Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

How artificial intelligence is revolutionizing learning and development practices throughout the addie value chain


Published on

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

Published in: Business
  • Have you ever heard of taking paid surveys on the internet before? We have one right now that pays $50, and takes less than 10 minutes! If you want to take it, here is your personal link ●●●
    Are you sure you want to  Yes  No
    Your message goes here
  • Just got my check for $500, Sometimes people don't believe me when I tell them about how much you can make taking paid surveys online... So I took a video of myself actually getting paid $500 for paid surveys to finally set the record straight. I'm not going to leave this video up for long, so check it out now before I take it down! 
    Are you sure you want to  Yes  No
    Your message goes here
  • Thanks for the acknowledgement Orestes and Venu - much appreciated.
    Are you sure you want to  Yes  No
    Your message goes here

How artificial intelligence is revolutionizing learning and development practices throughout the addie value chain

  2. 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
  3. 3. 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. 6. 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)
  8. 8. 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
  9. 9. 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).
  10. 10. 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.
  11. 11. 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.
  12. 12. 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.
  13. 13. 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.
  14. 14. 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.
  15. 15. 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.
  16. 16. 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.
  17. 17. 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.
  18. 18. 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.
  19. 19. 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.
  21. 21. 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.
  22. 22. 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.
  23. 23. 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.
  24. 24. 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.
  25. 25. 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.
  26. 26. 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) • e/5-reasons-why-virtual- reality-related-devices-unlikely- charles-cotter/
  27. 27. 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.
  28. 28. 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."
  29. 29. 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.
  30. 30. 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.
  31. 31. 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.
  32. 32. 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.
  33. 33. 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.
  35. 35. 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.
  36. 36. MINDMARKER • Refer to https://mindmarker. com/how- mindmarker-works/
  37. 37. 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.
  38. 38. 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.
  39. 39. 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.
  40. 40. 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.
  41. 41. CONCLUSION • Key points • Summary • Question and Answer session
  42. 42. 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. 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. • • leaning-experience.html • the-future-of-work/#11fab8042bba
  43. 43. LIST OF SOURCES • LinkedIn Learning Solutions. 2018. 2018 Workplace Learning Report: The Rise and Responsibility of Talent Development in the New Labour Market. • learning-help-in-upskilling-employees • corporate- education/?utm_source=ReviveOldPost&utm_medium=social&utm_campai gn=ReviveOldPost • and-development/ • ai-on-learning-and-development/
  44. 44. CONTACT DETAILS • Dr. Charles Cotter • (+27) 84 562 9446 • • LinkedIn • Twitter: @Charles_Cotter • •