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E-book: Artificial Intelligence for Learning: How to use AI to Support Employee Development

  • Format: PDF+DRM
  • Pub. Date: 13-Aug-2020
  • Publisher: Kogan Page Ltd
  • Language: eng
  • ISBN-13: 9781789660821
  • Format - PDF+DRM
  • Price: 40,74 €*
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  • This ebook is for personal use only. E-Books are non-refundable.
  • Format: PDF+DRM
  • Pub. Date: 13-Aug-2020
  • Publisher: Kogan Page Ltd
  • Language: eng
  • ISBN-13: 9781789660821

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Artificial intelligence is creating huge opportunities for workplace learning and employee development. However, it can be difficult for L&D professionals to assess what difference AI can make in their organization and where it is best implemented. Artificial Intelligence for Learning is the practical guide L&D practitioners need to understand what AI is and how to use it to improve all aspects of learning in the workplace. It includes specific guidance on how AI can provide content curation and personalization to improve learner engagement, how it can be implemented to improve the efficiency of evaluation, assessment and reporting and how chatbots can provide learner support to a global workforce.

Artificial Intelligence for Learning debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.



Critically assess the impact of artificial intelligence on the L&D function and understand how to use it to improve learning in the workplace.

Reviews

"The world of workplace learning will be dominated by AI within a few years. Artificial Intelligence for Learning plots a clear and concise path through what is the biggest opportunity the industry has had for many years." * Paul McElvaney, CEO of Learning Pool * "Donald Clark has been at the leading edge of technology in learning for over 30 years. His take on tech is always informed by his detailed knowledge of learning theory. This book on AI is no exception - it's bold, thorough, bang up to date, well-researched, evidence-based and practical." * Kirstie Donnelly MBE, CEO of City & Guilds Group *

About the author xiii
About this book xiv
Preface xvii
Acknowledgements xxi
List of abbreviations
xxii
PART ONE Introduction
1(20)
01 Homo technus
3(11)
Technological revolutions
3(3)
Culture
6(1)
Philosophy and mathematics
7(1)
Learning technology
8(4)
Conclusion
12(1)
References
12(2)
02 What is AI?
14(7)
AI as idiot savant
14(1)
AI is many things
15(1)
AI and intelligence
16(1)
AI as competence without comprehension
17(2)
AI as collective competence
19(3)
AI learns
22(1)
AI in learning
23(3)
References
26(1)
PART TWO Teaching
27(2)
03 Robot teacher fallacy
29(1)
Anthropomorphizing AI in learning
29(2)
Reductive robot fallacy
31(4)
Teaching versus technology
35(2)
References
37(2)
04 Teaching
39(16)
AI for teacher administration
39(4)
AI for teaching activities
43(5)
AI for enhancing teaching
48(4)
AI and online learning make you a better teacher
52(1)
References
53(2)
PART THREE Chatbots
55(44)
05 AI is the new UI
57(13)
Invisible interface
60(2)
Learning interfaces
62(1)
Voice in learning
63(3)
Future interfaces
66(2)
Conclusion
68(1)
References
69(1)
06 Chatbots
70(15)
The tutorbot that fooled everyone
71(3)
Chatbots and learning theory
74(3)
Uses of chatbots in learning
77(6)
References
83(2)
07 Building chatbots
85(14)
Building or buying a chatbot
85(6)
Chatbot abuse
91(2)
Botched bots
93(1)
Caution
94(2)
Conclusion
96(1)
References
97(2)
PART FOUR Learning
99(76)
08 Content creation
101(16)
Learning science
101(1)
Text
102(1)
Natural language processing (NLP)
103(1)
Content creation
104(1)
Summarize text content
105(2)
Adapt language content
107(1)
Create content from existing resources
108(3)
Open input content
111(1)
Create content from scratch
112(3)
Conclusion
115(1)
References
115(2)
09 Video
117(11)
What can we learn from YouTube?
117(1)
What can we learn from Netflix?
118(3)
Video and AI
121(2)
AI turns video into deep learning
123(2)
Retrieval
125(1)
Conclusion
126(1)
References
127(1)
10 Push learning
128(13)
Peer learning
129(1)
Nudge learning
130(3)
Campaigns
133(1)
Interleaving
133(2)
Spaced practice
135(4)
Conclusion
139(1)
References
139(2)
11 Adaptive learning
141(13)
Adaptive learning
141(2)
Types of adaptation
143(6)
Adaptive results
149(3)
Conclusion
152(1)
References
153(1)
12 Learning organizations
154(13)
What can we learn from Amazon?
154(2)
AI and informal learning
156(2)
Moments of need
158(1)
From LMS to LXP
158(7)
Organizational learning
165(1)
Conclusion
166(1)
References
166(1)
13 Assessment
167(8)
Recruitment and assessment
167(1)
Digital identification
168(1)
Plagiarism and AI
169(2)
Automatic essay assessment
171(3)
Reference
174(1)
PART FIVE Data
175(30)
14 Data analytics
177(20)
Sources of data
177(1)
Data pitfalls
178(2)
Types of data
180(2)
Learners and data
182(1)
Learning analytics
183(1)
Level 1 Describe
184(2)
Level 2 Analyse
186(3)
Level 3 Predict
189(1)
Level 4 Prescribe
190(2)
A/B testing
192(1)
Learning analytics and organizational change
193(1)
Conclusion
194(1)
References
195(2)
15 Sentiment analysis
197(8)
Social learning
198(1)
Sentiment analysis
199(3)
Digging deeper
202(2)
Conclusion
204(1)
References
204(1)
PART SIX Future
205(78)
16 Future skills
207(15)
AI and learning design
208(4)
AI and technology design
212(2)
AI and data design
214(3)
AI as agile production
217(2)
AI and procurement
219(2)
Conclusion
221(1)
References
221(1)
17 Ethics and bias
222(18)
Brains and AI
223(2)
Human bias and AI
225(2)
Common charges
227(4)
AI as statistics
231(1)
Avoiding bias
232(1)
Pedagogic concerns
233(2)
Doomsday is hot
235(2)
Conclusion
237(1)
References
238(2)
18 Employment
240(18)
47 per cent of jobs will be automated...
241(3)
65 per cent of today's students will be employed in jobs that don't exist yet...
244(1)
Professions and AI
244(5)
Learning jobs and AI
249(3)
Under- and unemployment
252(4)
Conclusion
256(1)
References
256(2)
19 The final frontier
258(16)
AI, AR and VR
260(2)
Neurotech
262(4)
Runaway learning
266(6)
References
272(2)
20 Where next?
274(9)
Technology
274(3)
Utopian
277(1)
Dystopian
277(4)
References
281(2)
Index 283
Donald Clark has over 30 years' experience in online learning, simulations, virtual reality, mobile and artificial intelligence projects. He was a founding member of Epic Group plc and the Founder and CEO of Wildfire Learning. He is a frequent global speaker, blogger, advisor and researcher on AI in learning and is also a Visiting Professor at the University of Derby.