How artificial intelligence is revolutionizing and disrupting learning and development practices throughout the ADDIE value chain - analysis, design, development, delivery and evaluation

1. HOW ARTIFICIAL INTELLIGENCE (AI) IS
REVOLUTIONIZING LEARNING AND
DEVELOPMENT (L&D) PRACTICES
CHARLES COTTER PhD, MBA, B.A (Hons), B.A
www.slideshare.net/CharlesCotter
SIERRA HOTEL, RANDBURG
16 AUGUST 2018

2. PRESENTATION
OVERVIEW
• The current context and
the future of learning
and development (L&D)
– the rise Intelligent
Learning
• The business case for AI
in L&D
• Ways in which AI is
revolutionizing L&D
practices, throughout
the L&D ADDIE value
chain

5. THE FUTURE OF L&D
• Strategic goal: To transform to be a Strategic Learning Partner (role)
• Strategic objective: To create a HILO (High Impact Learning
Organization)
• Q1: So how strategic is L&D?
• Q2: Is AI the solution – the driver/accelerator of change?
• Transform from training to L&D navigation:
❑Learn more intelligently (smarter)
❑Learn with impact
❑Learn faster

6. AGREE OR DISAGREE?
WHY?

7. RESEARCH: DIAGNOSIS OF STRATEGIC L&D
(COTTER, 2018)

8. STRATEGIC L&D MATURITY MODEL
Level 4: Strategic L&D
(mean range of 3.5 - 4.0)
Level 3: Transformational L&D
(mean range of 3.0 - 3.49)
Level 2: Transactional L&D
(mean range of 2.5 - 2.99)
Level 1: Traditional L&D
(mean range of 1.0 - 2.49)

9. SABPP HR AUDITED RATINGS
(X39 COMPANIES)

10. THE FUTURE OF LEARNING AND
DEVELOPMENT (COTTER, 2018)
• #1: Transition from e-learning to mobile (m)-learning
• #2: More video-based, on-demand micro-learning
• #3: Learners taking more ownership and responsibility for
their learning
• #4: More use of Virtual Reality in the traditional learning
space
• #5: Technology-enabled and digital learning devices – the
rise of Augmented learning
• #6: Transition from training facilitators to Learning Navigators

11. THE FUTURE OF LEARNING AND
DEVELOPMENT (COTTER, 2018)
• #7: Less focus on learning content and more focus on the learner
experience
• #8: Less focus on learner assessment and qualifications and more focus on
holistic application and transfer of learning
• #9: Less formal training and more focus on social and experiential learning
(refer to the 70-20-10 model of learning)
• #10: Transition from books to MOOC’s
• #11: Transition from digital learning to Intelligent learning
• #12: Use of a Strategic L&D Scorecard and adoption and implementation
of the Strategic L&D Conceptual Framework (Cotter, 2017).

13. THE FUTURE
OF LEARNING
• Companies are
finding that AI is
allowing them to
succeed more than
their competitors
that don’t use AI.
• AI is a driver of the
future of learning
and the disruption
of digital learning.

15. IMPROVEMENT RECOMMENDATIONS –
SLP (COTTER, 2018)
• CURATE - from providing training programmes to providing business valued
learning solutions;
• CREATE – an enabling high impact learning organization (HILO) culture and
improved learner experience (Lx);
• NAVIGATE - from being people pleasers and comfort-seekers to making
employees competitive and competent;
• MIGRATE - from traditional, manual methods to technology-enabled learning,
augmented and intelligent learning;
• EDUCATE - transform from training departments to learning factories
(repositories of knowledge) and
• GRADUATE - from being transactional (administrative) to being
transformational (strategic) i.e. from training administrators to being strategic
learning partners.

16. THE BUSINESS CASE FOR AI IN L&D
• #1: Personalization - More individualized learning experiences (Lx) - AI creates
immersive, engaging and meaningful experiences, not lessons e.g. Google's
AlphaGo
• #2: Gap Analysis - AI emphasizes areas that need improvement and provides
recursive feedback for such improvement
• #3: Acceleration - With machine learning, the ability of employees to move from
novice to expert will be fast-tracked, collapsing the development timeline from
years to months.
• #4: Assessment - AI creates intuitive, intelligent tests and quizzes. AI will also
make it possible to assess and recommend tailored learning solutions quickly.
• #5: Accessibility and Multiple Learning Interfaces (MLI) – AI creates smarter
learning interfaces for employees e.g. 3D, virtual reality and simulation. AI is an
enabler of learning on-demand and curates and recommends learning content
just as needed.

17. THE BUSINESS CASE FOR AI IN L&D
• #6: Optimization of comprehension and retention - AI will also begin to be used as virtual
mentors more to increase the number of experiential learning employees are put through
to ensure their comprehension and retention of the learning material is effective. Feedback
loops and ongoing, automated performance support provide reinforcement and practice
that can extend skills development.
• #7: Trouble shooting and Adaptation - Learning and Teaching software is adaptive to
relationships, abstract concepts, real-world use and individual learning related
requirements of a learner. The benefit of AI comes from its ability to evaluate, learn and
adopt a dynamic strategy – AI solves problems that baffle most humans.
• #8: Productivity and Flexibility - By using online training modules, employees can remain at
their desks and still engage the material thoroughly. The flexibility allows them to choose a
time where they won’t be preoccupied with work commitments that can all serve as a
learning distraction. AI allows managers to provide more training at a significantly lower
cost.
• #9: Accuracy of Measurement - AI measures employee engagement more effectively and
compares the results to determine if the program is doing its intended job.
• #10: Business Intelligence and Predictive Analytics – AI creates more detailed reports on
training effectiveness and ROI.

19. HOW AI IS
IMPACTING
ON
TRAINING
NEEDS
ANALYSIS
(TNA) AND
ID OF
SKILLS
GAPS
• AI and ML enable the system to make
recommendations beyond a particular topic to
analyze what their training teammates and
people with similar interests are taking.
• The advantage of cognitive technology is that it
can handle vast amounts of structured and
unstructured data with a speed and accuracy to
find training courses that match employees
current career experience.

20. HOW AI IS
IMPACTING
ON
TRAINING
NEEDS
ANALYSIS
(TNA) AND
ID OF
SKILLS
GAPS
• Progressive companies are experimenting with other
software that uses ML to identify skills gaps
of upwardly mobile employees.
• The EdCast learning platform uses AI to suggest
training paths for employees.
• AI and ML are enablers of better understanding
learner behaviours and predict needs by
recommending and positioning content based on
past behaviour.

21. HOW AI IS IMPACTING ON LEARNING
DESIGN AND DEVELOPMENT
• In most workplaces, training is episodic and not continuous.
• By using AI to help analyse the current status, role, behaviour,
satisfaction, engagement and sentiment of each employee,
companies will be able to deliver training and skills development
opportunities to employees at the right time to support career
path planning and retention.
• AI and ML show promise in making it easier for L&D professionals
to connect the dots between metrics around key organizational
challenges.
• The key lies in using workplace analytics tools for measuring these
soft skills and then using AI and ML to identify which training
approaches support people in becoming measurably better all-
around contributors.

22. HOW AI IS IMPACTING ON LEARNING
DESIGN AND DEVELOPMENT
• ML is being used to improve instructional content
creation and to enable faster instruction design.
• AI will also be able to enhance and streamline
content development for instructional designers.
• AI will free up time for L&D professionals to
concentrate on creating quality content for
learners.

24. HOW AI IS IMPACTING ON LEARNING
DESIGN AND DEVELOPMENT
• With so many open source options for learning, it almost doesn’t
make sense for a company to create its own virtual platform.
• However, distinguishing high-quality content aligned with
company values and culture is a critically important skill, which
makes a case for customized, company-specific content.
• According to Bersin (2017), “Yes it’s important for employees to be
able to quickly find the content they want.”
• The introduction of AI technologies to learning on demand will
provide additional speed and accessibility for both L&D and the
employees the departments support.

26. LEARNING STYLES
• Learning styles impact the development of learning solutions.
• The introduction of AI may not only help new hires learn more
quickly but may also free up L&D departments to be able to
provide more face-to-face coaching options.
• A person’s learning style may be influenced by age, ethnicity and
cultural background, which must be factored into the
development process e.g. Millennials reported being a little more
interested in microlearning, with a preference for short how-to
videos.
• But across the board, all ages wanted face-to-face, live training.
And, contrary to popular belief, millennials want face-to-face
training even more than others. Why? Part of the reason is the
constant desire for learning.
• Studies have found that the number-one complaint of new hires in
entry-level positions is that they aren’t learning fast enough. New
hires also say they would like more hands-on help from managers
or peers.

27. VALUE/USEFULNESS OF LEARNING DELIVERY
METHODS – 7TH ANNUAL LEARNING IN THE
WORKPLACE SURVEY (N=5 500)

28. ALGORITHMS AND LEARNING STYLES AND
PREFERENCES
• Among the most interesting are apps that use AI to
create interactive tests and assessments to match test
takers’ personal learning styles and engagement
levels.
• Similar to Lumosity’s interactive brain games, these
tools generate countless data points about users as
they learn, including their pace and learning style.
• For L&D professionals, such innovations highlight the
need for customized learning paths and data-driven
approaches to employee development.

29. HOW AI IS IMPACTING ON LEARNING
IMPLEMENTATION/DELIVERY
• Given the AI capacity to adapt, targeted learning instructions can be
developed that are based on their relative strengths and weaknesses.
• It also reduces the meaningless work that trainers have to periodically do.
• AI can make learning a lot more interesting than traditional delivery
methods:
❑ It can create the sort of immersive experience that you need in order to
captivate and stimulate learners and lead to better levels of retention and
understanding.
❑ For example, game technology and simulation are expected to play major roles
in this regard.
❑ AI can actually make education, learning and teaching a lot more adaptive and
intuitive.
❑ Such technology can actually be used in order to encourage learners to come
together and develop knowledge themselves i.e. create knowledge
communities.

30. AI IN E-LEARNING SYSTEMS
• AI is allowing teaching software to be adaptive to individual learning types
to increase positive outcomes of online learning.
• AI also emphasizes areas that need improvement in teaching software.
• This is allowing online systems to generate better material and more
comprehensive testing.
• AI creates meaningful lessons by identifying particular learner needs and
comes up with models that focus on methods and reason to improve
problem areas.
• AI has the ability to evaluate, learn and adopt new strategies to come up
with solutions for problem areas users may be facing.
• One of the best benefits of AI in e-learning is that students can learn at
their own pace to retain the information better.

31. AI IN BLENDED
LEARNING
• The kinds of programs
that are most
successful today will
continue to be most
successful in the future
– programs that blend
online, virtual and
face-to-face learning.

32. AI AND VIRTUAL REALITY (VR) AND
AUGMENTED REALITY (AR)
• According to Accenture Consulting (2017), digital learning methods, such as
virtual reality and augmented reality technologies can provide realistic
simulations to enable workers to master new manual tasks, so they can
work with smart machinery.
• These digital technologies can reinforce correct procedures on the shop
floor, monitoring how employees execute tasks and coaching them to
optimise procedure and their performance.
• Workers want to know how to perform their jobs with excellence, but they
often require continued education to stay at the front of their field.
• Managers can’t continuously encourage employees to take entire days away
from their work in the interest of corporate training. However, they can
make digital learning with artificial intelligence available at a worker’s
convenience.

33. COUNTERPOINT
• Refer to the article, 5 REASONS
WHY VIRTUAL REALITY AND
RELATED TECHNOLOGY–
ENABLED DEVICES ARE
UNLIKELY TO BE THE NEXT LEAP
IN LEARNING IN S.A
(Cotter, 2017)
• https://www.linkedin.com/puls
e/5-reasons-why-virtual-
reality-related-devices-unlikely-
charles-cotter/

34. INTELLIGENT TUTORING
SYSTEMS
• Just like human tutors can do, intelligent
tutoring systems are able to understand
the style of learning preferred by
students. They are also able to gauge
the amount of knowledge that a learner
already has.
• All this data and analysis is being used to
deliver instructions and support that is
created specifically for that learner.

35. CASE STUDY: AI IN EDUCATION (GIT)
• At Georgia Institute of Technology, 2017, Jill Watson,
powered by IBM Watson analytics, became the ninth
teaching assistant for an online course taught by
Professor Ashok Goel entitled, Knowledge Based Artificial
Intelligence.
• Professor Goel estimates that within a year, Jill Watson was
able to answer 40% of all the students’ questions, freeing the
human TAs to tackle more complex technical inquiries.
• In fact, one student reported, "Just when I wanted to
nominate Jill Watson as an outstanding TA, always there
reminding us of due dates and posting questions to engage us
mid-week, I find out she is a chatbot. I was flabbergasted."

36. MICRO LEARNING
• With micro-learning
gaining popularity, learning
modules are being
increasingly broken up into
more digestible pieces,
providing employees with
access to learning material
when they need it - ‘just in
time’ learning.

37. CREATING A GLOBAL LEARNING PLATFORM –
MOOCs, COOCs and SPOCs
• With AI it would be possible for companies to create virtual
global learning platforms. It would no longer matter as to
where a learner is located. If they are unable to attend a
training session all they would need to do is visit a link, click
on it and the learner can join the live classroom.
• Similarly, thanks to this technology it would also be possible
for learners to interact with their peers even if they were a
thousand miles apart from each other.
• Hadley Ferguson (Edcamp Foundation) states that learners
can actually use such technology in order to interact with
their trainers as well as famous authors, experts, and
scientists, whose books they may be reading for that training
module.

39. COULD AI TRAIN HUMANS?
• Yes, it’s similar to many of the AI aids we now use e.g. Google
Maps. It’s possible that AI could train humans. The training that AI
can provide will result in humans learning more difficult and
creative jobs.
• A few companies are now on the path of making cloud-based
training programs possible. They have done this by simply
gathering massive amounts of data on one subject and
categorized the data so that the data becomes a training tool.
• This AI training is not done in a training room with other learners,
but is one that ‘’listens in’’ on conversations, such as sales and
make recommendations to the ‘’learner’ about better words to
use, suggests alternate tasks and makes other recommendation
that will make sales more likely.

40. COULD AI REPLACE TRAINERS?
• Experts such as Shannon May, who has founded the Bridge
International Academies, say that technology would never drive
trainers completely out of the fray.
• A more likely scenario, would be trainers, skilled in the ways of
using technology, driving the usage of AI based on the needs of
their learners.
• Education technology, such as AI would be used more to
supplement the best ways of teaching and learning that exist
already.
• Jake Schwartz, co-founder and CEO of General Assembly, states
that there is no way that going online completely is going to solve
all the problems with corporate education now - the human factor
would always be important.

41. CASE STUDY: CHATBOTS IN LEARNING
(MIT AND FREEMAN)
• MIT Media Lab startup, GiantOtter is using AI to develop and train a bot, Coach Otto, to
provide online coaching for companies.
• An employer can use a chatbot to participate in an extended conversation as a coach or
companion amplifying a person’s ability to do their job.
• In the case of Coach Otto, this is preparing a manager to have a difficult conversation with a
team member.
• Chatbots are also being used as a learning reinforcement following a traditional training
program.
• This is the case with Freeman, a brand experience company. Freeman trains its sales staff on
the basics of selling with a course called Selling Fundamentals. But Freeman needed a
reinforcement strategy to help sales people apply sales skills on-the-job.
• Their solution: Coach TopGun SellFun, a chatbot designed to improve the retention of new
skills from the Selling Fundamentals program.

42. LEVELS OF LEARNING EVALUATION

43. HOW AI IS IMPACTING ON
LEARNING EVALUATION
• It's important for L&D management to identify
useful metrics that can guide upskilling efforts.
• Efficiency (level 1) and effectiveness (level
2): Machine learning is intended to enable the
ability to track real-time program efficiency and
effectiveness, thereby conserving resources and
reducing training investment costs.
• Behavioural change – level 3 (transfer of learning) -
With AI, you can use the built-in testing
mechanisms to judge just how focused your
workers are on the content. This data can be used
to continue motivating employees through inner-
office rankings. Refer to Mindmarker.

44. MINDMARKER
• Refer to
https://mindmarker.
com/how-
mindmarker-works/

45. HOW AI IS IMPACTING ON LEARNING
EVALUATION
• Impact (level 4): Upskilling employees through machine
learning platforms is intended to improve targeted
performance outcomes, both in terms of inspiring
measurable positive people impact and driving
demonstrable value creation for the business.
• Prediction and prescription (level 5) - leading indicators can
be used to improve the probability of success by making
corrections going forward, rather than by looking back and
using historical lessons that may not apply.
• It could also be used to identify which workers meet the
criteria for a promotion.

46. MONITORING LEARNER PERFORMANCE
• AI makes it a lot easy for L&D management to keep track of
how well or poorly the learners are performing.
• Such systems can be used to deal effectively with the vast
volume of data and statistics that these institutions normally
have.
• They can use these to create definite reports that help them
understand the progress being made by various learners.
• The best part of all this is that such reports can be created as
many times as needed.
• The quality of data can be enhanced as well.

47. HOW AI IS IMPACTING ON LEARNING ASSESSMENT AND
LEARNER PERFORMANCE
• These days, machines have become a lot more
advanced than what they were earlier. They are
now capable of performing a lot more than just
assessing an examination by using an answer key.
• They are capable of compiling data regarding how
learners have been performing.
• They can also assess assignments that are as
subjective as essays.

48. HOW AI IS IMPACTING ON
QUALITY ASSURANCE
• AI has the capacity to find out gaps in course
content on the basis of how learners are
performing in the assessments.
• AI can actually look into patterns and see if certain
information or concepts are missing from the
program’s curriculum or not.
• This, in turn, can help learning designers provide
better materials or use better methods of learning
so that learners can improve in those areas.

49. CONCLUSION
• Key points
• Summary
• Question and
Answer session

50. LIST OF SOURCES
• Bersin, J. 2017. The Disruption of Digital Learning: Ten Things We Have Learned.
• Cotter, C.A. 2017. Transforming learning and development into a strategic, value-adding
business solution: A conceptual and business-minded framework. NWU. PhD research.
https://www.slideshare.net/CharlesCotter/charles-cotters-phd-research-findings-
recommendationsstrategic-ld
• Cotter, C.A; Gerber, P.D. & Schutte, N. 2018. Proceedings of AC 2018 in Prague, pg. 142-149,
Academic Conferences Association, Czech Technical University, ISBN 978-80-88085-20-1
• Deloitte Consulting LLP. 2018. Global human capital trends report for South Africa 2018.
Oakland, CA: Deloitte University.
• https://elearningindustry.com/future-artificial-intelligence-in-elearning-systems
• https://fedena.com/blog/2018/03/artificial-intelligence-in-education-how-it-improves-the-
leaning-experience.html
• https://www.forbes.com/sites/jeannemeister/2018/01/11/ai-plus-human-intelligence-is-
the-future-of-work/#11fab8042bba

51. LIST OF SOURCES
• LinkedIn Learning Solutions. 2018. 2018 Workplace Learning Report: The
Rise and Responsibility of Talent Development in the New Labour Market.
• https://searchhrsoftware.techtarget.com/feature/How-AI-and-machine-
learning-help-in-upskilling-employees
• https://www.thetechedvocate.org/artificial-intelligence-is-the-future-of-
corporate-
education/?utm_source=ReviveOldPost&utm_medium=social&utm_campai
gn=ReviveOldPost
• https://www.techfunnel.com/hr-tech/future-of-ai-in-corporate-training-
and-development/
• https://trainingindustry.com/articles/learning-technologies/the-impact-of-
ai-on-learning-and-development/

52. CONTACT DETAILS
• Dr. Charles Cotter
• (+27) 84 562 9446
• charlescot@polka.co.za
• LinkedIn
• Twitter: @Charles_Cotter
• https://www.facebook.com/CharlesACotter/
• http://www.slideshare.net/CharlesCotter