Author: Carter Alexander
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 476
Book Description
How to Make Data Work
Author: Jenny Grant Rankin
Publisher: Routledge
ISBN: 1317353382
Category : Education
Languages : en
Pages : 163
Book Description
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.
Publisher: Routledge
ISBN: 1317353382
Category : Education
Languages : en
Pages : 163
Book Description
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.
How to Locate Educational Information and Data
Author: Carter Alexander
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 476
Book Description
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 476
Book Description
Street Data
Author: Shane Safir
Publisher: Corwin
ISBN: 1071812661
Category : Education
Languages : en
Pages : 281
Book Description
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.
Publisher: Corwin
ISBN: 1071812661
Category : Education
Languages : en
Pages : 281
Book Description
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.
Educational Data Mining
Author: Alejandro Peña-Ayala
Publisher: Springer
ISBN: 3319027387
Category : Technology & Engineering
Languages : en
Pages : 477
Book Description
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.
Publisher: Springer
ISBN: 3319027387
Category : Technology & Engineering
Languages : en
Pages : 477
Book Description
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.
Handbook of Information Sources in Education and the Behavioral Sciences
Author: Jesse L. Gates
Publisher:
ISBN:
Category : Bibliographical centers
Languages : en
Pages : 206
Book Description
Publisher:
ISBN:
Category : Bibliographical centers
Languages : en
Pages : 206
Book Description
The Datafication of Education
Author: Juliane Jarke
Publisher: Routledge
ISBN: 100068296X
Category : Computers
Languages : en
Pages : 189
Book Description
This book attends to the transformation of processes and practices in education, relating to its increasing digitisation and datafication. The introduction of new means to measure, capture, describe and represent social life in numbers has not only transformed the ways in which teaching and learning are organised, but also the ways in which future generations (will) construct reality with and through data. Contributions consider data practices that span across different countries, educational fields and governance levels, ranging from early childhood education, to schools, universities, educational technology providers, to educational policy making and governance. The book demonstrates how digital data not only support decision making, but also fundamentally change the organisation of learning and teaching, and how these transformation processes can have partly ambivalent consequences, such as new possibilities for participation, but also the monitoring and emergence/manifestation of inequalities. Focusing on how data can drive decision making in education and learning, this book will be of interest to those studying both educational technology and educational policy making. The chapters in this book were originally published in Learning, Media and Technology. Chapter 4 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Publisher: Routledge
ISBN: 100068296X
Category : Computers
Languages : en
Pages : 189
Book Description
This book attends to the transformation of processes and practices in education, relating to its increasing digitisation and datafication. The introduction of new means to measure, capture, describe and represent social life in numbers has not only transformed the ways in which teaching and learning are organised, but also the ways in which future generations (will) construct reality with and through data. Contributions consider data practices that span across different countries, educational fields and governance levels, ranging from early childhood education, to schools, universities, educational technology providers, to educational policy making and governance. The book demonstrates how digital data not only support decision making, but also fundamentally change the organisation of learning and teaching, and how these transformation processes can have partly ambivalent consequences, such as new possibilities for participation, but also the monitoring and emergence/manifestation of inequalities. Focusing on how data can drive decision making in education and learning, this book will be of interest to those studying both educational technology and educational policy making. The chapters in this book were originally published in Learning, Media and Technology. Chapter 4 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Big Data in Education
Author: Ben Williamson
Publisher: SAGE
ISBN: 1526416328
Category : Education
Languages : en
Pages : 281
Book Description
Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
Publisher: SAGE
ISBN: 1526416328
Category : Education
Languages : en
Pages : 281
Book Description
Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
OE [publication]
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 572
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 572
Book Description
Resources in Education
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 312
Book Description
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 312
Book Description
Library Data
Author: Darby Orcutt
Publisher: Bloomsbury Publishing USA
ISBN: 1591588278
Category : Language Arts & Disciplines
Languages : en
Pages : 313
Book Description
Numerical evidence is everywhere and how best to handle and leverage it is a growing concern in the academic world in general and the academic library world in particular. Libraries are not only storehouses and key contacts for library patrons in accessing numbers, but are also collectors and users of their own data, which is integral to the functioning of the library itself. The essays in Library Data: Empowering Practice and Persuasion focus on interpreting and using library-generated and outside data in support of data-driven practice and data-strengthened persuasion. The collection includes such topics as how to make data presentations appealing and effective; applying capital-budgeting models to libraries; and using data for evaluation and improvement of collections and services. Articles also cover specialized scenarios, including reference, collection development, serial acquisitions, institutional repositories, web site design, interlibrary loan, and bibliographic instruction.
Publisher: Bloomsbury Publishing USA
ISBN: 1591588278
Category : Language Arts & Disciplines
Languages : en
Pages : 313
Book Description
Numerical evidence is everywhere and how best to handle and leverage it is a growing concern in the academic world in general and the academic library world in particular. Libraries are not only storehouses and key contacts for library patrons in accessing numbers, but are also collectors and users of their own data, which is integral to the functioning of the library itself. The essays in Library Data: Empowering Practice and Persuasion focus on interpreting and using library-generated and outside data in support of data-driven practice and data-strengthened persuasion. The collection includes such topics as how to make data presentations appealing and effective; applying capital-budgeting models to libraries; and using data for evaluation and improvement of collections and services. Articles also cover specialized scenarios, including reference, collection development, serial acquisitions, institutional repositories, web site design, interlibrary loan, and bibliographic instruction.