Educational Data Analytics for Teachers and School Leaders / by Sofia Mougiakou, Dimitra Vinatsella, Demetrios Sampson, Zacharoula Papamitsiou, Michail Giannakos, Dirk Ifenthaler.

Format:

Book

Author/Creator:

Mougiakou, Sofia., Author.

Vinatsella, Dimitra., Author.

Sampson, Demetrios., Author.

Papamitsiou, Zacharoula., Author.

Giannakos, Michail, Author.

Ifenthaler, Dirk, Author.

Series:

Advances in Analytics for Learning and Teaching, 2662-2130

Language:

English

Subjects (All):

Educational technology.

Quantitative research.

Digital Education and Educational Technology.

Data Analysis and Big Data.

Local Subjects:

Digital Education and Educational Technology.

Data Analysis and Big Data.

Physical Description:

1 online resource (XII, 238 p. 94 illus., 82 illus. in color.)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2023.

Language Note:

English

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 leadersand 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.

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.

ISBN:

9783031152665

3031152662

OCLC:

1351747710

Access Restriction:

Open access Unrestricted online access