From DSC: Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.
AI Policy 101: a Beginners’ Framework — from drphilippahardman.substack.com by Dr. Philippa Hardman How to make a case for AI experimentation & testing in learning & development
The role of learning & development
Given these risks, what can L&D professionals do to ensure generative AI contributes to effective learning? The solution lies in embracing the role of trusted learning advisors, guiding the use of AI tools in a way that prioritizes achieving learning outcomes over only speed. Here are three key steps to achieve this:
1. Playtest and Learn About AI… 2. Set the Direction for AI to Be Learner-Centered…
3. Become Trusted Learning Advisors…
In the last year, AI has become even more intertwined with our education system. More teachers, parents, and students are aware of it and have used it themselves on a regular basis. It is all over our education system today.
While negative views of AI have crept up over the last year, students, teachers, and parents feel very positive about it in general. On balance they see positive uses for the technology in school, especially if they have used it themselves.
Most K-12 teachers, parents, and students don’t think their school is doing much about AI, despite its widespread use. Most say their school has no policy on it, is doing nothing to offer desired teacher training, and isn’t meeting the demand of students who’d like a career in a job that will need AI.
The AI vacuum in school policy means it is currently used “unauthorized,” while instead people want policies that encourage AI. Kids, parents, and teachers are figuring it out on their own/without express permission, whereas all stakeholders would rather have a policy that explicitly encourages AI from a thoughtful foundation.
There is much discourse about the rise and prevalence of AI in education and beyond. These debates often lack the perspectives of key stakeholders – parents, students and teachers.
In 2023, the Walton Family Foundation commissioned the first national survey of teacher and student attitudes toward ChatGPT. The findings showed that educators and students embrace innovation and are optimistic that AI can meaningfully support traditional instruction.
A new survey conducted May 7-15, 2024, showed that knowledge of and support for AI in education is growing among parents, students and teachers. More than 80% of each group says it has had a positive impact on education.
How Humans Do (and Don’t) Learn— from drphilippahardman.substack.com by Dr. Philippa Hardman One of the biggest ever reviews of human behaviour change has been published, with some eye-opening implications for how we design & deliver learning experiences
Excerpts (emphasis DSC):
This month, researchers from the University of Pennsylvania publishedone of the biggest ever reviews of behaviour change efforts– i.e. interventions which do (and don’t) lead to behavioural change in humans.
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Research into human behaviour change suggests that, in order to impact capability in real, measurable terms, we need to rethink how we typically design and deliver training.
The interventions which we use most frequently to behaviour change – such as video + quiz approaches and one off workshops – have a negligible impact on measurable changes in human behaviour.
For learning professionals who want to change how their learners think and behave, this research shows conclusively the central importance of:
Shifting attention away from the design of content to the design of context.
Delivering sustained cycles of contextualised practice, support & feedback.
The Magic of Storytelling: Lessons from Penn Jillette — from learningguild.com by David Kelly This fall we’re celebrating 20 Years of DevLearn. As part of that celebration, I’m reflecting on the insights I’ve gained from some of my favorite DevLearn keynote speakers over the years. I kick off this series by revisiting The Magic of Storytelling and Learning from Penn Jillette, from DevLearn 2016.
At the heart of Jillette’s message is the power of storytelling. He demonstrates that, much like a magician’s performance, effective learning experiences are crafted from engaging narratives. These stories, although selectively told, can ethically captivate and teach, making the learning process more impactful. Jillette’s career itself is a story of transformation and adaptation, one that resonates deeply with the ongoing journey of a learning professional.
Complementing these conversational approaches are learning experiences enhanced with AI. I highlighted the fast-growing role of immersive scenarios and simulations, produced in tandem with AI and powered through AI in their delivery.
Moreover, the integration of voice interactions, advanced image processing, and augmented reality (AR) and virtual reality (VR) technologies provides additional tools to enrich learning experiences.
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The rapid adoption of AI signifies a real shift for our industry, and we are able to see sparks of what is coming our way throughout 2024 and beyond.
Practicing difficult conversations One of the most compelling applications I’ve seen lies in managerial and leadership training, specifically in navigating complex interpersonal dynamics: practicing difficult conversations. Through interactions with sophisticated avatars capable of mimicking a diverse range of employee personalities and behaviors, learners can engage in realistic scenarios that challenge their communication skills.
Table 1. Most Important Transferable Skills 2024–2028
Transferable Skill
Description
Problem-solving
The ability to identify, analyze, and solve complex problems.
Critical thinking
The ability to think objectively, analyze information, and form sound judgments.
Communication (written & verbal)
The ability to effectively convey ideas and information to others, both in writing and verbally.
Collaboration
The ability to work effectively with others to achieve a common goal.
Creativity & innovation
The ability to think creatively and come up with new ideas and solutions.
Digital literacy & competency
The ability of everyone from CEO to workers to use digital tools and technologies effectively.
Data analysis & interpretation
The ability to collect, analyze, and interpret data to draw meaningful conclusions.
Self-directed learning & adaptability
The ability to take initiative to learn new things and adapt to change.
Time management & organization
The ability to manage time effectively and stay organized.
Emotional intelligence & empathy
The ability to understand and manage one’s own emotions, and the emotions of others.
Also for the L&D world, see:
When Business Is Just a Game — from bloomberg.com by Robb Mandelbaum Corporate trainer Abilitie uses simulations to teach lessons in management.
When is the high-stakes, high-pressure world of the C-suite just a game? When executives at emerging companies Compuline and Nanotel met on a Wednesday evening in May to manage existing products and roll out new ones, that’s exactly what it was. The “executives” were students in…
Summary:
Most corporate learnings aren’t cutting it. Almost 60% of employees say they’re interested in upskilling and training, but 57% of workers also say they’re already pursuing training outside of work. The author, the former Head of Innovation and Creativity at Disney, argues that creativity is the missing piece to make upskilling engaging and effective. From his experience, he shares four strategies to unlock creativity in trainings: 1) Encourage “What if?”, 2) respond “How else?” to challenges, 3) give people time to think by encouraging playfulness, and 4) make training a game.
[Report] The Top 100 AI for Work – April 2024 — from flexos.work; with thanks to Daan van Rossum for this resource AI is helping us work up to 41% more effectively, according to recent Bain research. We review the platforms to consider for ourselves and our teams.
Following our AI Top 150, we spent the past few weeks analyzing data on the top AI platforms for work. This report shares key insights, including the AI tools you should consider adopting to work smarter, not harder.
While there is understandable concern about AI in the work context, the platforms in this list paint a different picture. It shows a future of work where people can do what humans are best suited for while offloading repetitive, digital tasks to AI.
This will fuel the notion that it’s not AI that takes your job but a supercharged human with an army of AI tools and agents. This should be a call to action for every working person and business leader reading this.
Most leaders understand the value of investing in an onboarding process for orientation, productivity, and retention, but few associate onboarding with strong performance over the employee’s full tenure with the organization. By contrast, everboarding is a newer approach that prioritizes ongoing learning and development rather than only an initial commitment. Insights from Deloitte indicate organizations that establish an ongoing learning culture are 52 percent more productive with engagement and achieve retention rates 30–50 percent higher than those that don’t.
When implemented effectively, everboarding embraces proven elements of a coaching culture that establish an ongoing commitment to skill development, deepens understanding of the organization, and supports real-time feedback to prevent stagnancy in high-potential employees brought in through strong hiring practices.
What if, for example, the corporate learning system knew who you were and you could simply ask it a question and it would generate an answer, a series of resources, and a dynamic set of learning objects for you to consume? In some cases you’ll take the answer and run. In other cases you’ll pour through the content. And in other cases you’ll browse through the course and take the time to learn what you need.
And suppose all this happened in a totally personalized way. So you didn’t see a “standard course” but a special course based on your level of existing knowledge?
This is what AI is going to bring us. And yes, it’s already happening today.
“Knowing is not enough; we must apply. Willing is not enough; we must do.”
Johann Wolfgang von Goethe
Learning Transfer’s ultimate outcome is behaviour change, so we must understand the conditions that trigger a behaviour to start.
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According to Fogg, three specific elements must converge at the same moment for a specific behaviour to occur. Given that learning transfer is only successful when the learner starts behaving in the desired new ways, Fogg’s work is critical to understanding how to generate these new behaviours. The Fogg Behavioural Model [*1] states that B=MAP. That is, a specific behaviour will occur if at the same moment there is sufficient motivation, sufficient ability and sufficient prompt. If the behaviour does not occur, at least one of these three elements is missing or below the threshold required.
The prompt is, in effect, a call to action to do a specific behaviour. The prompt must be ‘loud’ enough for the target person to perceive it and be consciously aware of it. Once aware of a prompt, the target immediately, and largely unconsciously, assesses their ability to carry out the requested behaviour: how difficult would this be, how long will it take, who can help me, and so on. They base this on their perception of the difficulty of the requested behaviour, and their ability, as they see it, to achieve that behaviour.
Over the past year, many excellent and resourceful books have crossed my desk or Kindle. I’m rounding them up here so you can find a few to expand your horizons. The list below is in alphabetical order by title.
Each book is unique, yet as a collection, they reflect some common themes and trends in Learning and Development: a focus on empathy and emotion, adopting best practices from other fields, using data for greater impact, aligning projects with organizational goals, and developing consultative skills. The authors listed here are optimistic and forward-thinking—they believe change is possible. I hope you enjoy the books.
Outside of practicing their learning, there are many challenges to creating and delivering meaningful workplace L&D programs. Participants are busy and may struggle to free up even an hour or two on their calendars. Training could be delivered in the wrong format or at the wrong time. After they attend the training, they may not have an opportunity to apply what they have learned. This can lead to some participants not perceiving training as time well spent. As L&D professionals, our job is to create learning experiences that are meaningful and relevant to people’s day-to-day work.
Adults learn best when training is delivered when it is most relevant to their work, and they can apply what they have learned right away. They must be able to connect what they are learning with the work they are doing and the overarching goals and strategies of the organization.
One possible solution is to implement a microlearning strategy into workplace learning programs. In this article, I will discuss reasons why microlearning can be an effective tool in the L&D toolkit, things to think about when creating a microlearning strategy, cost-effective technology solutions to leverage and ideas to help your microlearning strategy feel exciting and engaging for your participants.
The AI era is here, and leaders across learning and talent development have a new mandate: help people and organizations rise to opportunity with speed and impact.
As AI reshapes how people learn, work, and chart their careers, L&D sits at the center of organizational agility, delivering business innovation and critical skills. This report combines survey results, LinkedIn behavioral data, and wisdom from L&D pros around the globe to help you rewrite your playbook for the future of work.
Accenture announced today that it would acquire the learning platform Udacity as part of an effort to build a learning platform focused on the growing interest in AI. While the company didn’t specify how much it paid for Udacity, it also announced a $1 billion investment in building a technology learning platform it’s calling LearnVantage.
“The rise of generative AI represents one of the most transformative changes in how work gets done and is driving a growing need for enterprises to train and upskill people in cloud, data and AI as they build their digital core and reinvent their enterprises,” Kishore Durg, global lead of Accenture LearnVantage said in a statement.
1. AI already plays a central part in the instructional design process A whopping 95.3% of the instructional designers interviewed said they use AI in their day to day work. Those who don’t use AI cite access or permission issues as the primary reason that they haven’t integrated AI into their process.
2. AI is predominantly used at the design and development stages of the instructional design process
When mapped to the ADDIE process, the breakdown of use cases goes as follows:
Analysis: 5.5% of use cases
Design: 32.1%
Development: 53.2%
Implementation: 1.8%
Evaluation: 7.3%
Speaking of AI in our learning ecosystems, also see:
The majority of educators expect use of artificial intelligence tools will increase in their school or district over the next year, according to an EdWeek Research Center survey.
Applying Multimodal AI to L&D — from learningguild.com by Sarah Clark We’re just starting to see Multimodal AI systems hit the spotlight. Unlike the text-based and image-generation AI tools we’ve seen before, multimodal systems can absorb and generate content in multiple formats – text, image, video, audio, etc.
“The world is adapting to seismic shifts from generative AI,” says Luben Pampoulov, Partner at GSV Ventures. “AI co-pilots, AI tutors, AI content generators—AI is ubiquitous, and differentiation is increasingly critical. This is an impressive group of EdTech companies that are leveraging AI and driving positive outcomes for learners and society.”
Workforce Learning comprises 34% of the list, K-12 29%, Higher Education 24%, Adult Consumer Learning 10%, and Early Childhood 3%. Additionally, 21% of the companies stretch across two or more “Pre-K to Gray” categories. A broader move towards profitability is also evident: the collective gross and EBITDA margin score of the 2024 cohort increased 5% compared to 2023.
Selected from 2,000+ companies around the world based on revenue scale, revenue growth, user reach, geographic diversification, and margin profile, this impressive group is reaching an estimated 3 billion people and generating an estimated $23 billion in revenue.
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