With the current push toward educational reform, there is great potential for innovation and change, particularly in large scale testing. One area where change is possible is in cognitive diagnostic assessment. Researchers in educational measurement and cognitive psychology are finally in a position to design tests targeted specifically for providing valuable information about students' cognitive strengths and weaknesses. This self-contained volume organizes what is known about cognitive diagnostic assessment in education, including its conceptual and philosophical basis, methods, and applications. The complete list of topics includes educational demand, philosophical rationale, construct validity, cognitive methods, test construction, statistical models, and unresolved issues (e.g., how to best translate diagnostic information into teaching practices). Leighton and Gierl present a comprehensive and up-to-date examination of cognitive diagnostic assessment in education.

The purpose of this book is to identify how educational tests, especially large-scale tests given to students in grades K-12, can be improved so that they produce better information about what students know and don't know. By consulting and integrating psychological research into the design of educational tests, it is now possible to create new test items that students understand better than old test items. Moreover, these new test items help identify where students may be experiencing difficulties in learning.

During the past two or three decades, research in cognitive science and psychology has yielded an improved understanding of the fundamental psychological nature of knowledge and cognitive skills that psychological testing attempts to measure. These theories have reached sufficient maturity, making it reasonable to look upon them to provide a sound theoretical foundation for assessment, particulary for the content of assessments. This fact, combined with much discontentedness over current testing practices, has inspired efforts to bring testing and cognitive theory together to create a new theoretical framework for psychological testing -- a framework developed for diagnosing learners' differences rather than for ranking learners based on their differences. This volume presents some initial accomplishments in the effort to bring testing and cognitive theory together. Contributors originate from both of the relevant research communities -- cognitive research and psychometric theory. Some represent collaborations between representatives of the two communities; others are efforts to reach out in the direction of the other community. Taking fundamentally different forms, psychometric test theory assumes that knowledge can be represented in terms of one or at most a few dimensions, whereas modern cognitive theory typically represents knowledge in networks -- either networks of conceptual relationships or the transition networks of production systems. Cognitively diagnostic assessment is a new enterprise and it is evident that many challenging problems remain to be addressed. Still, it is already possible to develop highly productive interactions between assessment and instruction in both automated tutoring systems and more conventional classrooms. The editors hope that the chapters presented here show how the reform of assessment can take a rigorous path.

As the educational system continues to evolve, it is essential that educators of today devise innovative and strategic approaches to program development and assessment. The Handbook of Research on Program Development and Assessment Methodologies in K-20 Education is an essential reference source for the latest terminology and concepts related to program development. Featuring extensive coverage on a broad range of topics such as cognitive diagnostic assessments, self-directed learning, and digital education, this publication is ideally designed for educators, students, program designers, and librarians seeking current research on inventive strategies and practices to enhance education in the 21st century.

This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification. The handbook also offers applications and special topics and practical guidelines how to plan and conduct research studies with the help of DCMs. Commonly used models in educational measurement and psychometrics typically assume a single latent trait or at best a small number of latent variables that are aimed at describing individual differences in observed behavior. While this allows simple rankings of test takers along one or a few dimensions, it does not provide a detailed picture of strengths and weaknesses when assessing complex cognitive skills. DCMs, on the other hand, allow the evaluation of test taker performance relative to a potentially large number of skill domains. Most diagnostic models provide a binary mastery/non-mastery classification for each of the assumed test taker attributes representing these skill domains. Attribute profiles can be used for formative decisions as well as for summative purposes, for example in a multiple cut-off procedure that requires mastery on at least a certain subset of skills. The number of DCMs discussed in the literature and applied to a variety of assessment data has been increasing over the past decades, and their appeal to researchers and practitioners alike continues to grow. These models have been used in English language assessment, international large scale assessments, and for feedback for practice exams in preparation of college admission testing, just to name a few. Nowadays, technology-based assessments provide increasingly rich data on a multitude of skills and allow collection of data with respect to multiple types of behaviors. Diagnostic models can be understood as an ideal match for these types of data collections to provide more in-depth information about test taker skills and behavioral tendencies.

The Asia-Pacific region needs to maximize the benefits of education to enable it to compete in an economic future dominated by innovation, in which assessing student progress must be an empowering rather than delimiting factor. This detailed exposition of the theoretical basis and application tools of self-directed learning-oriented assessment (SLOA) reflects the very latest research championed by the Assessment Research Centre at The Hong Kong Institute of Education. Featuring a range of relevant case studies, it explores the varied theoretical issues related to SLOA and offers an integrated view of the system fully in line with the constructivist paradigm of learning which advocates formative rather than summative assessment. Many of the initiatives outlined here are firsts in the region. SLOA is already being applied in many schools with links to the ARC. It is an approach to assessment that acknowledges the centrality of self-directed learning and which positions assessment as a tool to enable and enhance self-directed learning. It draws on several theories of learning and assessment, including the constructivist notion that learning is best achieved when students take ownership of their educational process, setting their own goals and monitoring their own progress towards those goals. SLOA has been the research and service approach of the ARC since 2005. In the intervening years the centre has developed a number of tools to facilitate SLOA learning and assessment, including vertical ability scales, teacher-friendly computer software and packages for self-directed learning.

This state-of-the-art resource brings together the most innovative scholars and thinkers in the field of testing to capture the changing conceptual, methodological, and applied landscape of cognitively-grounded educational assessments. Offers a methodologically-rigorous review of cognitive and learning sciences models for testing purposes, as well as the latest statistical and technological know-how for designing, scoring, and interpreting results Written by an international team of contributors at the cutting-edge of cognitive psychology and educational measurement under the editorship of a research director at the Educational Testing Service and an esteemed professor of educational psychology at the University of Alberta as well as supported by an expert advisory board Covers conceptual frameworks, modern methodologies, and applied topics, in a style and at a level of technical detail that will appeal to a wide range of readers from both applied and scientific backgrounds Considers emerging topics in cognitively-grounded assessment, including applications of emerging socio-cognitive models, cognitive models for human and automated scoring, and various innovative virtual performance assessments