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Data For Learning

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Data For Learning

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Author : Husein Abdul-Hamid
language : en
Publisher: World Bank Publications
Release Date : 2017-09-21

Data For Learning written by Husein Abdul-Hamid and has been published by World Bank Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-21 with Education categories.

Data are a crucial ingredient in any successful education system, but building and sustaining a data system are challenging tasks. Many countries around the world have spent significant resources but still struggle to accomplish a functioning Education Management Information System (EMIS). On the other hand, countries that have created successful systems are harnessing the power of data to improve education outcomes. Increasingly, EMISs are moving away from using data narrowly for counting students and schools. Instead, they use data to drive system-wide innovations, accountability, professionalization, and, most important, quality and learning. This broader use of data also benefits classroom instruction and support at schools. An effective data system ensures that education cycles, from preschool to tertiary, are aligned and that the education system is monitored so it can achieve its ultimate goal—producing graduates able to successfully transition into the labor market and contribute to the overall national economy. Data for Learning: Building a Smart Education Data System and its forthcoming companion volume shed light on challenges in building a data system and provide actionable direction on how to navigate the complex issues associated with education data for better learning outcomes and beyond. Data for Learning details the key ingredients of successful data systems, including tangible examples, common pitfalls, and good practices. It is a resource for policy makers working to craft the vision and strategic road map of an EMIS, as well as a handbook to assist teams and decision makers in avoiding common mistakes. It is designed to provide the “how-to†? and to guide countries at various stages of EMIS deployment. A forthcoming companion volume will focus on digging deeper into the practical applications of education data systems by various user groups in different settings.

Advancing The Power Of Learning Analytics And Big Data In Education

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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2021-03-19

Advancing The Power Of Learning Analytics And Big Data In Education written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-19 with Education categories.

The term learning analytics is used in the context of the use of analytics in e-learning environments. Learning analytics is used to improve quality. It uses data about students and their activities to provide better understanding and to improve student learning. The use of learning management systems, where the activity of the students can be easily accessed, potentiated the use of learning analytics to understand their route during the learning process, help students be aware of their progress, and detect situations where students can give up the course before its completion, which is a growing problem in e-learning environments. Advancing the Power of Learning Analytics and Big Data in Education provides insights concerning the use of learning analytics, the role and impact of analytics on education, and how learning analytics are designed, employed, and assessed. The chapters will discuss factors affecting learning analytics such as human factors, geographical factors, technological factors, and ethical and legal factors. This book is ideal for teachers, administrators, teacher educators, practitioners, stakeholders, researchers, academicians, and students interested in the use of big data and learning analytics for improved student success and educational environments.

Big Data And Learning Analytics In Higher Education

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Author : Ben Kei Daniel
language : en
Publisher: Springer
Release Date : 2018-04-21

Big Data And Learning Analytics In Higher Education written by Ben Kei Daniel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-21 with Education categories.

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.

Open Data For Education

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Author : Dmitry Mouromtsev
language : en
Publisher: Springer
Release Date : 2016-03-18

Open Data For Education written by Dmitry Mouromtsev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-18 with Computers categories.

This volume comprises a collection of papers presented at an Open Data in Education Seminar and the LILE workshops during 2014-2015. In the first part of the book, two chapters give different perspectives on the current use of linked and open data in education, including the use of technology and the topics that are being covered. The second part of the book focuses on the specific, practical applications that are being put in place to exploit open and linked data in education today. The goal of this book is to provide a snapshot of current activities, and to share and disseminate the growing collective experience on open and linked data in education. This volume brings together research results, studies, and practical endeavors from initiatives spread across several countries around the world. These initiatives are laying the foundations of open and linked data in the education movement and leading the way through innovative applications.

Learning With Big Data

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Author : Viktor Mayer-Schönberger
language : en
Publisher: HarperCollins
Release Date : 2014-03-04

Learning With Big Data written by Viktor Mayer-Schönberger and has been published by HarperCollins this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-04 with Education categories.

Homework assignments that learn from students. Courses tailored to fit individual pupils. Textbooks that talk back. This is tomorrow’s education landscape, thanks to the power of big data. These advances go beyond online courses. As the New York Times-bestselling authors of Big Data explain, the truly fascinating changes are actually occurring in how we measure students’ progress and how we can use that data to improve education for everyone, in real time, both on- and offline. Learning with Big Data offers an eye-opening, insight-packed tour through these new trends, for educators, administrators, and readers interested in the latest developments in business and technology.

Big Data And Learning Analytics In Higher Education

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Author : Ben Kei Daniel
language : en
Publisher: Springer
Release Date : 2016-08-27

Using Data To Improve Learning For All

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Author : Nancy Love
language : en
Publisher: Corwin Press
Release Date : 2009

Using Data To Improve Learning For All written by Nancy Love and has been published by Corwin Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Education categories.

Collaborative inquiry + effective use of data = significant leaps in learning and achievement! This resource combines a powerful collaborative inquiry process, reflective dialogue, and rigorous use of data to improve outcomes for all students. The editor and contributors provide detailed examples of schools that have demonstrated dramatic gains by building collaborative cultures, nurturing ongoing inquiry, and using data systematically. The book shows school leaders how to: Implement collaborative inquiry to meet accountability mandates Build and support a high-performing data culture Establish a school climate characterized by collective responsibility for student learning and a respect for students’ cultures

Big Data In Education

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Author : Ben Williamson
language : en
Publisher: SAGE
Release Date : 2017-07-24

Big Data In Education written by Ben Williamson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-24 with Education categories.

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!

Big Data In Education Pedagogy And Research

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Author : Theodosia Prodromou
language : en
Publisher: Springer Nature
Release Date : 2021-10-04

Big Data In Education Pedagogy And Research written by Theodosia Prodromou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-04 with Education categories.

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.

Machine Learning And Data Science Blueprints For Finance

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Author : Hariom Tatsat
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-10-01

Machine Learning And Data Science Blueprints For Finance written by Hariom Tatsat and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-01 with Computers categories.

Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Data For Learning

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