Data Management In Large Scale Education Research Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Data Management In Large Scale Education Research book. This book definitely worth reading, it is an incredibly well-written.
Data Management in Large-Scale Education Research by Crystal Lewis Pdf
This book is for those involved in a research study involving original data collection. Whilst it focuses on quantitative data, collected from human participants, many of the practices covered apply to other types of data. It contains foundational context, instructions, and examples.
Data Management in Large-Scale Education Research by Crystal Lewis Pdf
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
Data Management and Analysis by Reda Alhajj,Mohammad Moshirpour,Behrouz Far Pdf
Data management and analysis is one of the fastest growing and most challenging areas of research and development in both academia and industry. Numerous types of applications and services have been studied and re-examined in this field resulting in this edited volume which includes chapters on effective approaches for dealing with the inherent complexity within data management and analysis. This edited volume contains practical case studies, and will appeal to students, researchers and professionals working in data management and analysis in the business, education, healthcare, and bioinformatics areas.
Petra Lietz,John C. Cresswell,Keith F. Rust,Raymond J. Adams
Author : Petra Lietz,John C. Cresswell,Keith F. Rust,Raymond J. Adams Publisher : John Wiley & Sons Page : 466 pages File Size : 45,9 Mb Release : 2017-04-24 Category : Mathematics ISBN : 9781118336090
Implementation of Large-Scale Education Assessments by Petra Lietz,John C. Cresswell,Keith F. Rust,Raymond J. Adams Pdf
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.
Big Data in Education: Pedagogy and Research by Theodosia Prodromou Pdf
This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications.
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.
Perspectives in Contemporary STEM Education Research by Thomas Delahunty,Máire Ní Ríordáin Pdf
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.
This cutting-edge overview explores big data and the related topic of computer code, examining the implications for education and schooling for today and the near future.
Leading Schools in a Data-Rich World by Lorna M. Earl,Steven Katz Pdf
Turn skepticism about data into knowledge for true educational reform! More versatile than mere number crunching and statistics, data can be an effective tool—or even a powerful catalyst—for change within a school. Lorna M. Earl and Steven Katz show educators how to become comfortable with data, and provide valuable tools that school leaders and school improvement teams can use in their work, including: Vignettes to support group discussion Activities to give readers a chance to practice ideas and concepts Task sheets Short case studies that show how the full process works
Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management by Kosar, Tevfik Pdf
"This book focuses on the challenges of distributed systems imposed by the data intensive applications, and on the different state-of-the-art solutions proposed to overcome these challenges"--Provided by publisher.
International Large-Scale Assessments in Education by Bryan Maddox Pdf
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.
Teaching Research Data Management by Julia Bauder Pdf
Armed with this guide's strategies and concrete examples, subject librarians, data services librarians, and scholarly communication librarians will be inspired to roll up their sleeves and get involved with teaching research data management competencies to students and faculty. The usefulness of research data management skills bridges numerous activities, from data-driven scholarship and open research by faculty to documentation for grant reporting. And undergrads need a solid foundation in data management for future academic success. This collection gathers practitioners from a broad range of academic libraries to describe their services and instruction around research data. You will learn about such topics as integrating research data management into information literacy instruction; threshold concepts for novice learners of data management; four key competencies that are entry points for library-faculty collaboration in data instruction; an 8-step plan for outreach to faculty and grad students in engineering and the sciences; using RStudio to teach data management, data visualization, and research reproducibility; expanding data management instruction with adaptable modules for remote learning; designing a data management workshop series; developing a research guide on data types, open data repositories, and data storage; creating a data management plan assignment for STEM undergraduates; and data management training to ensure compliance with grant requirements.
Facilitator's Guide to Leading Schools in a Data-Rich World by Lorna M. Earl,Steven Katz,Sonia Ben Jaafar Pdf
Designed around the bestseller by Lorna M. Earl and Steven Katz, this Facilitator's Guide to Leading Schools in a Data-Rich World gives staff developers and workshop leaders the tools to facilitate book study groups, seminars, and professional development events to help school leaders integrate data as a vital force in the school reform process. This facilitator's guide features chapter summaries, discussion questions, journal prompts, staff development activities, resources, a seminar evaluation form, and more.
Large-scale Graph Analysis: System, Algorithm and Optimization by Yingxia Shao,Bin Cui,Lei Chen Pdf
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.
