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.

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.

Digital Education is recognised as a key transformative innovation for K-12 school and university teaching and learning, as well as, for professional development and vocational training. As a result, blended and online courses are nowadays widely deployed to meet the needs of K-12, higher education and vocational training students, as well as, the needs for professional development of in-service professionals. In this context, important professional roles in digital education and training, such as, the Instructional Designers, who design and develop online and blended courses, and the Trainers or Tutors who support the delivery of these online and blended courses, require new professional competences compared to those assumed at the traditional face to face education and tra ining programs.This is particularly relevant today, in the post Covid-19 era, where educational organisations, leaders and teachers are challenged with reinventing their teaching and learning environments to offer higher quality, more accessible and inclusive teaching, learning and assessment. Educational Data Literacy (EDL) is a core competence for all education professionals, including school teachers, instructional designers and tutors of online and blended learning courses, as well as educational institutions' leaders. Nevertheless, existing professional competence frameworks for educators pay little attention to EDL, missing out the potential of using emerging EDL methods and tools in online and blended teaching and learning - thus there is a need for extending existing professional competence frameworks for educators with new competences to accommodate the emerging field of EDL. To this end, this brief monograph presents a comprehensive proposal of an Educational Data Literacy Competence Profile (EDL-CP) framework for education professionals, as well as, exemplary learning outcomes for the proposed EDL-CP framework, and use-case examples for indicative target groups, namely instructional designers, e-Trainers and K-12 school teachers. The work of this book has been produced within the project "Learn2Analyze - An Academia-Industry Knowledge Alliance for enhancing Online Training Professionals' (Instructional Designers and e-Trainers) Competences in Educational Data Analytics" which is co-funded by European Commission through the Erasmus+ Program (Cooperation for innovation and the exchange of good practices - Knowledge Alliances).