Download or read book Data Management in Large Scale Education Research written by Crystal Lewis and published by CRC Press. This book was released on 2024-07-09 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research data management is becoming more complicated. Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices. Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection. While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well. The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies. The book starts by describing the research life cycle and how data management fits within this larger picture. The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase. Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features: Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaboratively Can be read in its entirety, or referenced as needed throughout the life cycle Includes relatable examples specific to education research Includes a discussion on how to organize and document data in preparation for data sharing requirements Contains links to example documents as well as templates to help readers implement practices

Download or read book Data Management for Researchers written by Kristin Briney and published by Pelagic Publishing Ltd. This book was released on 2015-09-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin

Download or read book Effective Big Data Management and Opportunities for Implementation written by Singh, Manoj Kumar and published by IGI Global. This book was released on 2016-06-20 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Big data” has become a commonly used term to describe large-scale and complex data sets which are difficult to manage and analyze using standard data management methodologies. With applications across sectors and fields of study, the implementation and possible uses of big data are limitless. Effective Big Data Management and Opportunities for Implementation explores emerging research on the ever-growing field of big data and facilitates further knowledge development on methods for handling and interpreting large data sets. Providing multi-disciplinary perspectives fueled by international research, this publication is designed for use by data analysts, IT professionals, researchers, and graduate-level students interested in learning about the latest trends and concepts in big data.

Download or read book Implementation of Large Scale Education Assessments written by Petra Lietz and published by John Wiley & Sons. This book was released on 2017-04-24 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a comprehensive treatment of issues related to the inception, design, implementation and reporting of large-scale education assessments. In recent years many countries have decided to become involved in international educational assessments to allow them to ascertain the strengths and weaknesses of their student populations. Assessments such as the OECD's Programme for International Student Assessment (PISA), the IEA's Trends in Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy (PIRLS) have provided opportunities for comparison between students of different countries on a common international scale. This book is designed to give researchers, policy makers and practitioners a well-grounded knowledge in the design, implementation, analysis and reporting of international assessments. Readers will be able to gain a more detailed insight into the scientific principles employed in such studies allowing them to make better use of the results. The book will also give readers an understanding of the resources needed to undertake and improve the design of educational assessments in their own countries and regions. Implementation of Large-Scale Education Assessments: Brings together the editors’ extensive experience in creating, designing, implementing, analysing and reporting results on a wide range of assessments. Emphasizes methods for implementing international studies of student achievement and obtaining highquality data from cognitive tests and contextual questionnaires. Discusses the methods of sampling, weighting, and variance estimation that are commonly encountered in international large-scale assessments. Provides direction and stimulus for improving global educational assessment and student learning Is written by experts in the field, with an international perspective. Survey researchers, market researchers and practitioners engaged in comparative projects will all benefit from the unparalleled breadth of knowledge and experience in large-scale educational assessments gathered in this one volume.

Download or read book Telling Stories with Data written by Rohan Alexander and published by CRC Press. This book was released on 2023-07-27 with total page 759 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book equips students with the end-to-end skills needed to do data science. That means gathering, cleaning, preparing, and sharing data, then using statistical models to analyse data, writing about the results of those models, drawing conclusions from them, and finally, using the cloud to put a model into production, all done in a reproducible way. At the moment, there are a lot of books that teach data science, but most of them assume that you already have the data. This book fills that gap by detailing how to go about gathering datasets, cleaning and preparing them, before analysing them. There are also a lot of books that teach statistical modelling, but few of them teach how to communicate the results of the models and how they help us learn about the world. Very few data science textbooks cover ethics, and most of those that do, have a token ethics chapter. Finally, reproducibility is not often emphasised in data science books. This book is based around a straight-forward workflow conducted in an ethical and reproducible way: gather data, prepare data, analyse data, and communicate those findings. This book will achieve the goals by working through extensive case studies in terms of gathering and preparing data, and integrating ethics throughout. It is specifically designed around teaching how to write about the data and models, so aspects such as writing are explicitly covered. And finally, the use of GitHub and the open-source statistical language R are built in throughout the book. Key Features: Extensive code examples. Ethics integrated throughout. Reproducibility integrated throughout. Focus on data gathering, messy data, and cleaning data. Extensive formative assessment throughout.

Download or read book Perspectives in Contemporary STEM Education Research written by Thomas Delahunty and published by Taylor & Francis. This book was released on 2022-10-13 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the methodological innovations and developments present in the field of STEM education research as well as providing a practically orientated resource on research method design more broadly. Featuring a range of international contributors in the field, the book provides a compendium of exemplary innovative methodological designs, implementations, and analyses that answer a variety of research questions relating to STEM education disciplines. Charting the thinking behind the design and implementation of successful research investigations, the book’s two parts present an accessible and pragmatically framed set of chapters that cover a range of important methodological areas presented by active researchers in the field. Ultimately, this book presents a comprehensive resource that explores the act of educational research as related to STEM. By showcasing key methodological principles with guidance on practical approaches underpinned by theory, the book offers scholarly research-informed suggestions for practice. It will be of great interest to researchers, academics, and students in the fields of STEM education and education research methods, as well as educational research more broadly.

Download or read book Model Management and Analytics for Large Scale Systems written by Bedir Tekinerdogan and published by Academic Press. This book was released on 2019-09-14 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. - Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics - Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics - Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions

Download or read book Transactions on Large Scale Data and Knowledge Centered Systems LVI written by Abdelkader Hameurlain and published by Springer Nature. This book was released on with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book International Large Scale Assessments in Education written by Bryan Maddox and published by Bloomsbury Publishing. This book was released on 2018-11-29 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the often controversial international large-scale assessments (ILSAs) in education and offers research-based accounts of international testing as a social practice. Assessment exercises, such as the Organisation for Economic Co-operation and Development's Programme for International Student Assessment (PISA), produce comparable international statistics and rankings on educational performance, and are influential practices that shape educational policy on a global scale. The chapters in this volume, written by expert researchers in the field, take the reader behind the scenes to document a broad range of ILSA practices – from the recruitment of countries into ILSAs, to the production and performance of large-scale testing, and the management, media reception and use of test data. Based on data that is only available to expert researchers with inside access, the international case study material includes examples from Australia, Ecuador, Germany, Japan, Mexico, Norway, Russia, Scotland, Slovenia, Sweden, the UK and the USA. The volume provides important insights for teachers, researchers and policy-makers who use and study assessment data and who wish to evaluate its significance for educational policy and practice.

Download or read book Large scale Graph Analysis System Algorithm and Optimization written by Yingxia Shao and published by Springer Nature. This book was released on 2020-07-01 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently. More concretely, it proposes a workload-aware cost model to guide the development of high-performance algorithms. On the basis of the cost model, the book subsequently presents a system-level optimization resulting in a partition-aware graph-computing engine, PAGE. In addition, it presents three efficient and scalable advanced graph algorithms – the subgraph enumeration, cohesive subgraph detection, and graph extraction algorithms. This book offers a valuable reference guide for junior researchers, covering the latest advances in large-scale graph analysis; and for senior researchers, sharing state-of-the-art solutions based on advanced graph algorithms. In addition, all readers will find a workload-aware methodology for designing efficient large-scale graph algorithms.

Download or read book Legal and ethical issues in the use of video in education research written by and published by DIANE Publishing. This book was released on with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Resources in Education written by and published by . This book was released on 1992-05 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multilevel Modeling Methods with Introductory and Advanced Applications written by Ann A. O'Connell and published by IAP. This book was released on 2022-03-01 with total page 645 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation. In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs. Each chapter contains a section called Try This!, which poses a structured data problem for the reader. We have linked our book to a website (http://modeling.uconn.edu) containing data for the Try This! section, creating an opportunity for readers to learn by doing. The inclusion of the Try This! problems, data, and sample code eases the burden for instructors, who must continually search for class examples and homework problems. In addition, each chapter provides recommendations for additional methodological and applied readings.

Download or read book A Machine Learning Artificial Intelligence Approach to Institutional Effectiveness in Higher Education written by John N. Moye Ph.D. and published by Emerald Group Publishing. This book was released on 2019-07-29 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a practical, effective, and systematic approach to the measurement, assessment, and sensemaking of institutional performance. Included are strategies to measure and assess the performance of Curriculum, Learning, Instruction, Support Services, and Program Feasibility as well as a meaningful Environmental Scanning method.

Download or read book Achieving Greater Educational Impact Through Data Intelligence Practice Challenges And Expectations Of Education written by Bian Wu and published by World Scientific. This book was released on 2021-11-24 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is data intelligence? How can data intelligence influence education system systematically? The paradigm shift of scientific research implies a coming age of data-driven educational research and practice. This book presents research and practice of data intelligence in education from three levels: (i) educational governance, (ii) teaching practice, and (iii) student learning. Each chapter gives an analysis of fundamental knowledge, key themes, the state-of-the-art technologies and education application cases. This interdisciplinary book is essential reading for anyone interested in applying big data technology in education and for different stakeholders including education administrators, teachers, students, and researchers to broaden their minds to wisely use educational data to solve complex problems in the education field.

Download or read book Big Data and Learning Analytics in Higher Education written by Ben Kei Daniel and published by Springer. This book was released on 2016-08-27 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.

Download or read book International Handbook of Comparative Large Scale Studies in Education written by Trude Nilsen and published by Springer Nature. This book was released on 2022-09-21 with total page 1518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is the first of its kind to provide a general and comprehensive overview of virtually every aspect of International Large Scale Assessment (ILSA). It includes historical, economic, and policy perspectives, theoretical foundations, methodology, and reviews of findings from analyses of ILSA data. After decades, during which ILSAs have generated knowledge within central areas of education research and gained increased and substantial impact on educational policy, practice and research, such a broad overview for a wide-ranging audience is much needed. With contributions from authors and editors from all continents, this handbook appeals to an international audience and keeps a neutral perspective, not favoring one ILSA over another. The handbook is suitable to be read by politicians, researchers and stakeholders who are seeking an overview of ILSAs, their history and development, and both potential benefits and limitations with regard to policy implications. The reviews of findings from studies analyzing ILSA data will be of interest to stakeholders, teachers, researchers, and policymakers. Considering that the reviews extend to all fields pertaining to educational research, the book will be valuable to all researchers interested in education. Students may use the book to learn about ILSAs in the context of policy, theoretical underpinnings, or research. Moreover, the methodology section is written in a manner that is understandable and accessible for students, stakeholders, or researchers not familiar with these data. This methodology part, however, is also a valuable resource for researchers who are familiar with ILSA data, as it provides overviews of the design and sampling procedures of several ILSAs, and includes advice on methods of analysis.Even the owners of the ILSAs may find the book valuable, as it contains overviews and insights into a number of ILSAs, provides information how the data is used by the research community, and includes recommendations for future instruments.