Educational data analytics for teachers and school leaders / Sofia Mougiakou, Dimitra Vinatsella, Demetrios Sampson, Zacharoula Papamitsiou, Michail Giannakos, Dirk Ifenthaler.
2023
LB2846
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Online Access
Concurrent users
Unlimited
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Open access
Document Delivery Supplied
Open access
Details
Title
Educational data analytics for teachers and school leaders / Sofia Mougiakou, Dimitra Vinatsella, Demetrios Sampson, Zacharoula Papamitsiou, Michail Giannakos, Dirk Ifenthaler.
Author
Mougiakou, Sofia, author.
ISBN
9783031152665 (electronic bk.)
3031152662 (electronic bk.)
9783031152658
3031152662 (electronic bk.)
9783031152658
Published
Cham, Switzerland : Springer, [2023]
Language
English
Description
1 online resource (xii, 238 pages) : illustrations (some color).
Item Number
10.1007/978-3-031-15266-5 doi
Call Number
LB2846
Dewey Decimal Classification
370.21
Summary
Educational Data Analytics (EDA) have been attributed with significant benefits for enhancing on-demand personalized educational support of individual learners as well as reflective course (re)design for achieving more authentic teaching, learning and assessment experiences integrated into real work-oriented tasks. This open access textbook is a tutorial for developing, practicing and self-assessing core competences on educational data analytics for digital teaching and learning. It combines theoretical knowledge on core issues related to collecting, analyzing, interpreting and using educational data, including ethics and privacy concerns. The textbook provides questions and teaching materials/ learning activities as quiz tests of multiple types of questions, added after each section, related to the topic studied or the video(s) referenced. These activities reproduce real-life contexts by using a suitable use case scenario (storytelling), encouraging learners to link theory with practice; self-assessed assignments enabling learners to apply their attained knowledge and acquired competences on EDL. By studying this book, you will know where to locate useful educational data in different sources and understand their limitations; know the basics for managing educational data to make them useful; understand relevant methods; and be able to use relevant tools; know the basics for organising, analysing, interpreting and presenting learner-generated data within their learning context, understand relevant learning analytics methods and be able to use relevant learning analytics tools; know the basics for analysing and interpreting educational data to facilitate educational decision making, including course and curricula design, understand relevant teaching analytics methods and be able to use relevant teaching analytics tools; understand issues related with educational data ethics and privacy. This book is intended for school leaders and teachers engaged in blended (using the flipped classroom model) and online (during COVID-19 crisis and beyond) teaching and learning; e-learning professionals (such as, instructional designers and e-tutors) of online and blended courses; instructional technologists; researchers as well as undergraduate and postgraduate university students studying education, educational technology and relevant fields.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Open access.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed October 31, 2022).
Added Author
Vinatsella, Dimitra, author.
Sampson, Demetrios G., author.
Papamitsiou, Zacharoula, author.
Giannakos, Michail, author.
Ifenthaler, Dirk, author.
Sampson, Demetrios G., author.
Papamitsiou, Zacharoula, author.
Giannakos, Michail, author.
Ifenthaler, Dirk, author.
Series
Advances in analytics for learning and teaching, 2662-2130
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Online Access
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All Resources
Table of Contents
Chapter 1: Online and Blended Teaching and Learning supported by Educational Data
Chapter 2: Adding Value and Ethical Principles to Educational Data Chapter
3: Learning Analytics Chapter
4: Teaching Analytics
Appendix: Learn2Analyse Educational Data Literacy competence framework.
Chapter 2: Adding Value and Ethical Principles to Educational Data Chapter
3: Learning Analytics Chapter
4: Teaching Analytics
Appendix: Learn2Analyse Educational Data Literacy competence framework.