Theodosia Prodromou – författare

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.

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.  

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.

New digital technologies offer many exciting opportunities to educators who are looking to develop better teaching practices. When technologies are new, however, the potential for beneficial and effective implementations and applications is not yet fully recognized. This book is intended to provide teachers and researchers with a wide range of ideas from researchers working to integrate the new technology of Augmented Reality into educational settings and processes. It is hoped that the research and theory presented here can support both teachers and researchers in future work with this exciting new technology.Contributors are: Miriam Adamková, Gilles Aldon, Panayiota Anastasi, Ferdinando Arzarello, Martina Babinská, Robert Bohdal, Francisco Botana, Constadina Charalambous, Eva Csandova, Omer Deperlioglu, Monika Dillingerová, Christos Dimopoulos, Jiri Dostal, Jihad El-Sana, Michael N. Fried, Maria Fuchsová, Marianthi Grizioti, Tomas Hlava, Markus Hohenwarter, Kateřina Jančaříková, Konstantinos Katzis, Lilla Korenova, Utku Köse, Zoltán Kovács,Blanka Kožík Lehotayová, Maria Kožuchová, Chronis Kynigos, Ilona-Elefteryja Lasica, Zsolt Lavicza, Álvaro Martínez, Efstathios Mavrotheris, Katerina Mavrou, Maria Meletiou-Mavrotheris, Georgios Papaioannou, Miroslava Pirháčová Lapšanská, Stavros Pitsikalis, Corinne Raffin, Tomás Recio, Cristina Sabena, Florian Schacht, Eva Severini, Martina Siposova, Zacharoula Smyrnaiou, Nayia Stylianidou, Osama Swidan, Christos Tiniakos, Melanie Tomaschko, Renata Tothova, Christina Vasou, and Ibolya Veress-Bágyi.