Innovative Psychometric Modeling And Methods PDF Download
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| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 236 |
| Release | : 2020-09-01 |
| Genre | : Education |
| ISBN | : 1648022243 |
Download Innovative Psychometric Modeling and Methods Book in PDF, ePub and Kindle
The general theme of this book is to present innovative psychometric modeling and methods. In particular, this book includes research and successful examples of modeling techniques for new data sources from digital assessments, such as eye-tracking data, hint uses, and process data from game-based assessments. In addition, innovative psychometric modeling approaches, such as graphical models, item tree models, network analysis, and cognitive diagnostic models, are included. Chapters 1, 2, 4 and 6 are about psychometric models and methods for learning analytics. The first two chapters focus on advanced cognitive diagnostic models for tracking learning and the improvement of attribute classification accuracy. Chapter 4 demonstrates the use of network analysis for learning analytics. Chapter 6 introduces the conjunctive root causes model for the understanding of prerequisite skills in learning. Chapters 3, 5, 8, 9 are about innovative psychometric techniques to model process data. Specifically, Chapters 3 and 5 illustrate the usage of generalized linear mixed effect models and item tree models to analyze eye-tracking data. Chapter 8 discusses the modeling approach of hint uses and response accuracy in learning environment. Chapter 9 demonstrates the identification of observable outcomes in the game-based assessments. Chapters 7 and 10 introduce innovative latent variable modeling approaches, including the graphical and generalized linear model approach and the dynamic modeling approach. In summary, the book includes theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to model and analyze multiple data sources from digital assessments. When computer-based assessments are emerging and evolving, it is important that researchers can expand and improve the methods for modeling and analyzing new data sources. This book provides a useful resource to researchers who are interested in the development of psychometric methods to solve issues in this digital assessment age.
| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 248 |
| Release | : 2018-12-01 |
| Genre | : Education |
| ISBN | : 1641133287 |
Download Data Analytics and Psychometrics Book in PDF, ePub and Kindle
The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large-scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student’s learning and guide teacher’s instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.
| Author | : Alina A. von Davier |
| Publisher | : Springer |
| Total Pages | : 330 |
| Release | : 2017-04-04 |
| Genre | : Education |
| ISBN | : 3319332619 |
Download Innovative Assessment of Collaboration Book in PDF, ePub and Kindle
This edited volume provides a platform for experts from various fields to introduce and discuss their different perspectives on the topic of teamwork and collaborative problem solving. It brings together researchers in organizational teaming, educational collaboration, tutoring, simulation, and gaming as well as those involved in statistical and psychometric process modelling. This book seeks to channel this expertise towards advances in the measurement and assessment of cognitive and non-cognitive skills of individuals and teams.
| Author | : Malcolm Williams |
| Publisher | : SAGE Publications |
| Total Pages | : 665 |
| Release | : 2011-04-19 |
| Genre | : Social Science |
| ISBN | : 1412946484 |
Download The SAGE Handbook of Innovation in Social Research Methods Book in PDF, ePub and Kindle
Social research is a bourgeoning field. Of course it has many traditions and approaches, but there is a high premium upon thinking differently and thinking anew because social life is never static or wholly predictable. The Handbook, edited by internationally recognized scholars, provides a comprehensive, pitch-perfect critical assessment of the field. The main features of the Handbook are: Clear organization into 4 parts dealing with The Social Context of Research; Design and Data Collection; Integrating The Analysis of New Data Types; Sampling, Inference and Measurement Clear, cutting edge chapters on Objectivity; Causation; Organizing Social Research; Correspondence Analysis; Grounded Theory; Conversational Surveys; Mixed Methods; Meta-Analysis; Optimal Matching Analysis; GIS Analysis; Quantitative Narrative Analysis; Longitudinal Studies; SEM; MLM; Qualitative Comparative Analysis; Respondent Driven Sampling Brings together a glittering assembly of the key figures working in the field of research methods Demonstrates the continuities and productive tensions between classical traditions and real world research. The result is a superbly organized text which will be required reading for anyone interested in the routes and future of social research. It is an unparalleled teaching resource and a 'must have' for serious social researchers.
| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 242 |
| Release | : 2024-04-01 |
| Genre | : Computers |
| ISBN | : |
Download Machine Learning, Natural Language Processing, and Psychometrics Book in PDF, ePub and Kindle
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better understand the assessment products or accuracy and the process how an item product was attained. The analysis of the conventional and non-conventional assessment data calls for more methodology other than the latent trait modeling. Natural language processing (NLP) methods and machine learning algorithms have been successfully applied in automated scoring. It has been explored in providing diagnostic feedback to test-takers in writing assessment. Recently, machine learning algorithms have been explored for cheating detection and cognitive diagnosis. When the measurement field promote the use of assessment data to provide feedback to improve teaching and learning, it is the right time to explore new methodology and explore the value added from other data sources. This book presents the use cases of machine learning and NLP in improving the assessment theory and practices in high-stakes summative assessment, learning, and instruction. More specifically, experts from the field addressed the topics related to automated item generations, automated scoring, automated feedback in writing, explainability of automated scoring, equating, cheating and alarming response detection, adaptive testing, and applications in science assessment. This book demonstrates the utility of machine learning and NLP in assessment design and psychometric analysis.
| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 223 |
| Release | : 2020-03-01 |
| Genre | : Computers |
| ISBN | : 1641139536 |
Download Application of Artificial Intelligence to Assessment Book in PDF, ePub and Kindle
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.
| Author | : Luiz Moutinho |
| Publisher | : Springer |
| Total Pages | : 282 |
| Release | : 2017-12-05 |
| Genre | : Business & Economics |
| ISBN | : 3319643940 |
Download Innovative Research Methodologies in Management Book in PDF, ePub and Kindle
A seminal collection of research methodology themes, this two-volume work provides a set of key scholarly developments related to robustness, allowing scholars to advance their knowledge of research methods used outside of their own immediate fields. With a focus on emerging methodologies within management, key areas of importance are dissected with chapters covering statistical modelling, new measurements, digital research, biometrics and neuroscience, the philosophy of research, computer modelling approaches and new mathematical theories, among others. A genuinely pioneering contribution to the advancement of research methods in business studies, Innovative Research Methodologies in Management presents an analytical and engaging discussion on each topic. By introducing new research agendas it aims to pave the way for increased application of innovative techniques, allow ing the exploration of future research perspectives. Volume I covers a range of research methodologies within the realms of philosophy, measurement and modelling, and focusses on meta-modern mixed methods such as neurophilosophy, diagnostic measurement, and emotivity and ephemera research.
| Author | : Paul Irwing |
| Publisher | : John Wiley & Sons |
| Total Pages | : 1064 |
| Release | : 2018-03-14 |
| Genre | : Education |
| ISBN | : 1118489705 |
Download The Wiley Handbook of Psychometric Testing Book in PDF, ePub and Kindle
A must-have resource for researchers, practitioners, and advanced students interested or involved in psychometric testing Over the past hundred years, psychometric testing has proved to be a valuable tool for measuring personality, mental ability, attitudes, and much more. The word ‘psychometrics’ can be translated as ‘mental measurement’; however, the implication that psychometrics as a field is confined to psychology is highly misleading. Scientists and practitioners from virtually every conceivable discipline now use and analyze data collected from questionnaires, scales, and tests developed from psychometric principles, and the field is vibrant with new and useful methods and approaches. This handbook brings together contributions from leading psychometricians in a diverse array of fields around the globe. Each provides accessible and practical information about their specialist area in a three-step format covering historical and standard approaches, innovative issues and techniques, and practical guidance on how to apply the methods discussed. Throughout, real-world examples help to illustrate and clarify key aspects of the topics covered. The aim is to fill a gap for information about psychometric testing that is neither too basic nor too technical and specialized, and will enable researchers, practitioners, and graduate students to expand their knowledge and skills in the area. Provides comprehensive coverage of the field of psychometric testing, from designing a test through writing items to constructing and evaluating scales Takes a practical approach, addressing real issues faced by practitioners and researchers Provides basic and accessible mathematical and statistical foundations of all psychometric techniques discussed Provides example software code to help readers implement the analyses discussed
| Author | : Roy Levy |
| Publisher | : CRC Press |
| Total Pages | : 480 |
| Release | : 2017-07-28 |
| Genre | : Mathematics |
| ISBN | : 1439884684 |
Download Bayesian Psychometric Modeling Book in PDF, ePub and Kindle
A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate—and sometimes conflicting—ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.
| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 243 |
| Release | : 2022-01-01 |
| Genre | : Education |
| ISBN | : 1648026281 |
Download Enhancing Effective Instruction and Learning Using Assessment Data Book in PDF, ePub and Kindle
This book introduces theories and practices for using assessment data to enhance learning and instruction. Topics include reshaping the homework review process, iterative learning engineering, learning progressions, learning maps, score report designing, the use of psychosocial data, and the combination of adaptive testing and adaptive learning. In addition, studies proposing new methods and strategies, technical details about the collection and maintenance of process data, and examples illustrating proposed methods and software are included. Chapters 1, 4, 6, 8, and 9 discuss how to make valid interpretations of results and achieve more efficient instructions from various sources of data. Chapters 3 and 7 propose and evaluate new methods to promote students’ learning by using evidence-based iterative learning engineering and supporting the teachers’ use of assessment data, respectively. Chapter 2 provides technical details on the collection, storage, and security protection of process data. Chapter 5 introduces software for automating some aspects of developmental education and the use of predictive modeling. Chapter 10 describes the barriers to using psychosocial data for formative assessment purposes. Chapter 11 describes a conceptual framework for adaptive learning and testing and gives an example of a functional learning and assessment system. In summary, the book includes comprehensive perspectives of the recent development and challenges of using test data for formative assessment purposes. The chapters provide innovative theoretical frameworks, new perspectives on the use of data with technology, and how to build new methods based on existing theories. This book is a useful resource to researchers who are interested in using data and technology to inform decision making, facilitate instructional utility, and achieve better learning outcomes.
