How many features are too many?

Colin de la Higuera; Jotsna Iyer

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Contents

About the book
Acknowledgements
About the Project
Preface
I. Why Learn About AI
II. Finding Information
III. Managing Learning
1. 14. Smart Learning Management Systems
  Manuel Gentile and Giuseppe Città
2. 15. Learning Analytics and Educational Data Mining
  Azim Roussanaly; Anne Boyer; and Jiajun Pan
3. 16. AI-Speak: Data-based systems, part 1
4. 17. AI-Speak: Data-based Systems, part 2
5. 18. Issues with Data: Personal Identity
6. 19. Issues with Data: Bias and Fairness
IV. Personalising Learning
V. Listening, Speaking and Writing
1. 27. Translators
2. 28. Writing with AI
  Manuel Gentile and Giuseppe Città
3. 29. AI-Speak: Deep Neural Networks
4. 30. AI-Speak: Natural Language Processing
5. 31. AI, AIED and Human Agency
  Wayne Holmes
6. 32. Homogenisation, Invisibility and beyond, towards an Ethical AI
VI. On Generative AI
1. 33. Introducing Generative and Conversational AI
  Michael Hallissy and John Hurley
2. 34. Generative AI for the Classroom, part 1
3. 35. Generative AI for the Classroom, part 2
4. 36. ChatGPT and its Potential Impact on Homework in Schools
  Michael Hallissy and John Hurley
5. 37. The Gears of Generative AI
  Manuel Gentile and Fabrizio Falchi
6. 38. The Art, Craft or Science of Prompting
  Bastien Masse
7. 39. The Degenerative, part 1
8. 40. The Degenerative, part 2
VII. The Next Steps
VIII. Additional Content
As a very provisional conclusion...

AI for Teachers: an Open Textbook

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