The first edition of the Handbook of Learning Analytics FIRST EDITION was published in 2017 and can be downloaded for free. https://solaresearch.org/hla-17/
Part 1 Basic Concepts
Chapter 1 Theory and Learning Analysis 17-22
Simon Knight and Simon Buckingham Shum
Chapter 2 Learning Analysis and Knowledge Construction Calculation Methods 23-33
Urlich Hoppe
Chapter 3 Measurement Methods and Their Application in Learning Analysis 34-48
Yoav Bergner
Chapter 4 Moral and Learning Analysis: Recording or Not Recording 49-57
Paul Prinsloo and Sharon Slade
Part 2 Techniques and Methods
Chapter 5 Predictive Modeling of Teaching 61-68
Christopher Brooks and Craig Thompson
Chapter 6 beyond better data to create predictive models of education data can be interpreted 69-76
Ren Liu and Kenneth Koedinger
Chapter 7 content analysis: definitions, scope, and reviewed published studies 77-92
VitomirKovanović, SrećkoJoksimović , Dragan Gašević, Marek Hatala and George Siemens
Chapter 8 Natural Language Processing and Learning Analysis 93-104
Danielle McNamara, Laura Allen, Scott Crossley, Mihai Dascalu and Cecile Perret
Chapter 9 Discourse Analysis 105-114
Carolyn Rosé
Chapter 10 Emotional Learning Analysis 115-127
Sidney D'Mello
Chapter 11 Multimodal Learning Analysis 129-141
Xavier Ochoa
Chapter 12 Learning Analysis Dashboard 143-150
Joris Klerkx Katrien Verbert and Erik Duval
Chapter 13 Learning Analysis Implementation Design 151-160
Alyssa Wise and Jovita Vytasek
Part 3 Application
Chapter 14 uses learning analytics and educational data mining techniques to provide data-driven feedback to students 163-174
Abelardo Pardo, Oleksandra Poquet, Roberto Martínez-Maldonado and Shane Dawson
Chapter 15 Cognitive Network Analysis: Theory-based Learning Analysis 175-187
David Williamson Shaffer and Andrew Ruis
Chapter 16 Multilevel Analysis of Activities and Participants in a Heterogeneous Network Learning Environment 189-197
Daniel Suthers
Chapter 17 Data Mining for Large-Scale Formative Writing 199-210
Peter Foltz and Mark Rosenstein
Chapter 18 Large-scale open online courses of various big data and random field experiments 211-222
Rene Kizilcec
Chapter 19 uses granular large-scale action data to predict student behavior 223-233
Steven Tang, Joshua Peterson and Zachary Pardos
Chapter 20 Recommendation System for Applied Learning Analysis Data: Tutorials 234-240
Soude Fazeli, Hendrik Drachsler and Peter Sloep
Chapter 21 Learning Self-Adjusting Learning Analysis 241-249
Philip Winne
Chapter 22 Learning Video Analysis 251-2 267
Negin Mirriahi and Lorenzo Vigentini
Chapter 23 Study and Work: Professional Learning Analysis 269-277
Allison Littlejohn
