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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.
Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.
This key resource helps practitioners optimize their diagnostic practices in PreK–12 settings. Now significantly revised for DSM-5, the book cuts through the overwhelming length and complexity of the diagnostic manual by focusing thematically on the most common child and adolescent concerns. Tips are provided for diagnostic decision making and coding, and technical terms are demystified. Emphasis is given to using diagnosis as a foundation for effective intervention. The book highlights links to special education eligibility under IDEA and discusses ethical and professional issues in school-based assessment. New to This Edition *Revised throughout for DSM-5. *Restructured chapters on learning, communication, and motor problems; mood problems; anxiety problems; conduct problems; and impulse-control problems. *Updated content on IDEA 2004. *Notes encapsulating changes to each set of diagnostic criteria, for those familiar with the prior DSM. *Author Commentary sidebars sharing clinical insights and experiences.
Offers practical advice on using and improving assessment for learning in the classroom.
This book offers a smart and tightly reasoned critique of the educational status quo.
Children living in poverty are more likely to have mental health problems, and their conditions are more likely to be severe. Of the approximately 1.3 million children who were recipients of Supplemental Security Income (SSI) disability benefits in 2013, about 50% were disabled primarily due to a mental disorder. An increase in the number of children who are recipients of SSI benefits due to mental disorders has been observed through several decades of the program beginning in 1985 and continuing through 2010. Nevertheless, less than 1% of children in the United States are recipients of SSI disability benefits for a mental disorder. At the request of the Social Security Administration, Mental Disorders and Disability Among Low-Income Children compares national trends in the number of children with mental disorders with the trends in the number of children receiving benefits from the SSI program, and describes the possible factors that may contribute to any differences between the two groups. This report provides an overview of the current status of the diagnosis and treatment of mental disorders, and the levels of impairment in the U.S. population under age 18. The report focuses on 6 mental disorders, chosen due to their prevalence and the severity of disability attributed to those disorders within the SSI disability program: attention-deficit/hyperactivity disorder, oppositional defiant disorder/conduct disorder, autism spectrum disorder, intellectual disability, learning disabilities, and mood disorders. While this report is not a comprehensive discussion of these disorders, Mental Disorders and Disability Among Low-Income Children provides the best currently available information regarding demographics, diagnosis, treatment, and expectations for the disorder time course - both the natural course and under treatment.
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.
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.