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Educational Data
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Book Synopsis How to Make Data Work by : Jenny Grant Rankin
Download or read book How to Make Data Work written by Jenny Grant Rankin and published by Routledge. This book was released on 2016-01-22 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Educators are increasingly responsible for using data to improve teaching and learning in their schools. This helpful guide provides leaders with simple steps for facilitating accurate analysis and interpretation of data, while avoiding common errors and pitfalls. How to Make Data Work provides clear strategies for getting data into workable shape and creating an environment that supports understanding, analysis, and successful use of data, no matter what data system or educational technology tools are in place in your district. This accessible resource makes data easy to understand and use so that educators can better evaluate and maximize their systems to help their staff, students, and school succeed. With this tried-and-true guidance, you’ll be prepared to advocate for tools that adhere to data reporting standards, avoid misinterpretation of data, and improve the data use climate in your school.
Book Synopsis Multilevel Modeling of Educational Data by : Ann A. O'Connell
Download or read book Multilevel Modeling of Educational Data written by Ann A. O'Connell and published by IAP. This book was released on 2008-04-01 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: (sponsored by the Educational Statisticians, SIG) Multilevel Modeling of Educational Data, co-edited by Ann A. O’Connell, Ed.D., and D. Betsy McCoach, Ph.D., is the next volume in the series: Quantitative Methods in Education and the Behavioral Sciences: Issues, Research and Teaching (Information Age Publishing), sponsored by the Educational Statisticians' Special Interest Group (Ed-Stat SIG) of the American Educational Research Association. The use of multilevel analyses to examine effects of groups or contexts on individual outcomes has burgeoned over the past few decades. Multilevel modeling techniques allow educational researchers to more appropriately model data that occur within multiple hierarchies (i.e.- the classroom, the school, and/or the district). Examples of multilevel research problems involving schools include establishing trajectories of academic achievement for children within diverse classrooms or schools or studying school-level characteristics on the incidence of bullying. Multilevel models provide an improvement over traditional single-level approaches to working with clustered or hierarchical data; however, multilevel data present complex and interesting methodological challenges for the applied education research community. In keeping with the pedagogical focus for this book series, the papers this volume emphasize applications of multilevel models using educational data, with chapter topics ranging from basic to advanced. This book represents a comprehensive and instructional resource text on multilevel modeling for quantitative researchers who plan to use multilevel techniques in their work, as well as for professors and students of quantitative methods courses focusing on multilevel analysis. Through the contributions of experienced researchers and teachers of multilevel modeling, this volume provides an accessible and practical treatment of methods appropriate for use in a first and/or second course in multilevel analysis. A supporting website links chapter examples to actual data, creating an opportunity for readers to reinforce their knowledge through hands-on data analysis. This book serves as a guide for designing multilevel studies and applying multilevel modeling techniques in educational and behavioral research, thus contributing to a better understanding of and solution for the challenges posed by multilevel systems and data.
Book Synopsis Data Science in Education Using R by : Ryan A. Estrellado
Download or read book Data Science in Education Using R written by Ryan A. Estrellado and published by Routledge. This book was released on 2020-10-26 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Book Synopsis Education Data Done Right by : Dorothyjean Cratty
Download or read book Education Data Done Right written by Dorothyjean Cratty and published by . This book was released on 2019-10-08 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lots of pundits and researchers have ideas about how education data work should be done and who should do it. Many of their ideas are disseminated widely. This book covers the things those books do not: metadata, working with enterprise IT, data requests, politics, and why descriptive statistics can take you far.
Book Synopsis The K-12 Educator’s Data Guidebook by : Ryan A. Estrellado
Download or read book The K-12 Educator’s Data Guidebook written by Ryan A. Estrellado and published by Taylor & Francis. This book was released on 2022-03-21 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The K-12 Educator’s Data Guidebook is a comprehensive field guide for school professionals learning to use data. “Non-data people,” rejoice! Requiring no prior proficiency in data tools and programming, this book validates the implicit challenges of learning to use data to empower educators and features original real-world examples from in-service educators to illustrate common problem-solving. Each chapter uses stories, humor, and a human approach to set the tone for a safe and fun learning experience. Through this highly practical foundation, everyday educators can better engage school initiatives, professional development, and instructional challenges that require competent data use for improving school systems.
Book Synopsis Handbook of Educational Data Mining by : Cristobal Romero
Download or read book Handbook of Educational Data Mining written by Cristobal Romero and published by CRC Press. This book was released on 2010-10-25 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. Researchers at the Forefront of the Field Discuss Essential Topics and the Latest Advances With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It brings the educational and data mining communities together, helping education experts understand what types of questions EDM can address and helping data miners understand what types of questions are important to educational design and educational decision making. Encouraging readers to integrate EDM into their research and practice, this timely handbook offers a broad, accessible treatment of essential EDM techniques and applications. It provides an excellent first step for newcomers to the EDM community and for active researchers to keep abreast of recent developments in the field.
Book Synopsis Educational Data Mining by : Alejandro Peña-Ayala
Download or read book Educational Data Mining written by Alejandro Peña-Ayala and published by Springer. This book was released on 2013-11-08 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education. · Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click. · Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data. · Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks. This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledge and find targets for future work in the field of educational data mining.
Book Synopsis The Data-Driven School by : Daniel M. Hyson
Download or read book The Data-Driven School written by Daniel M. Hyson and published by Guilford Publications. This book was released on 2020-05-06 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This indispensable practitioner's guide helps to build the capacity of school psychologists, administrators, and teachers to use data in collaborative decision making. It presents an applied, step-by-step approach for creating and running effective data teams within a problem-solving framework. The authors describe innovative ways to improve academic and behavioral outcomes at the individual, class, grade, school, and district levels. Applications of readily available technology tools are highlighted. In a large-size format for easy photocopying, the book includes learning activities and helpful reproducible forms. The companion website provides downloadable copies of the reproducible forms as well as Excel spreadsheets, PowerPoint slides, and an online-only chapter on characteristics of effective teams. This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas.
Book Synopsis Quantitative Data Analysis in Education by : Paul Connolly
Download or read book Quantitative Data Analysis in Education written by Paul Connolly and published by Routledge. This book was released on 2007-08-07 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a refreshing and user-friendly guide to quantitative data analysis in education for students and researchers. It assumes absolutely no prior knowledge of quantitative methods or statistics. Beginning with the very basics, it provides the reader with the knowledge and skills necessary to be able to undertake routine quantitative data analysis to a level expected of published research. Rather than focusing on teaching statistics through mathematical formulae, the book places an emphasis on using SPSS to gain a real feel for the data and an intuitive grasp of the main concepts and techniques involved. Drawing extensively upon up-to-date and relevant examples, the reader will be encouraged to think critically about quantitative research and its potential as well as its limitations in relation to education. Packed with helpful features, this book: provides illustrated step-by-step guides showing how to use SPSS, with plenty of exercises to encourage the reader to practice and consolidate their new skills makes extensive use of real-life educational datasets derived from national surveys in the US and UK to illustrate key points and to bring the material to life has a companion website that contains all of the educational datasets used in the book to download as well as comprehensive answers to exercises and a range of other useful resources that are regularly updated. The book will therefore appeal not only to undergraduate and postgraduate students but also to more established and seasoned educational researchers and lecturers and professors who have tended to avoid or shy away from quantitative methods.
Book Synopsis Using Data to Improve Teacher Education by : Charles A. Peck
Download or read book Using Data to Improve Teacher Education written by Charles A. Peck and published by . This book was released on 2021 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A collaborative effort between researchers and practitioners, this volume presents lessons learned to assist teacher educators who are engaged daily with the challenges of making data useful and used in their programs. Readers will see how the work carried out in "high data use" teacher education programs strengthened local program identity and coherence"--
Book Synopsis Schools and Data by : Theodore B. Creighton
Download or read book Schools and Data written by Theodore B. Creighton and published by Corwin Press. This book was released on 2006-07-06 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve instructional leadership practice with proven, easy-to-understand strategies for data-based decision making! This reader-friendly second edition of Schools and Data provides real-world examples and step-by-step procedures for collecting and organizing data, providing every school leader with the means to facilitate more appropriate and effective decision making. With a highly practical method for statistical analysis, this highly accessible resource places special emphasis on: Connecting statistics and educators’ daily work Integrating Excel and SPSS technology Strengthening educators’ data interpretation skills Increasing the focus on correlation and regression Building strong skills in problem analysis, program evaluation, data-driven decision making, and report preparation
Book Synopsis Adoption of Data Analytics in Higher Education Learning and Teaching by : Dirk Ifenthaler
Download or read book Adoption of Data Analytics in Higher Education Learning and Teaching written by Dirk Ifenthaler and published by Springer Nature. This book was released on 2020-08-10 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.
Download or read book Street Data written by Shane Safir and published by Corwin. This book was released on 2021-02-12 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radically reimagine our ways of being, learning, and doing Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the student up—with classrooms, schools and systems built around students’ brilliance, cultural wealth, and intellectual potential. Street data reminds us that what is measurable is not the same as what is valuable and that data can be humanizing, liberatory and healing. By breaking down street data fundamentals: what it is, how to gather it, and how it can complement other forms of data to guide a school or district’s equity journey, Safir and Dugan offer an actionable framework for school transformation. Written for educators and policymakers, this book · Offers fresh ideas and innovative tools to apply immediately · Provides an asset-based model to help educators look for what’s right in our students and communities instead of seeking what’s wrong · Explores a different application of data, from its capacity to help us diagnose root causes of inequity, to its potential to transform learning, and its power to reshape adult culture Now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.
Book Synopsis Data-based Decision Making in Education by : Kim Schildkamp
Download or read book Data-based Decision Making in Education written by Kim Schildkamp and published by Springer Science & Business Media. This book was released on 2012-09-18 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students’ assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are ‘best practice’ studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.
Book Synopsis Big Data in Education by : Ben Williamson
Download or read book Big Data in Education written by Ben Williamson and published by SAGE. This book was released on 2017-07-24 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Literacy for Educators by : Ellen B. Mandinach
Download or read book Data Literacy for Educators written by Ellen B. Mandinach and published by Teachers College Press. This book was released on 2016 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data literacy has become an essential skill set for teachers as education becomes more of an evidence-based profession. Teachers in all stages of professional growth need to learn how to use data effectively and responsibly to inform their teaching practices. This groundbreaking resource describes data literacy for teaching, emphasizing the important relationship between data knowledge and skills and disciplinary and pedagogical content knowledge. Case studies of emerging programs in schools of education are used to illustrate the key components needed to integrate data-driven decisionmaking into the teaching curricula. The book offers a clear path for change while also addressing the inherent complexities associated with change. Data Literacy for Educators provides concrete strategies for schools of education, professional developers, and school districts. Book Features: Defines data literacy for teaching and outlines the knowledge and skills it comprises. Uses examples and case studies that tie theory to practice. Provides a roadmap for integrating data literacy into teacher preparation programs. Covers emerging trends, such as virtual and hybrid courses and massive open online courses. “This thoughtful, well-organized book raises the challenges that beginning and experienced teachers face in becoming more data literate to increase their pedagogical effectiveness in their classrooms.” —From the Foreword by Barbara Schneider “Deans of colleges of education, practicing teachers, education advocates, and many others will find useful information here.” —Benjamin Riley, Deans for Impact “This work should join the ‘common core’ of teacher education and professional development programs.” —Lee S. Shulman, The Carnegie Foundation for the Advancement of Teaching “The authors lay out a compelling call to action to ensure that every teacher in this country has the skills, knowledge, and disposition in knowing how to use data to inform effective teaching.” —Aimee Rogstad Guidera, Data Quality Campaign
Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton
Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
