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| big data in education: Big Data in Education Ben Williamson, 2017-07-24 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: Big Data in Education: Pedagogy and Research Theodosia Prodromou, 2021-10-04 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. |
| big data in education: Big Data on Campus Karen L. Webber, Henry Y. Zheng, 2020-11-03 Webber, Henry Y. Zheng, Ying Zhou |
| big data in education: Big Data and Learning Analytics in Higher Education Ben Kei Daniel, 2016-08-27 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. |
| big data in education: Learning With Big Data Viktor Mayer-Schönberger, Kenneth Cukier, 2014-03-04 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 in education: Advancing the Power of Learning Analytics and Big Data in Education Azevedo, Ana, Azevedo, José Manuel, Onohuome Uhomoibhi, James, Ossiannilsson, Ebba, 2021-03-19 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 in education: Data Science in Education Using R Ryan A. Estrellado, Emily Freer, Joshua M. Rosenberg, Isabella C. Velásquez, 2020-10-26 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. |
| big data in education: Big Data-Enabled Nursing Connie W. Delaney, Charlotte A. Weaver, Judith J. Warren, Thomas R. Clancy, Roy L. Simpson, 2017-11-02 Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. |
| big data in education: Digital Disruption in Teaching and Testing Claire Wyatt-Smith, Bob Lingard, Elizabeth Heck, 2021-04-28 This book provides a significant contribution to the increasing conversation concerning the place of big data in education. Offering a multidisciplinary approach with a diversity of perspectives from international scholars and industry experts, chapter authors engage in both research- and industry-informed discussions and analyses on the place of big data in education, particularly as it pertains to large-scale and ongoing assessment practices moving into the digital space. This volume offers an innovative, practical, and international view of the future of current opportunities and challenges in education and the place of assessment in this context. |
| big data in education: Data Mining and Learning Analytics Samira ElAtia, Donald Ipperciel, Osmar R. Zaïane, 2016-09-20 Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research. |
| big data in education: Data Science and Big Data Analytics EMC Education Services, 2014-12-19 Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today! |
| big data in education: Big Data Viktor Mayer-Schönberger, Kenneth Cukier, 2013 A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large. |
| big data in education: Big Data and Analytics Vincenzo Morabito, 2015-01-31 This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners can use the book as a toolbox to improve understanding and exploit business opportunities related to Big Data and analytics. |
| big data in education: Big Data for Twenty-First-Century Economic Statistics Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, Matthew D. Shapiro, 2022-03-11 Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra. |
| big data in education: Applications of Big Data in Large- and Small-Scale Systems Goundar, Sam, Rayani, Praveen Kumar, 2021-01-15 With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems. |
| big data in education: The Datafication of Education Juliane Jarke, Andreas Breiter, 2020-05-21 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: Research Anthology on Big Data Analytics, Architectures, and Applications Information Resources Management Association, 2022 Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians. |
| big data in education: The Educational Intelligent Economy Tavis D. Jules, Florin D. Salajan, 2019-11-25 This book examines, from a comparative perspective, the impact of the movement from the so-called knowledge-based economy towards the Intelligent Economy, which is premised upon the application of knowledge. This volume links the advent of this new technological revolution to the world of governance and policy formulation in education. |
| big data in education: Radical Solutions and Learning Analytics Daniel Burgos, 2020-05-08 Learning Analytics become the key for Personalised Learning and Teaching thanks to the storage, categorisation and smart retrieval of Big Data. Thousands of user data can be tracked online via Learning Management Systems, instant messaging channels, social networks and other ways of communication. Always with the explicit authorisation from the end user, being a student, a teacher, a manager or a persona in a different role, an instructional designer can design a way to produce a practical dashboard that helps him improve that very user’s performance, interaction, motivation or just grading. This book provides a thorough approach on how education, as such, from teaching to learning through management, is improved by a smart analysis of available data, making visible and useful behaviours, predictions and patterns that are hinder to the regular eye without the process of massive data. |
| big data in education: Big Data MBA Bill Schmarzo, 2015-12-11 Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions. |
| big data in education: Current Achievements, Challenges and Digital Chances of Knowledge Based Economy Svetlana Igorevna Ashmarina, Valentina Vyacheslavovna Mantulenko, 2020-05-29 This book is based on research from Russia, Hungary, Bulgaria, Great Britain, Switzerland and the Czech Republic on issues related to knowledge-based economy development. The idea for this book was developed during three international conferences on digitalization: VI, VII and VIII International Scientific Weeks, organized by Samara State University of Economics (Samara, Russia) in 2018–2020. It is an initiative by the scientific and business organizations in the Samara Region and their Russian and international partners to analyze the current digitalization of social-economic systems, the problems and perspectives of this process, and its role in the creation and development of a new type of economy and new quality of human capital. All the contributions focus on the search for effective ways of adapting to the new digital reality and are based analyses of international statistics, and data from specific companies, educational institutions and governmental development programs. The book explores a variety of topics, including • Knowledge and Information as Basic Values of a New Economic Paradigm; • Information Technologies for Ensuring Sustainable Development of Organizations; • Augmented Reality, Artificial Intelligence and Big Data in Education and Business; • Digital Platforms and the Sharing Economy; • Potential of Digital Footprints in Economies and Education; • Sociocultural Consequences of Digitalization. |
| big data in education: Digital Solutions and the Case for Africa’s Sustainable Development Maake, Albert Ong'uti, Maake, Benard Magara, Awuor, Fredrick Mzee, 2020-11-20 African economies can benefit tremendously from the new wave of digital innovation and information technology by using it to build and maintain sustainable systems. However, the gap in the theory and practice of providing these solutions remains poorly understood and difficult to fill. Only by addressing this gap head-on can it be traversed to the greater benefit of African citizens. Digital Solutions and the Case for Africa’s Sustainable Development is a pivotal reference source that presents existing technologies and their relevant solutions and further inspires inventions and innovation to provide sustainable solutions to African problems. Highlighting a wide range of topics including artificial intelligence, cryptocurrency, and digital identity, this book is ideally designed for government officials, public officials, computer engineers, economists, IT specialists, entrepreneurs, researchers, academicians, and students. |
| big data in education: Technology-Supported Teaching and Research Methods for Educators Makewa, Lazarus Ndiku, Ngussa, Baraka Manjale, Kuboja, Joshua Michael, 2018-09-28 Technology can be a powerful tool for transforming learning. It can help affirm and advance relationships between educators and students, reinvent approaches to learning and collaboration, shrink long-standing equity and accessibility gaps, and adapt learning experiences to meet the needs of all learners. Technology-Supported Teaching and Research Methods for Educators provides innovative insights into the utilization and maintenance of technology-supported teaching and research methods for educators. The content within this publication represents the work of e-learning, digital technologies, and current issues and trends in the field of teaching and learning in the context of contemporary technologies. It is a vital reference source for school educators, professionals, school administrators, academicians, researchers, and graduate-level students seeking coverage on topics centered on the integration of effective technologies that will support educators and students. |
| big data in education: Powering a Learning Society During an Age of Disruption Sungsup Ra, Shanti Jagannathan, Rupert Maclean, 2021-05-22 This open access book presents contemporary perspectives on the role of a learning society from the lens of leading practitioners, experts from universities, governments, and industry leaders. The think pieces argue for a learning society as a major driver of change with far-reaching influence on learning to serve the needs of economies and societies. The book is a testimonial to the importance of ‘learning communities.’ It highlights the pivotal role that can be played by non-traditional actors such as city and urban planners, citizens, transport professionals, and technology companies. This collection seeks to contribute to the discourse on strengthening the fabric of a learning society crucial for future economic and social development, particularly in the aftermath of the coronavirus disease. |
| big data in education: Building a Smarter University Jason E. Lane, 2014-09-30 The Big Data movement and the renewed focus on data analytics are transforming everything from healthcare delivery systems to the way cities deliver services to residents. Now is the time to examine how this Big Data could help build smarter universities. While much of the cutting-edge research that is being done with Big Data is happening at colleges and universities, higher education has yet to turn the digital mirror on itself to advance the academic enterprise. Institutions can use the huge amounts of data being generated to improve the student learning experience, enhance research initiatives, support effective community outreach, and develop campus infrastructure. This volume focuses on three primary themes related to creating a smarter university: refining the operations and management of higher education institutions, cultivating the education pipeline, and educating the next generation of data scientists. Through an analysis of these issues, the contributors address how universities can foster innovation and ingenuity in the academy. They also provide scholarly and practical insights in order to frame these topics for an international discussion. |
| big data in education: OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots OECD, 2021-06-08 How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems. |
| big data in education: Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing Singh, Amandeep, 2021-06-18 The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies. |
| big data in education: Applied Degree Education and the Future of Work Christina Hong, Will W. K. Ma, 2020-05-16 This edited volume sets the stage for discussion on Education 4.0, with a focus on applied degree education and the future of work. Education 4.0 refers to the shifts in the education sector in response to Industry 4.0 where digital transformation is impacting the ways in which the world of work and our everyday lives are becoming increasingly automated. In the applied degree sector, significant change and transformation is occurring as leaders, educators and partners evolve smart campus environments to include blended learning, artificial intelligence, data analytics, BYOD devices, process automation and engage in curriculum renewal for and with industries and professions. This volume aims to profile and enhance the contribution of applied educational practice and research particularly in the applied degree sector and includes contributions that show case real world outcomes with students and industry as partners. This edited volume includes a wide range of topics, such as rethinking the role of education and educators; curriculum and the future of work; industrial partnership, collaboration and work integrated learning; vocational and professional practices; students, industry and professions as partners; employability skills and qualities for the 21st century world of work; innovative pedagogy and instructional design; adaptive learning technologies; and data analytics, assessment and feedback. The contributors come from different parts of the world in higher education, including, Canada, China, Finland, Germany, Hong Kong, Italy, Macau, Singapore and the United Kingdom. |
| big data in education: Street Data Shane Safir, Jamila Dugan, 2021-02-12 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. |
| big data in education: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| big data in education: Big Data: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2016-04-20 The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics. |
| big data in education: Driven by Data Paul Bambrick-Santoyo, 2010-04-12 Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD. |
| big data in education: Handbook of Research on Big Data, Green Growth, and Technology Disruption in Asian Companies and Societies Patricia Ordóñez de Pablos, Xi Zhang, Mohammad Nabil Almunawar, Jose Emilio Labra Gayo, 2021-10-23 This book offers an international platform to bring together academics, researchers, lecturers, decision makers, policy makers, and practitioners to share new theories, research findings, and case studies, to enhance understanding and collaboration in business, digital strategies, disruptive innovation, green growth, and technology in Asia-- |
| big data in education: Global Approaches to Sustainability Through Learning and Education Al-Sartawi, Abdalmuttaleb M.A. Musleh, Hussainey, Khaled, Hannoon, Azzam, Hamdan, Allam, 2019-08-30 Unequal distribution of wealth, poverty, pollution, and gender inequality are just a few of the problems we face and struggle to eliminate. Sustainable development offers a long-term holistic solution to these problems through meeting the needs of the current generation without endangering the capability of future generations in meeting their own needs. Sustainable education or education for sustainability is a transformative learning paradigm that prepares learners and provides them with knowledge, ethical awareness, skills, values, and attitudes to achieve sustainable goals. Global Approaches to Sustainability Through Learning and Education is a comprehensive academic publication that facilitates a greater understanding of sustainable development and fosters a culture of sustainability through learning and education. Highlighting a range of topics such as ethics, game-based learning, and knowledge management, this book is ideal for teachers, environmentalists, higher education faculty, activists, curriculum developers, academicians, researchers, professionals, administrators, and policymakers. |
| big data in education: The Transformation of Title IX R. Shep Melnick, 2018-03-06 One civil rights-era law has reshaped American society—and contributed to the country's ongoing culture wars Few laws have had such far-reaching impact as Title IX of the Education Amendments of 1972. Intended to give girls and women greater access to sports programs and other courses of study in schools and colleges, the law has since been used by judges and agencies to expand a wide range of antidiscrimination policies—most recently the Obama administration’s 2016 mandates on sexual harassment and transgender rights. In this comprehensive review of how Title IX has been implemented, Boston College political science professor R. Shep Melnick analyzes how interpretations of equal educational opportunity have changed over the years. In terms accessible to non-lawyers, Melnick examines how Title IX has become a central part of legal and political campaigns to correct gender stereotypes, not only in academic settings but in society at large. Title IX thus has become a major factor in America's culture wars—and almost certainly will remain so for years to come. |
| big data in education: Smart Sensors at the IoT Frontier Hiroto Yasuura, Chong-Min Kyung, Yongpan Liu, Youn-Long Lin, 2017-05-29 This book describes technology used for effective sensing of our physical world and intelligent processing techniques for sensed information, which are essential to the success of Internet of Things (IoT). The authors provide a multidisciplinary view of sensor technology from materials, process, circuits, to big data domains and they showcase smart sensor systems in real applications including smart home, transportation, medical, environmental, agricultural, etc. Unlike earlier books on sensors, this book provides a “global” view on smart sensors covering abstraction levels from device, circuit, systems, and algorithms. |
| big data in education: Algorithms of Education Kalervo N. Gulson, Sam Sellar, P. Taylor Webb, 2022-05-17 A critique of what lies behind the use of data in contemporary education policy While the science fiction tales of artificial intelligence eclipsing humanity are still very much fantasies, in Algorithms of Education the authors tell real stories of how algorithms and machines are transforming education governance, providing a fascinating discussion and critique of data and its role in education policy. Algorithms of Education explores how, for policy makers, today’s ever-growing amount of data creates the illusion of greater control over the educational futures of students and the work of school leaders and teachers. In fact, the increased datafication of education, the authors argue, offers less and less control, as algorithms and artificial intelligence further abstract the educational experience and distance policy makers from teaching and learning. Focusing on the changing conditions for education policy and governance, Algorithms of Education proposes that schools and governments are increasingly turning to “synthetic governance”—a governance where what is human and machine becomes less clear—as a strategy for optimizing education. Exploring case studies of data infrastructures, facial recognition, and the growing use of data science in education, Algorithms of Education draws on a wide variety of fields—from critical theory and media studies to science and technology studies and education policy studies—mapping the political and methodological directions for engaging with datafication and artificial intelligence in education governance. According to the authors, we must go beyond the debates that separate humans and machines in order to develop new strategies for, and a new politics of, education. |
| big data in education: Transforming Healthcare with Big Data and AI Alex Liu, Anna Farzindar, Mingbo Gong, 2020-04-01 Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare. |
| big data in education: Educational Data Mining Alejandro Peña-Ayala, 2013-11-08 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. |
| big data in education: Big Data in Education KHRITISH SWARGIARY, 2024-08-01 Big Data in Education explores the revolutionary impact of big data on the educational landscape. In this comprehensive guide, educators, administrators, policymakers, and researchers will discover how data-driven insights can enhance learning experiences, improve student outcomes, and streamline educational practices. The book begins by defining big data and its characteristics, such as volume, velocity, variety, veracity, and value. It delves into the various sources of educational data, including student information systems, learning management systems (LMS), social media, and IoT devices, as well as the methods for collecting this data. |
BIG | Bjarke Ingels Group
BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, …
Bjarke Ingels Group - BIG
Since BIG inception in 2006, David Zahle has been responsible for delivering imaginative and pioneering designs for buildings such as Copenhill, a waste-to energy plant with a ski slope on …
Athletics Las Vegas Ballpark | BIG | Bjarke Ingels Group
The project builds on a longstanding collaboration between BIG and the Athletics dating back to a different ballpark design in Oakland, California in 2018. The new ballpark’s roof is accentuated …
Jinji Lake Pavilion | BIG | Bjarke Ingels Group
Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, Architecture, Planning and Products. A plethora of in-house perspectives allows us to see …
Gowanus 175 Third Street | BIG | Bjarke Ingels Group
Catalyzed by the major Gowanus rezoning in 2021 – one of the most significant rezonings in New York City in recent years – 175 Third Street builds on years of BIG’s prior study and design …
Sankt Lukas Hospice and Lukashuset | BIG | Bjarke Ingels Group
A small step for each of us becomes a BIG LEAP for all of us. BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the …
Google Bay View | BIG | Bjarke Ingels Group
Leon Rost — Partner, BIG The campus includes 17.3 acres of high-value natural areas – including wet meadows, woodlands, and marsh – that contribute to Google’s broader efforts to …
Gelephu International Airport | BIG | Bjarke Ingels Group
As Bhutan’s second international airport, the project is a collaboration with aviation engineering firm NACO and an integral part of the Gelephu Mindfulness City (GMC) masterplan designed …
Opera and Ballet Theatre of Kosovo | BIG | Bjarke Ingels Group
BIG proposes a simple and prag matic arrangement of the performance venues draped in a soft, undulating exterior skin of photovoltaic tiles. The theatre ’s form is reminiscent of the free …
Freedom Plaza | BIG | Bjarke Ingels Group
Freedom Plaza will extend BIG’s contribution to New York City’s waterfront, alongside adjacent coastal projects that include the East Side Coastal Resiliency project, the Battery Park City …
BIG | Bjarke Ingels Group
BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, …
Bjarke Ingels Group - BIG
Since BIG inception in 2006, David Zahle has been responsible for delivering imaginative and pioneering designs for buildings such as Copenhill, a waste-to energy plant with a ski slope on …
Athletics Las Vegas Ballpark | BIG | Bjarke Ingels Group
The project builds on a longstanding collaboration between BIG and the Athletics dating back to a different ballpark design in Oakland, California in 2018. The new ballpark’s roof is accentuated …
Jinji Lake Pavilion | BIG | Bjarke Ingels Group
Our latest transformation is the BIG LEAP: Bjarke Ingels Group of Landscape, Engineering, Architecture, Planning and Products. A plethora of in-house perspectives allows us to see …
Gowanus 175 Third Street | BIG | Bjarke Ingels Group
Catalyzed by the major Gowanus rezoning in 2021 – one of the most significant rezonings in New York City in recent years – 175 Third Street builds on years of BIG’s prior study and design …
Sankt Lukas Hospice and Lukashuset | BIG | Bjarke Ingels Group
A small step for each of us becomes a BIG LEAP for all of us. BIG has grown organically over the last two decades from a founder, to a family, to a force of 700. Our latest transformation is the …
Google Bay View | BIG | Bjarke Ingels Group
Leon Rost — Partner, BIG The campus includes 17.3 acres of high-value natural areas – including wet meadows, woodlands, and marsh – that contribute to Google’s broader efforts to …
Gelephu International Airport | BIG | Bjarke Ingels Group
As Bhutan’s second international airport, the project is a collaboration with aviation engineering firm NACO and an integral part of the Gelephu Mindfulness City (GMC) masterplan designed …
Opera and Ballet Theatre of Kosovo | BIG | Bjarke Ingels Group
BIG proposes a simple and prag matic arrangement of the performance venues draped in a soft, undulating exterior skin of photovoltaic tiles. The theatre ’s form is reminiscent of the free …
Freedom Plaza | BIG | Bjarke Ingels Group
Freedom Plaza will extend BIG’s contribution to New York City’s waterfront, alongside adjacent coastal projects that include the East Side Coastal Resiliency project, the Battery Park City …
