Iasonas Lamprianou – författare

This book highlights the impact of policy and politics on assessment across the globe. With contributions from England, the Irish Republic, Northern Ireland, Norway, Sweden, Switzerland, and Wales, it explores state-led assessment policies and practices that have been the subject of much debate.We are experiencing a shift from using assessments — especially national tests — as measurement instruments designed to produce information, to a reliance on tests to influence policy and instruction. Once tests become high stakes — for students, teachers, and schools — even those that might have been reasonable monitors of educational success can lose dependability and credibility. However, not all countries’ assessment policies follow the same model and the contributors explore and analyse a range of different national (and supra-national) assessment policy approaches and perspectives. The chapters identify the impetus behind changing assessment policies and practices and analyse ways forward and innovative approaches. Readers can draw their own conclusions about which model(s) can provide the best outcomes for learners – surely the most important part of the equation.This book was originally published as a special issue of Assessment in Education: Principles, Policy & Practice.

This book highlights the impact of policy and politics on assessment across the globe. With contributions from England, the Irish Republic, Northern Ireland, Norway, Sweden, Switzerland, and Wales, it explores state-led assessment policies and practices that have been the subject of much debate.We are experiencing a shift from using assessments — especially national tests — as measurement instruments designed to produce information, to a reliance on tests to influence policy and instruction. Once tests become high stakes — for students, teachers, and schools — even those that might have been reasonable monitors of educational success can lose dependability and credibility. However, not all countries’ assessment policies follow the same model and the contributors explore and analyse a range of different national (and supra-national) assessment policy approaches and perspectives. The chapters identify the impetus behind changing assessment policies and practices and analyse ways forward and innovative approaches. Readers can draw their own conclusions about which model(s) can provide the best outcomes for learners – surely the most important part of the equation.This book was originally published as a special issue of Assessment in Education: Principles, Policy & Practice.

This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book provides updated guidance through the point-and-click menus of BlueSky Statistics software.The book covers all Rasch models frequently used in social sciences, from the Simple Rasch model to the Rating Scale, Partial Credit, and Many-Facets Rasch models. Using a pragmatic approach to model-data fit, this book offers helpful practical examples to investigate Rasch model assumptions. In addition to traditional Rasch model approaches, it introduces the Rasch model as a special case of a Generalized Mixed Effects Model. Readers will also benefit from the online support material which includes all the code used in the book in downloadable and useable files.It also provides a comprehensive guide to R programming and practical guidance on using BlueSky Statistics software's point-and-click menus. This dual approach enables readers to experiment with data analysis using the provided data sets, enhancing their understanding and application of statistical concepts. It will be a valuable resource for both students and researchers who want to use Rasch models in their research.

This new edition provides a step-by-step guide to applying the Rasch model in R, a probabilistic model used by researchers across the social sciences to measure unobservable (“latent”) variables. Although the focus is on simple R code, the book provides updated guidance through the point-and-click menus of BlueSky Statistics software.The book covers all Rasch models frequently used in social sciences, from the Simple Rasch model to the Rating Scale, Partial Credit, and Many-Facets Rasch models. Using a pragmatic approach to model-data fit, this book offers helpful practical examples to investigate Rasch model assumptions. In addition to traditional Rasch model approaches, it introduces the Rasch model as a special case of a Generalized Mixed Effects Model. Readers will also benefit from the online support material which includes all the code used in the book in downloadable and useable files.It also provides a comprehensive guide to R programming and practical guidance on using BlueSky Statistics software's point-and-click menus. This dual approach enables readers to experiment with data analysis using the provided data sets, enhancing their understanding and application of statistical concepts. It will be a valuable resource for both students and researchers who want to use Rasch models in their research.

This is the first book to illustrate the use of Network Analysis for the analysis of rating datasets. It uses a multi-disciplinary approach to focus on the quantification and visualization of rater effects for exploration, diagnosis, reporting, decision-making, and planning.Combining cutting-edge theories of rater effects with step-by-step practical examples using publicly available data and open-source code (R packages), this book provides an introduction to the concept of rating datasets. It uses simple language to discuss data requirements, model assumptions, and other important details, and it follows all theoretical sections with practical applications that analyze empirical data step-by-step. The book also demonstrates how the proposed methods can be integrated with more established approaches, such as Rasch models, to make the analysis of relevant data more efficient. With its accessible language and gentle introduction to graph theory and network analysis, this book is suitable for readers unfamiliar with the methodology. throughout the book, readers will become able to plan a rater-effects study, format the dataset, conduct the analysis, and report the findings. The data and code are available as supplementary online material to encourage readers to replicate the analysis and reflect on the results.This book will be of great interest to graduate students and researchers who conduct research on using ratings, and will also be an important reference for anyone studying measurement, research, and quantitative methods. Researchers and practitioners in the fields of testing services, awarding bodies and social sciences in general will also find this book useful