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The Race To The Top program strongly advocates the use of computer technology in assessments. It dramatically promotes computer-based testing, linear or adaptive, in K-12 state assessment programs. Moreover, assessment requirements driven by this federal initiative exponentially increase the complexity in assessment design and test development. This book provides readers with a review of the history and basics of computer-based tests. It also offers a macro perspective for designing such assessment systems in the K-12 setting as well as a micro perspective on new challenges such as innovative items, scoring of such items, cognitive diagnosis, and vertical scaling for growth modeling and value added approaches to assessment. The editors’ goal is to provide readers with necessary information to create a smarter computer-based testing system by following the advice and experience of experts from education as well as other industries. This book is based on a conference (http://marces.org/workshop.htm) held by the Maryland Assessment Research Center for Education Success. It presents multiple perspectives including test vendors and state departments of education, in designing and implementing a computer-based test in the K-12 setting. The design and implementation of such a system requires deliberate planning and thorough considerations. The advice and experiences presented in this book serve as a guide to practitioners and as a good source of information for quality control. The technical issues discussed in this book are relatively new and unique to K-12 large-scale computer-based testing programs, especially due to the recent federal policy. Several chapters provide possible solutions to psychometricians dealing with the technical challenges related to innovative items, cognitive diagnosis, and growth modeling in computer-based linear or adaptive tests in the K-12 setting.
The papers in this collection were commissioned by the Board on Testing and Assessment (BOTA) of the National Research Council (NRC) for a workshop held on November 14, 2001, with support from the William and Flora Hewlett Foundation. Goals for the workshop were twofold. One was to share the major messages of the recently released NRC committee report, Knowing What Students Know: The Science and Design of Educational Assessment (2001), which synthesizes advances in the cognitive sciences and methods of measurement, and considers their implications for improving educational assessment. The second goal was to delve more deeply into one of the major themes of that report-the role that technology could play in bringing those advances together, which is the focus of these papers. For the workshop, selected researchers working in the intersection of technology and assessment were asked to write about some of the challenges and opportunities for more fully capitalizing on the power of information technologies to improve assessment, to illustrate those issues with examples from their own research, and to identify priorities for research and development in this area.
Over the past thirty years, student assessment has become an increasingly important component of public education. A variety of methodologies in testing have been developed to obtain and interpret the wealth of assessment outcomes. As assessment goals are getting increasingly multifaceted, new testing methodologies are called for to provide more accessible and reliable information on more complex constructs or processes, such as students' critical thinking and problem-solving skills. Testing methodologies are needed to extract information from assessments on such complicated skills, in order to advise teachers about certain areas of students that need intervention. It is even a bigger challenge, and a vital mission of today’s large-scale assessments, to gain such information from testing data in an efficient manner. For example PARCC and Smarter Balanced Assessments consortia are both striving to offer formative assessments through individualized, tailored testing. The book provides state-of-the-art coverage on new methodologies to support tradit ional summative assessment, and more importantly, for emerging formative assessments.
Devising tests that evaluate a nation’s educational standing and implement efficacious educational reforms requires a careful balance among the contributions of technology, psychometrics, test design, and the learning sciences. Unlike other forms of adaptive testing, multistage testing (MST) is highly suitable for testing educational achievement because it can be adapted to educational surveys and student testing. Computerized Multistage Testing: Theory and Applications covers the methodologies, underlying technology, and implementation aspects of this type of test design. The book discusses current scientific perspectives and practical considerations for each step involved in setting up an MST program. It covers the history of MST, test design and implementation for various purposes, item pool development and maintenance, IRT-based and classical test theory-based methodologies for test assembly, routing and scoring, equating, test security, and existing software. It also explores current research, existing operational programs, and innovative future assessments using MST. Intended for psychologists, social scientists, and educational measurement scientists, this volume provides the first unified source of information on the design, psychometrics, implementation, and operational use of MST. It shows how to apply theoretical statistical tools to testing in novel and useful ways. It also explains how to explicitly tie the assumptions made by each model to observable (or at least inferable) data conditions.
The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.
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
The capabilities and possibilities of emerging game-based learning technologies bring about a new perspective of learning and instruction. This, in turn, necessitates alternative ways to assess the kinds of learning that are taking place in the game-based environments. The field has been broadening the focus of assessment in game environments (i.e., what we measure), developing processes and methodologies that go beyond psychometrics practices (i.e., how we go about assessment in games), and implementing the game-based assessment (GBA) in real contexts. The current state of the field calls for a revisit of this topic to understand what we have learned from the research on this topic, and how the GBA work changed how the field thinks about assessment beyond game environments. Accordingly, this comprehensive volume covers the current state of research, methodology, and technology of game-based assessment. It features four major themes: what we are measuring in games, how GBA has influenced how people do assessment beyond games, new methods and practices, and implementations of GBA. The audience for this volume includes researchers, graduate students, teachers, and professional practitioners in the areas of education, instructional design, educational psychology, academic and organizational development, and instructional technology.
This book introduces and explores major topics in contemporary educational measurement: criterion-referenced testing, item response theory (IRT), computer-based testing, cross-lingual and cross-cultural assessment, and accountability testing. Psychometric experts describe forward-looking measurement practices and provide a contextualized understanding of how and why they were developed, how they can be used, and where they may go in the future. In addition to presenting key concepts and formulas, the volume covers established and emerging applications and discusses recurrent challenges that require additional research. A helpful glossary of abbreviations is included. The book is grounded in the work of Ronald K. Hambleton.
The U.S. information technology (IT) research and development (R&D) ecosystem was the envy of the world in 1995. However, this position of leadership is not a birthright, and it is now under pressure. In recent years, the rapid globalization of markets, labor pools, and capital flows have encouraged many strong national competitors. During the same period, national policies have not sufficiently buttressed the ecosystem, or have generated side effects that have reduced its effectiveness. As a result, the U.S. position in IT leadership today has materially eroded compared with that of prior decades, and the nation risks ceding IT leadership to other nations within a generation. Assessing the Impacts of Changes in the Information Technology R&D Ecosystem calls for a recommitment to providing the resources needed to fuel U.S. IT innovation, to removing important roadblocks that reduce the ecosystem's effectiveness in generating innovation and the fruits of innovation, and to becoming a lead innovator and user of IT. The book examines these issues and makes recommendations to strengthen the U.S. IT R&D ecosystem.