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About the book
Acknowledgements
About the Project
Preface
1. Technology, Change and You
2. AI is Everywhere
3. AI Already in Education
4. How AI Can Help You
5. Why not just do AI - Part 1
6. Why not just do AI - Part 2
7. Search Engines Part 1
8. Search Engines Part 2
9. AI Speak: Machine Learning
10. AI Speak: Search Engine Indexing
11. AI Speak: Search Engine Ranking
12. Behind the Search Lens: Effects of Search on the Individual
13. Behind the Search Lens: Effects of Search on the Society
14. Smart Learning Management Systems
Manuel Gentile and Giuseppe Città
15. Learning Analytics and Educational Data Mining
Azim Roussanaly; Anne Boyer; and Jiajun Pan
16. AI-Speak: Data-based systems, part 1
17. AI-Speak: Data-based Systems, part 2
18. Issues with Data: Personal Identity
19. Issues with Data: Bias and Fairness
20. A Note on Personalisation
21. Adaptive Learning Systems
22. AI Speak: How Youtube Learns You, part 1
23. AI Speak: How Youtube Learns You, part 2
24. AI-Speak: How Adaptive Systems Learn the Learner, part 1
25. AI-Speak: How Adaptive Systems Learn the Learner, part 2
26. The Flip Side of ALS: Some Paradigms to take note of
27. Translators
28. Writing with AI
29. AI-Speak: Deep Neural Networks
30. AI-Speak: Natural Language Processing
31. AI, AIED and Human Agency
Wayne Holmes
32. Homogenisation, Invisibility and beyond, towards an Ethical AI
33. Introducing Generative and Conversational AI
Michael Hallissy and John Hurley
34. Generative AI for the Classroom, part 1
35. Generative AI for the Classroom, part 2
36. ChatGPT and its Potential Impact on Homework in Schools
37. The Gears of Generative AI
Manuel Gentile and Fabrizio Falchi
38. The Art, Craft or Science of Prompting
Bastien Masse
39. The Degenerative, part 1
40. The Degenerative, part 2
41. Open or closed?
42. Artificial Intelligence, Homework, Exams and so forth
43. Obsolescence?
44. Individual or collective AI
45. Teaching AI
Optical Character Recognition
42
A brief description of some search engines
Optimising search
X5GON
Does Data always have to be labelled?
How many features are too many?
Hands-on Machine Learning
Cookies and Fingerprinting
More on Big Data
Other terms related to Personalised learning
AI technology is moving fast
Some automatic translation vocabulary
Understanding debates on the possible dangers of AI
Generative AIs - where should a teacher use them?
Transformers
GDPR in a nutshell
AI and Coding
Machine Learning and AI Through Data Experiments in Orange
Blaž Zupan
As a very provisional conclusion...
Additional Content
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AI for Teachers: an Open Textbook Copyright © 2024 by Colin de la Higuera and Jotsna Iyer is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.