Measuring and Modeling Persons and Situations presents major innovations and contributions on the topic, promoting deeper integration, cross-pollination of ideas across diverse academic disciplines, and the facilitation of the development of practical applications such as matching people to jobs, understanding decision making, and predicting how a group of individuals will interact with one another. The book is organized around two overarching and interrelated themes, with the first focusing on assessing the person and the situation, covering methodological advances and techniques for inferring and measuring characteristics, and showing how they can be instantiated for measurement and predictive purposes. The book's second theme presents theoretical models, conceptualizing how factors of the person and situation can help us understand the psychological dynamics which underlie behavior, the psychological experience of fit or congruence with one's environment, and changes in personality traits over time. - Identifies technologies for measuring and predicting behavior - Infers behavior causes from personality and/or situational variables - Utilizes big data, machine learning and modeling to understand behavior - Includes mobile phone, social media and wearable tech usage analysis - Explores the stability of personality over time - Considers behavior analysis to treat maladaptive behavior

Situations matter. They let people express their personalities and values; provoke motivations, emotions, and behaviors; and are the contexts in which people reason and act. The psychological assessment of situations is a new and rapidly developing area of research, particularly within the fields of personality and social psychology. This volume compiles state-of-the-art knowledge on psychological situations in chapters written by experts in their respective research areas. Bringing together historical reviews, theoretical pieces, methodological descriptions, and empirical applications, this volume is the definitive, go-to source for a psychology of situations.

Learn which dark side of personality assessment to use and when Introduces different assessment tools Highlights the nuances between tests Presents the relevant psychometric properties Explores findings about human nature More about the book We encounter people who possess undesirable dark sides of personality at low levels in our day to day lives, whether it is the boss who acts like a jerk, a cheating partner, or a friend who rubs everyone up the wrong way. This volume explores the latest research on the assessment of the dark personality traits, including the dark triad of narcissism, Machiavellianism, and psychopathy, and more. The internationally renowned group of contributors provide a comprehensive, evidence-based overview of the personality traits currently being explored. Each chapter reviews two main topics. First, a particular measure used to study such traits is discussed. This section is geared to help the reader to understand how researchers in this area capture data on these traits and to best decide which instrument they want to use and when. Second, each chapter then details what the psychometric data on the test reveals about human nature, including topics such as sex differences, workplace behaviors, sexuality, and value systems. In this way, the contributors highlight how the convergence of research from various measures can provide a broad mosaic of information about people colloquially called psychopaths, narcissists, spiteful, Machiavellian, and sadists. This book is essential reading for anyone interested in test development and practitioners interested in the dark side personality traits.

An in-depth guide to executing longitudinal confirmatory factor analysis (CFA) and structural equation modeling (SEM) in Mplus, this book uses latent state–trait (LST) theory as a unifying conceptual framework, including the relevant coefficients of consistency, occasion specificity, and reliability. Following a standard format, chapters review the theoretical underpinnings, strengths, and limitations of the various models; present data examples; and demonstrate each model's application and interpretation in Mplus, with numerous screen shots and output excerpts. Coverage encompasses both traditional models (autoregressive, change score, and growth curve models) and LST models for analyzing single- and multiple-indicator data. The book discusses measurement equivalence testing, intensive longitudinal data modeling, and missing data handling, and provides strategies for model selection and reporting of results. User-friendly features include special-topic boxes, chapter summaries, and suggestions for further reading. The companion website features data sets, annotated syntax files, and output for all of the examples.

Individual differences represent one of the oldest research areas within psychology and serve as the 'nature' component critical for understanding human behaviour. This domain's constructs have long been applied in organizational spheres, including organizational behaviour, organizational psychology, managerial psychology, personnel psychology, leadership, and management. As a result, there exists a vast body of literature exploring the role of individual differences in organizational settings. The Oxford Handbook of Individual Differences in Organizational Contexts reviews the individual differences, paying attention both to psychological differences (e.g., personality traits, dark personality traits, intelligence types, self-monitoring, chronic regulatory focus) and biological/physiological differences (e.g., sex, age, facial morphology, genetic differences, neurological differences). In doing so, it serves two purposes. First, it aims to help decrease fragmentation in the field, and facilitate discussions among different streams of research within this literature. Secondly, it aims to render this literature more accessible to academics and students wishing to deepen their understanding of individual differences. Comprising twenty-six chapters authored by fifty-seven esteemed academics, this book facilitates readers in comprehending the key findings, questions, and future research areas of individual differences research in organizational contexts. This book can be of interest also to practitioners that need a deep understanding of individual differences, such as HR managers and recruiters.

Several key developments challenge the field of educational measurement today: demands for tests at larger scales with higher stakes, an improved understanding of how people develop capabilities, and new technologies for interactive digital assessments. Sociocognitive Foundations of Educational Measurement integrates new developments in educational measurement and educational psychology in order to provide researchers, testing professionals, and students with an innovative sociocognitive perspective on assessment. This comprehensive volume begins with a broad explanation of the sociocognitive perspective and the foundations of assessment, then provides a series of focused applications to major topics such as assessment arguments, validity, fairness, interactive assessment, and a conception of "measurement" in educational assessment. Classical test theory, item response theory, categorical models, mixture models, cognitive diagnosis models, and Bayesian networks are explored from the resulting perspective. Ideal for specialists in these areas, graduate students, developers, and scholars in both educational measurement and fields that contribute to a sociocognitive perspective, this book consolidates nearly a decade of research into a fresh perspective on educational measurement.

Education is a hot topic. From the stage of presidential debates to tonight's dinner table, it is an issue that most Americans are deeply concerned about. While there are many strategies for improving the educational process, we need a way to find out what works and what doesn't work as well. Educational assessment seeks to determine just how well students are learning and is an integral part of our quest for improved education. The nation is pinning greater expectations on educational assessment than ever before. We look to these assessment tools when documenting whether students and institutions are truly meeting education goals. But we must stop and ask a crucial question: What kind of assessment is most effective? At a time when traditional testing is subject to increasing criticism, research suggests that new, exciting approaches to assessment may be on the horizon. Advances in the sciences of how people learn and how to measure such learning offer the hope of developing new kinds of assessments-assessments that help students succeed in school by making as clear as possible the nature of their accomplishments and the progress of their learning. Knowing What Students Know essentially explains how expanding knowledge in the scientific fields of human learning and educational measurement can form the foundations of an improved approach to assessment. These advances suggest ways that the targets of assessment-what students know and how well they know it-as well as the methods used to make inferences about student learning can be made more valid and instructionally useful. Principles for designing and using these new kinds of assessments are presented, and examples are used to illustrate the principles. Implications for policy, practice, and research are also explored. With the promise of a productive research-based approach to assessment of student learning, Knowing What Students Know will be important to education administrators, assessment designers, teachers and teacher educators, and education advocates.