Big Data in Education

Big Data in Education
Author: Ben Williamson
Publisher: SAGE
Total Pages: 281
Release: 2017-07-24
Genre: Education
ISBN: 1526416328

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 Psychological Research

Big Data in Psychological Research
Author: Sang Eun Woo
Publisher: American Psychological Association (APA)
Total Pages: 0
Release: 2020
Genre: Psychology
ISBN: 9781433831676

Big Data in Psychological Research provides an overview of big data theory, research design and analysis, collection methods, applications, ethical concerns, best practices, and future research directions for psychologists.

Learning Technology for Education in Cloud - MOOC and Big Data

Learning Technology for Education in Cloud - MOOC and Big Data
Author: Lorna Uden
Publisher: Springer
Total Pages: 214
Release: 2014-07-29
Genre: Education
ISBN: 3319106716

This book constitutes the refereed proceedings of the Third International Workshop on Learning Technology for Education in Cloud, LTEC 2014, held in Santiago, Chile, in September 2014. The 20 revised full papers presented were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on MOOC for learning; learning technologies; learning in higher education; case study in learning.

Adoption of Data Analytics in Higher Education Learning and Teaching

Adoption of Data Analytics in Higher Education Learning and Teaching
Author: Dirk Ifenthaler
Publisher: Springer Nature
Total Pages: 464
Release: 2020-08-10
Genre: Education
ISBN: 3030473929

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.

Data Mining and Learning Analytics

Data Mining and Learning Analytics
Author: Samira ElAtia
Publisher: John Wiley & Sons
Total Pages: 351
Release: 2016-09-20
Genre: Computers
ISBN: 1118998219

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, Health Law, and Bioethics

Big Data, Health Law, and Bioethics
Author: I. Glenn Cohen
Publisher: Cambridge University Press
Total Pages: 374
Release: 2018-03-08
Genre: Law
ISBN: 110815364X

When data from all aspects of our lives can be relevant to our health - from our habits at the grocery store and our Google searches to our FitBit data and our medical records - can we really differentiate between big data and health big data? Will health big data be used for good, such as to improve drug safety, or ill, as in insurance discrimination? Will it disrupt health care (and the health care system) as we know it? Will it be possible to protect our health privacy? What barriers will there be to collecting and utilizing health big data? What role should law play, and what ethical concerns may arise? This timely, groundbreaking volume explores these questions and more from a variety of perspectives, examining how law promotes or discourages the use of big data in the health care sphere, and also what we can learn from other sectors.

International Handbook of Psychology Learning and Teaching

International Handbook of Psychology Learning and Teaching
Author: Joerg Zumbach
Publisher: Springer Nature
Total Pages: 1483
Release: 2022-12-16
Genre: Education
ISBN: 3030287459

The International Handbook of Psychology Learning and Teaching is a reference work for psychology learning and teaching worldwide that takes a multi-faceted approach and includes national, international, and intercultural perspectives. Whether readers are interested in the basics of how and what to teach, in training psychology teachers, in taking steps to improve their own teaching, or in planning or implementing research on psychology learning and teaching, this handbook will provide an excellent place to start. Chapters address ideas, issues, and innovations in the teaching of all psychology courses, whether offered in psychology programs or as part of curricula in other disciplines. The book also presents reviews of relevant literature and best practices related to everything from the basics of course organization to the use of teaching technology. Three major sections consisting of several chapters each address “Teaching Psychology in Tertiary (Higher) Education”, “Psychology Learning and Teaching for All Audiences”, and “General Educational and Instructional Approaches to Psychology Learning and Teaching”.

How to Lie with Statistics

How to Lie with Statistics
Author: Darrell Huff
Publisher: W. W. Norton & Company
Total Pages: 144
Release: 2010-12-07
Genre: Mathematics
ISBN: 0393070875

If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.

Application of Big Data, Blockchain, and Internet of Things for Education Informatization

Application of Big Data, Blockchain, and Internet of Things for Education Informatization
Author: Mian Ahmad Jan
Publisher: Springer Nature
Total Pages: 682
Release: 2023-01-11
Genre: Computers
ISBN: 3031239474

The three-volume set LNICST 465, 466 and 467 constitutes the proceedings of the Second EAI International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2022, held as virtual event, in July 29–31, 2022. The 204 papers presented in the proceedings were carefully reviewed and selected from 550 submissions. BigIoT-EDU aims to provide international cooperation and exchange platform for big data and information education experts, scholars and enterprise developers to share research results, discuss existing problems and challenges, and explore cutting-edge science and technology. The conference focuses on research fields such as “Big Data” and “Information Education. The use of Artificial Intelligence (AI), Blockchain and network security lies at the heart of this conference as we focused on these emerging technologies to excel the progress of Big Data and information education.