With Artificial Intelligence (AI) creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment?
Artificial Intelligence for Learning is the essential guide for learning professionals who want to understand how to use AI to improve all aspects of learning in organizations. This new edition debunks the myths and misconceptions around AI, discusses the learning theory behind generative AI and gives strategic and practical advice on how AI can be used.
This book also includes specific guidance on how AI can provide learning support, chatbot functionality and content, as well as ideas on ethics and personalization. This book is necessary reading for all learning practitioners needing to understand AI and what it means in practice.

lgli/Artificial Intelligence for Learning, 2e - Donald Clark (2024)-v2.pdf

United Kingdom and Ireland, United Kingdom

Kogan Page, [S.l.], 2024

2, PS, 2024

2, US, 2024

Cover
Contents
List of figures and tables
Preface
Acknowledgements
List of abbreviations
01 Homo technus
Technological revolutions
Culture
Philosophy and mathematics
Learning technology
Conclusion
References
02 What is AI?
AI is many things
AI and intelligence
AI as competence without comprehension
AI as collective competence
AI learns
AI in learning
References
03 Learning theory and AI
Generative AI and learning
Learning theory and generative AI
AI, language and learning
Personalized learning
Learning design
Conclusion
References
04 AI is the new UI
Invisible interface
Learning interfaces
Voice in learning
AI interfaces and learning
Low floor, high ceiling, wide walls
Conclusion
References
05 Teaching
Anthropomorphizing AI in learning
Reductive robot fallacy
Teaching versus technology
AI for teaching activities
AI for enhancing teaching
References
06 Universal teacher
21st-century skills myth
Human exceptionalism
Productivity
Is there anything left?
Concept of a universal teacher
Universal teaching
AI and emotions
Conclusion
References
07 Chatbots
Tutorbot that fooled everyone
Chatbots and learning theory
Uses of chatbots in learning
Building chatbots
Personal chatbots
Chatbot abuse
Botched bots
Caution
Conclusion
References
08 AI and performance support
AI and informal learning
AI and performance support
Organizational learning
Conclusion
References
09 AI content creation
Learning science
Create content from scratch
Prompting
Learning science and pedagogy
Branching scenarios
AI as agile production
Death of the SME
Video and AI
Interleaving and spaced practice
Assessment
Conclusion
References
10 Adaptive learning
Adaptive learning
Types of adaptation
From LMS to AI
Conclusion
11 Data analytics
Sources of data
Data pitfalls
Types of data
Learners and data
Learning analytics
Learning analytics and organizational change
Conclusion
Reference
12 AI learning organizations
AI changes everything
Strategy on AI
Using generative AI
AI and learning design
AI and technology design
AI and data design
AI and procurement
Conclusion
References
13 AI and ethics
Deontological versus utilitarian
Ethics and regulation
Techno-determinism
AI developments
Conclusion
References
14 AI and bias
Brains and AI
Human bias and AI
Common charges
AI as statistics
Avoiding bias
Pedagogic concerns
References
15 AI and employment
‘47 per cent of jobs will be automated...’
‘65 per cent of today’s students will be employed in jobs that don’t exist yet...’
Impact of AI
Productivity
Creativity
Professions and AI
Learning jobs and AI
Under- and unemployment
Conclusion
References
16 AI and extinction
Dystopia or utopia
Conclusion
References
17 Where next?
Technology
Energy and emissions
Biocomputers
Quantum computing
Fusion
References
18 Learning frontiers
AI learning
AI, AR and VR
Neurotech
References
19 Crossing learning frontiers
Teaching frontier
Educational frontier
Cognitive frontier
Art frontier
Social frontier
Final message from the frontier
Index

With Artificial Intelligence creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment? Artificial Intelligence for Learning is the essential guide for HR and L&D practitioners who want to understand how to use AI to improve all aspects of learning in the workplace. This new edition debunks the myths and fallacies around AI, gives strategic and practical advice on how to upskill by utilizing AI and overall illustrates how AI can aid the learning experience.This book also includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, as well as how to improve the efficiency of evaluating, assessing and reporting learning content. With real-world examples from companies who have effectively implemented AI, such as the NHS and Netflix, this book is necessary reading for all L&D practitioners needing to understand AI and what it means in practice.

With Artificial Intelligence creating huge opportunities for learning and employee development, how can learning professionals best implement the use of AI into their environment?
Artificial Intelligence for Learning is the essential guide for HR and L&D practitioners who want to understand how to use AI to improve all aspects of learning in the workplace. This new edition debunks the myths and fallacies around AI, gives strategic and practical advice on how to upskill by utilizing AI and overall illustrates how AI can aid the learning experience.
This book also includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, as well as how to improve the efficiency of evaluating, assessing and reporting learning content. With real-world examples from companies who have effectively implemented AI, such as the NHS and Netflix, this book is necessary reading for all L&D practitioners needing to understand AI and what it means in practice.

2024-05-12