications for validity, reliability, and implementation, and the calculations and processes of each technique. Intended for researchers, practitioners, and advanced students in educational testing and measurement, psychometrics, cognitive science, technical training and assessment, diagnostic, licensing, and certification exams, and expert systems, the book also serves as a resource in advanced courses in educational measurement or psychometrics.