This new and free Handbook of Learning Analytics covers a broad sprectrum of topics including Emotion (from Sidney D’Mello) and Self-Regulated Learning (from Philip Winne).

Learning Analytics

This book is edited by Charles Lang, George Siemens, Alyssa Wise & Dragan Gašević

The full book Handbook of Learning Analytics can be downloaded for free here (CC BY 4.0)

Handbook of Learning Analytics

Citation: Lang, C., Siemens, G., Wise, A., & Gašević, D. (Eds.). (2017). The Handbook of Learning Analytics. Society for Learning Analytics Research.
ISBN: 978-0-9952408-0-3
DOI: 10.18608/hla17

Handbook of Learning Analytics – Table of Contents

SECTION 1. FOUNDATIONAL CONCEPTS

Chapter 1. Theory and Learning Analytics

Simon Knight and Simon Buckingham Shum

Chapter 2. Computational Methods for the Analysis of Learning and Knowledge Building Communities

Urlich Hoppe

Chapter 3. Measurement and its Uses in Learning Analytics

Yoav Bergner

Chapter 4. Ethics and Learning Analytics: Charting the (Un)Charted

Paul Prinsloo and Sharon Slade

SECTION 2. TECHNIQUES & APPROACHES

Chapter 5. Predictive Modelling in Teaching and Learning

Christopher Brooks and Craig Thompson

Chapter 6. Going Beyond Better Data Prediction to Create Explanatory Models of Educational Data

Ren Liu and Kenneth Koedinger

Chapter 7. Content Analytics: The Definition, Scope, and an Overview of Published Research

Vitomir Kovanović, Srećko Joksimović, Dragan Gašević, Marek Hatala, and George Siemens

Chapter 8. Natural Language Processing and Learning Analytics

Danielle McNamara, Laura Allen, Scott Crossley, Mihai Dascalu, and Cecile Perret

Chapter 9. Discourse Analytics

Carolyn Rosé

Chapter 10. Emotional Learning Analytics

Sidney D’Mello

Chapter 11. Multimodal Learning Analytics

Xavier Ochoa

Chapter 12. Learning Analytics Dashboards

Joris Klerkx, Katrien Verbert and Erik Duval

Chapter 13. LA Implementation Design

Alyssa Wise and Jovita Vytasek

SECTION 3. APPLICATIONS

Chapter 14. Provision of Data-Driven Student Feedback in LA and EDM

Abelardo Pardo, Oleksandra Poquet, Roberto Martínez-Maldonado and Shane Dawson

Chapter 15. Epistemic Network Analysis: A Worked Example of Theory-Based Learning Analytics

David Williamson Shaffer and Andrew Ruis

Chapter 16. Multilevel Analysis of Activity and Actors in Heterogeneous Networked

Learning Environments

Daniel Suthers

Chapter 17. Data Mining Large-Scale Formative Writing

Peter Foltz and Mark Rosenstein

Chapter 18. Diverse Big Data and Randomized Field Experiments in Massive Open Online Courses

Rene Kizilcec and Christopher Brooks

Chapter 19. Predictive Modelling of Student Behaviour Using Granular Large-Scale

Action Data

Steven Tang, Joshua Peterson and Zachary Pardos

Chapter 20. Applying Recommender Systems for Learning Analytics Data: A Tutorial

Soude Fazeli, Hendrik Drachsler and Peter Sloep

Chapter 21. Learning Analytics for Self-Regulated Learning

Philip Winne

Chapter 22. Analytics of Learner Video Use

Negin Mirriahi and Lorenzo Vigentini

Chapter 23. Learning and Work: Professional Learning Analytics

Allison Littlejohn

SECTION 4. INSTITUTIONAL STRATEGIES & SYSTEMS PERSPECTIVES

Chapter 24. Addressing the Challenges of Institutional Adoption

Cassandra Colvin, Shane Dawson, Alexandra Wade, and Dragan Gašević

Chapter 25. LA: Layers, Loops and Processes in a Virtual Learning Infrastructure

Ruth Crick

Chapter 26. Unleashing the Transformative Power of Learning Analytics

Linda Baer and Donald Norris

Chapter 27. A Critical Perspective on Learning Analytics and Educational Data Mining

Rita Kop, Helene Fournier and Guillaume Durand

Chapter 28. Unpacking Student Privacy

Elana Zeide

Chapter 29. Linked Data for LA: The Case of the LAK Dataset

Davide Taibi and Stefan Dietze

Chapter 30. Linked Data for Learning Analytics: Potentials and Challenges

Amal Zouaq, Jelena Jovanović, Srećko Joksimović and Dragan Gašević

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