In this episode, Robin speaks with JD Dillon about the impact of AI on the future of work, and the importance of not being short-sighted with this technology. There is an ever-increasing need for critical thinking, and trust, transparency, and collaboration are key factors in AI adoption. JD encourages L&D professionals to engage with stakeholders and align their strategies with the organisation's vision for AI. About JD DillonJD Dillon is the founder of LearnGeek, where he helps organisations rethink how they enable their employees. Over the past 20 years, he has worked with some of the world's most dynamic brands, including Disney, Kaplan, AMC and Axonify. Today, he is the world's foremost expert on frontline learning and engagement as well as a prolific author and speaker in the global HR and L&D communities.Key takeaways:AI represents a significant shift in our relationship with technology, comparable to the introduction of the internet and mobile devices. It’s not about the quick-win – organisations need to see things long-term and should consider how it can fundamentally transform work processes and tasks.Trust and transparency are crucial for successful AI adoption: organisations must address data quality and knowledge management practices to establish trust in AI systems. L&D professionals should actively engage with stakeholders and align their strategies with the organisation's vision for AI-enabled technology.It is the perfect time to discuss how we can shape the future of work. Organisations need to actively participate in defining how AI supports work and learning, ensuring that it enhances productivity, decision-making, and overall employee experiences. The integration of AI in the workplace requires a balance between automation and human decision-making, and critical thinking will remain crucial in assessing AI-generated contentChapters:(00:00:00) Introduction.(00:02:43) What AI means for the future of work.(00:07:47) What AI means to be human.(00:10:39) What is L&D’s role in AI technology?(00:15:32) Why trust in technology is crucial for future success.(00:19:38) Skills in trust, critical thinking, and human decision-making.(00:23:29) JD’s greatest gem of wisdom when it comes to AI and L&D. Links from the podcast Connect with JD on LinkedInVisit JD’s WebsiteListen to JD’s interview about continuous learningListen to JD’s interview about modern learning ecosystems 

This is the start of a series on AI in L&D.  The series is exploring what people are doing now with AI, what people are thinking about, and what people are learning.In this episode, we kick off the series where Robin does an interview with ChatGPT on transforming learning at work. The voice is generated by ElevenLabs.If you are interested, it might be easier to read the blog post along with the podcast, than listening to the computer generated voice.Key takeaways:Promoting self-guided learning and automation in instructional design can contribute to a culture of continuous learning. Automation can be used in instructional design to automate routine tasks and increase efficiency, such as AI automating content curation, learner data analysis, and feedback collection and analysis.There are risks and considerations to be aware of when using AI. These include the dangers of dependency on AI, the digital divide in access to AI tools, ethical concerns regarding biassed information, and the importance of data privacy. To address these risks, organisations should comply with data privacy laws, implement quality control measures, balance AI with human-led learning experiences, and provide training and support for employees who are not comfortable with technology.Strategies for using AI in workplace learning include having human mentors or instructors for discussions and social learning opportunities, providing training and support for employees who are not comfortable with technology, and incorporating ethical considerations when choosing AI providers.Chapters:(00:00:00) Introduction.(00:01:58) AI in workplace learning.(00:05:35) Adaptive learning experience pathways.(00:08:15) On-demand learning for safety leadership.(00:11:41) Content curation and updates.(00:16:07) The risks of using AI in L&D.(00:21:33) The role of humans and AI in the workplace.(00:24:53) Balancing the use of AI.Links from the podcast Check out ElevenLabsTranscript:Robin: Act as an expert on L&D and learning. You're going to be a guest on the Learning While Working podcast. The audience is workplace L&D professionals. The interview is going to talk about how you (chatGPT) can transform learning at work. I'm going to ask you questions.ChatGPT: Sure, I'd be happy to participate in this mock podcast interview. Feel free to start with your questions.Please remember that while I can provide useful and insightful information, I'm an AI model developed by OpenAI and my responses are based on patterns in the data I was trained on, up until September 2021. Any information or insights I provide should be validated and adapted to your specific context.Robin: Welcome to the Learning While Working podcastChatGPT: Thank you for having me on the Learning While Working podcast. It's an exciting opportunity to connect with the L&D community. As an AI developed by OpenAI, I aim to provide insights and information that can help transform learning at work. Let's get started!Robin: What are 3 ways you transform learning at work?ChatGPT: AI, such as myself, can help to transform learning at work in various ways. Here are three significant ways:Personalised Learning: One of the biggest challenges in workplace learning is meeting the diverse needs of learners. AI can analyse an individual's learning style, previous knowledge, and performance data to deliver personalised learning experiences. For instance, based on a learner's progress, AI can recommend next steps, additional resources, or even a change in learning strategy to improve outcomes.On-Demand Learning: The traditional model of set training times and classrooms isn't flexible or scalable, especially in a world where remote work is increasingly common. AI can provide on-demand learning, allowing employees to learn at their own pace, anytime and anywhere. This is especially useful for quickly updating employees on new tools, policies, or industry developments.Automation of Routine Tasks: A lot of L&D professionals spend considerable time on administrative tasks like scheduling training sessions, tracking progress, and generating reports. AI can automate these routine tasks, allowing L&D professionals to focus more on strategic tasks such as designing better learning experiences and interventions.These are just a few examples of how AI can help. The actual impact will depend on the organisation, its culture, and its readiness to leverage AI in learning and development.Robin: Give me three examples of Personalized Learning?ChatGPT: Certainly, personalised learning through AI can take many forms. Here are three specific examples:Adaptive Learning Paths: AI can create adaptive learning paths based on each learner's knowledge level, skills, and learning speed. For instance, if an employee is already proficient in certain areas, the AI can automatically adjust their learning pathway to focus on areas where they need improvement. This avoids wasting time on content they already know and focuses on developing areas where they need growth.Recommendation Systems: Similar to how Netflix or Amazon recommends movies or products based on past behaviour, an AI can recommend learning resources based on a user's past learning behaviour and performance. For example, if a user struggled with a particular concept, the AI might suggest additional resources, such as videos or articles, to reinforce their understanding.Learning Style Adaptation: AI can adapt the format of the content to match the learner's preferred style. For example, some people learn better through visual materials like infographics and videos, while others prefer text-based resources or interactive simulations. AI can track how users interact with different types of content and then prioritise delivering content in the formats that work best for them.In all these ways, AI can help create a personalised, more engaging, and effective learning experience for each individual.Robin: You're being a bit vague. Give me and example of using ChatGPT for Adaptive Learning Paths for cybersecurity skills.ChatGPT: Certainly, let's take a more detailed look at how ChatGPT could be utilised for creating an adaptive learning path in the field of cybersecurity.Suppose an employee, let's call her Jane, is tasked with improving her cybersecurity skills. After an initial assessment or quiz, it's clear that Jane has a strong understanding of basic concepts such as types of threats and fundamental security protocols, but she struggles more with advanced topics like incident response management and network security.Initial Assessment: In this scenario, ChatGPT could begin by providing an interactive assessment, where Jane answers questions or solves problems related to various aspects of cybersecurity. This could involve everything from basic concepts to more advanced ones.Custom Learning Pathway: Based on Jane's performance on the assessment, ChatGPT identifies her strengths and weaknesses. Since she already has a strong understanding of basic concepts, the AI doesn't include these topics in her learning pathway. Instead, it prioritises advanced topics like incident response management and network security.Learning Delivery and Continuous Assessment: As Jane moves through her personalised learning pathway, she interacts with ChatGPT in a conversational manner, discussing cybersecurity scenarios, answering quiz questions, and solving problems related to her learning topics. ChatGPT adjusts the complexity and depth of the content based on Jane's progress.Regular Feedback and Adjustments: Throughout this process, Jane receives instant feedback on her progress, which helps her understand where she stands and how she's improving. If Jane is struggling with a certain topic, ChatGPT might choose to slow down, provide additional learning resources, or approach the topic from a different angle.In this way, ChatGPT can provide a flexible, responsive learning experience that adapts to Jane's needs, ensuring she focuses on the areas where she needs to grow most.This approach not only saves time by avoiding unnecessary repetition of known topics but also promotes engagement and effective learning by focusing on areas of need and providing instant feedback.Robin: This is good. How about an example for On-Demand Learning for safety leadershipChatGPT: Absolutely. Here's how ChatGPT could provide on-demand learning for an area such as safety leadership:Let's consider a manager, we'll call him John, who has been tasked with improving his safety leadership skills to better lead his team in a manufacturing environment. John works on a tight schedule and he often can't participate in traditional training programs during usual business hours.24/7 Availability: Since ChatGPT is an AI, it is available 24/7. John can interact with the training program whenever he has time, be it early in the morning before his shift starts, or late in the evening after he finishes his work. He doesn't have to wait for a scheduled training session.Learning in Context: Suppose a specific situation arises at work that John is unsure how to handle from a safety leadership perspective, like responding to a safety incident. He could immediately consult with ChatGPT, asking specific questions to learn how to best handle the situation. ChatGPT could provide guidance based on best practices in safety leadership, and provide resources for deeper learning.Role-Playing Simulations: On-demand learning isn't just about reading material or answering quiz questions. For example, John could engage in a role-playing scenario with ChatGPT at any time, where he has to navigate a simulated safety incident, make decisions and respond to changes. This on-the-spot, interactive learning can be highly effective for building practical skills.Just-In-Time Learning: If a new safety regulation or procedure is implemented, John can immediately get the necessary training from ChatGPT. It can provide an overview of the new rule, explain its implications, and even quiz John to ensure he has understood the change.This kind of on-demand learning can be particularly effective because it is self-paced, flexible, and contextual. It allows learners to get the knowledge when they need it, apply it immediately, and therefore, they are more likely to retain it.Robin: Is this key to type experience making sure employees are self guided learners?ChatGPT:Yes, fostering a culture of self-guided learning is a key aspect of successful implementation of AI-driven personalised and on-demand learning. Here's why:Ownership of Learning: When employees are self-guided learners, they take ownership of their learning journey. This makes the learning process more effective because they are actively seeking knowledge, rather than passively receiving it.Pace and Style: Self-guided learners can set their own pace and choose their preferred style of learning. This flexibility can lead to more engagement and better absorption of knowledge.Immediate Application: Self-guided learners can immediately apply what they've learned to their work, which can reinforce their learning and demonstrate its practical relevance.Continuous Learning Culture: Promoting self-guided learning can contribute to a culture of continuous learning. In today's rapidly changing work environment, continuous learning is crucial for businesses to stay competitive and for employees to keep their skills up-to-date.However, it's important to note that not everyone may be used to or comfortable with self-guided learning. In these cases, organisations can provide support and guidance to help employees become more self-directed learners. This could include training on how to use AI learning tools, creating clear learning paths for skills development, and providing mentors or coaches to guide learners.Robin: Getting those top 3 things. How could an instructional designer use Automation of Routine Tasks?ChatGPT: Absolutely. There are several routine tasks within instructional design that can be automated with AI, which can greatly increase efficiency and allow instructional designers to focus more on the creative and strategic aspects of their work. Here are three specific examples:Content Curation and Update: AI can automate the process of sourcing, organising, and updating learning content. For example, an AI could crawl the web or a specific database to find relevant articles, videos, or research papers for a particular course topic. It can also regularly check for updates or newer versions of the existing learning content and replace outdated materials.Learner Data Analysis: AI can automate the analysis of learner data to provide insights into learning behaviours and performance. For instance, AI could automatically generate reports on learner engagement, quiz performance, areas of struggle, and more. This allows instructional designers to quickly and efficiently evaluate the effectiveness of their courses and make data-driven improvements.Feedback Collection and Analysis: Collecting and analysing learner feedback is an important but time-consuming task. AI can automate this process by prompting learners for feedback at optimal times (like after a course completion), collating the feedback, and analysing it to provide actionable insights. It could categorise feedback into themes, identify common issues, and even suggest potential improvements.By automating these tasks, instructional designers can save significant time and focus more on designing effective, engaging learning experiences. Additionally, the insights provided by AI can inform their design decisions, leading to more effective learning outcomes.Robin: How about for content creation?ChatGPT: AI can indeed assist with content creation in a variety of ways, which can be particularly useful for instructional designers. Here are a few examples:AI-Powered Writing Assistants: Tools like ChatGPT can assist in drafting course content. Given an outline or a set of key points, AI can generate draft content, which can then be edited and refined by instructional designers. This can speed up the content creation process, especially for first drafts or when creating content in a specific area of expertise.Content Optimization: AI can analyse content and suggest improvements based on best practices. For example, it might suggest simplifying complex sentences, adding more visuals, or including quizzes and interactive elements at certain intervals to boost engagement and retention.Translation and Localization: If content needs to be provided in multiple languages, AI-powered translation tools can be used to translate the content. Additionally, AI can help localise content, i.e., adapt the content to fit the cultural, societal, and linguistic context of different learner groups.Creating Interactive Content: AI can help create interactive content such as quizzes, simulations, or even chatbots for role-playing scenarios. Instructional designers can input the learning objectives and key points, and the AI can generate appropriate interactive content.It's important to note that while AI can assist in content creation, the role of instructional designers remains crucial. They provide the human touch, the deep understanding of learner needs, and the creativity that AI cannot replicate. AI should be seen as a tool that can augment the capabilities of instructional designers, not replace them.Robin: What are some risks of using you for workplace learning?ChatGPT: Using AI like ChatGPT for workplace learning presents several opportunities but also comes with some risks. It's important to consider these potential challenges:Data Privacy: AI platforms often rely on data from users to provide personalised experiences. This can raise concerns about data privacy, particularly if sensitive information is involved. It's crucial to ensure that any AI used in the workplace complies with data privacy regulations and that users are informed about how their data is used.Quality Control: While AI can generate content and assist with learning, the quality of that content may not always meet the necessary standards. Misunderstandings or inaccuracies could lead to the dissemination of incorrect information, which could be particularly harmful in areas such as safety training or compliance.Dependency: There's a risk that organisations could become overly reliant on AI for learning and development, neglecting the importance of human interaction and guidance in the learning process. While AI can deliver information and even personalise learning to some extent, it can't replace the mentorship and social interaction that humans provide.Digital Divide: While AI can offer powerful tools for learning, not all employees may have equal access to these tools. For example, employees who are not comfortable with technology or who lack access to high-quality internet may not benefit as much from AI-based learning tools.Ethical Considerations: AI systems, including ChatGPT, are trained on vast amounts of data, which can include biassed or prejudiced information. Even though measures are taken to prevent it, these biases can sometimes influence the AI's output. This is a broader issue with AI and machine learning and something to be aware of when using AI tools.It's crucial for organisations to be aware of these risks and to implement strategies to mitigate them when using AI for workplace learning.Robin: Can we just drill into Data Privacy? What are your Data privacy features?ChatGPT: As an AI developed by OpenAI, I am designed with privacy in mind. Here are some key aspects to understand about how I handle data:No Personal Data Storage: As of my training cut-off in September 2021, I don't have the ability to access or retrieve personal data from users unless it's shared with me in the course of our conversation. I don't store personal conversations or use them to inform my responses.Temporary Data Retention: By default, OpenAI retains data passed to the ChatGPT API for 30 days, but doesn't use it to improve my models.Privacy by Design: From the outset, I've been designed to respect user privacy. For example, I don't ask for personal data unless it's strictly necessary for the conversation.However, it's important to note that the usage of AI tools should still comply with the organisation's data privacy policies and any local laws or regulations. You should always be clear with employees about how their data is being used, and make sure you have their consent before using AI tools in a learning context.As data privacy is a dynamic field with constantly evolving regulations and standards, it's crucial to regularly review and update your data privacy policies and practices.Robin: But doesn't mean you're losing opportunities for training data?ChatGPT: While it's true that retaining and using conversational data could potentially provide opportunities for refining and improving AI models, OpenAI has chosen not to use data from individual interactions with ChatGPT to improve the model in order to prioritise user privacy and confidentiality.This decision reflects an important balance in AI development between improving the system and ensuring user trust. Given that AI systems like me are often used in contexts where sensitive or private information might be discussed, ensuring that users feel safe and confident that their data won't be used without their explicit permission is a critical priority.It's worth noting, though, that overall improvements in the model, which are based on extensive and diverse datasets, will continue to enhance the effectiveness and accuracy of the AI, benefiting all users.Robin: Going back to the risks you talked about, how can we overcome those risks?ChatGPT: Addressing these risks requires thoughtful planning and implementation. Here are some suggestions:Data Privacy: Ensure any AI tool used complies with all relevant data privacy laws and regulations, such as GDPR in Europe. Implement robust data protection measures, and be transparent with users about what data you collect, why you collect it, and how you use and protect it.Quality Control: Don't rely solely on AI for creating and delivering content. Always have a human in the loop to review and validate the information. Regularly test the system and provide opportunities for users to give feedback or report errors.Dependency: Balance the use of AI with human-led learning experiences. AI is a tool to supplement and enhance learning, not replace human guidance and interaction. For example, you might use AI for delivering content and personalising learning paths, but still have human mentors or instructors for discussions, mentoring, and social learning opportunities.Digital Divide: Provide training and support for employees who are not comfortable with technology. This might include basic digital literacy training or one-on-one support. Make sure your learning experiences are accessible on different devices and internet speeds, and where necessary, provide alternative, non-digital learning options.Ethical Considerations: Choose AI providers who are transparent about their training data and methods and who actively work to minimise and address bias. Incorporate ethical considerations into your AI strategy and continuously monitor and evaluate the AI's output for potential bias or ethical issues.These strategies can help mitigate the risks of using AI in workplace learning. However, each organisation's situation is unique, so it's important to continually assess and address risks in your specific context.Robin: In the past I’ve talked about how AI means that humans need to focus on the 3 things that AI can't do, Create, Collaborate and Change. What are your thoughts on this?ChatGPT: You've highlighted a critical perspective on the interaction between humans and AI in the workplace, and particularly in learning and development. AI technology has made significant strides, but there remain areas where humans outperform any existing AI. Let's unpack the three Cs you've mentioned:Create: While AI can generate content, solve problems within a specified context, and even mimic some forms of creativity, it fundamentally lacks the ability to truly innovate or think outside of the box. Human creativity, which involves the generation of new ideas, unique insights, and novel solutions, remains unchallenged. In learning and development, this creativity plays a crucial role in designing engaging and effective learning experiences.Collaborate: AI can facilitate collaboration (for example, by coordinating schedules or organising tasks), but it cannot truly collaborate the way humans can. Human collaboration involves complex social interactions, empathetic understanding, negotiation, and the ability to build on each other's ideas in dynamic, unpredictable ways. Especially in a learning context, this ability to collaborate and learn from each other is a deeply human skill that AI cannot replicate.Change: AI can adapt to new data within a predefined framework, but it doesn't have the capacity for the kind of flexible, broad-spectrum change and adaptability that humans possess. Humans can change their beliefs, assumptions, behaviors, and strategies based on new experiences or insights, and this ability is key to learning and development.In the context of learning while working, humans should leverage AI for what it does best - managing large amounts of data, providing personalised content, offering on-demand support, and automating routine tasks. Meanwhile, human efforts can focus on these irreplaceable areas of creativity, collaboration, and change, which are at the heart of effective learning and development. This combination of AI's capabilities and the unique human skills can lead to a powerful, holistic approach to workplace learning.Robin: Now as the wrap questions what your greatest piece of advice about using ChatGPT is for learning while working?ChatGPT: When it comes to using ChatGPT or any AI in the learning while working context, the most important piece of advice I'd give is this: View AI as a tool that augments and enhances human-led learning, not as a replacement for it.AI tools like ChatGPT can offer great advantages in terms of personalising learning, providing on-demand support, and automating routine tasks. But they are not a silver bullet. The effectiveness of AI in learning and development depends greatly on how it's integrated into your broader L&D strategy.Here are a few key points to consider:Learner-Centric Approach: Focus on the learner. AI offers exciting possibilities, but ultimately, the goal is to create a better, more effective, more engaging learning experience for your employees. So always consider how the use of AI will benefit the learner.Blend with Human Interaction: Balance the use of AI with opportunities for human interaction and guidance. While AI can deliver content and personalise learning, it can't replace the mentorship, social learning, and human touch that are also crucial for effective learning.Ongoing Evaluation: Continually evaluate and adjust your approach. AI is a rapidly evolving field, so it's important to stay updated with new developments and be ready to adapt your strategies. Regularly solicit feedback from learners and use it to improve your AI-enhanced learning experiences.Training & Support: Provide training and support to help employees use AI tools effectively. Not everyone may be comfortable with technology, so it's important to help them understand how to use AI tools and how they can benefit from them.By keeping these principles in mind, organisations can leverage the power of AI to transform workplace learning, while still maintaining a human-centric approach that values and nurtures the unique capabilities of each individual learner.

In this episode, we are joined by guest JD Dillon to discuss his modern learning ecosystem framework and its importance in a constantly changing environment. Tune in as JD delves into tactics for influencing different departments, reinforcement and retention mechanisms, and why we need to eliminate the need for formal learning  About JD Dillon  JD Dillon strongly believes in the power of help. He is the founder of LearnGeek and helps organisations rethink how they enable their employees. Over the past 20 years, he has worked with some of the world's most dynamic brands, including Disney, Kaplan, AMC and Axonify. Today, he is the world's foremost expert on frontline learning and engagement as well as a prolific author and speaker in the global HR and L&D communities.Key takeaways:What ‘modern’ means in the Learning Ecosystem Framework: there is a vagueness of the term "modern”, and JD Dillon seeks to define it in his book. It’s about the importance of being prepared for change, and the need to establish flexible and agile systems and processes. It’s important to provide a stable foundation for a good experience despite the constantly changing environment.The importance of influence in building learning culture in organisations: There is a need for everyone in the organisation to prioritise learning. There are a number of tactics for influencing different departments and individuals to shift their mindset towards learning and development. Consider how to convince executives to adopt new ways of sharing information, and challenge outdated perspectives on learning and development.The integration of knowledge management, Learning & Development, and corporate communications: a curator in the organisation can help solve problems instead of prioritising departments. Explore how to incorporate information flow and solve systemic issues.Chapters:(00:00:00) Introduction.(00:01:46) Insights from his book 'The Modern Learning Ecosystem'.(00:04:44) A framework to help connect tools for learning solutions.(00:09:19) The disconnect in organisations hinders problem-solving and learning.(00:13:19) Differentiating shared knowledge vs. performance support.(00:17:46) How to influence everyone in the organisation.(00:24:00) Embracing learning as a constant, and why reinforcement is vital.(00:30:56) Replacing the word ‘Learning’ with ‘Helping’ in our job titles.Links from the podcast:Read the The Modern Learning Ecosystem - A New L&D Mindset for the Ever-Changing WorkplaceConnect with JD Dillon on LinkedInVisit the JD’s website Learning GeeksAnother Learning While Working podcast interview with JD Dillon on continuous learning and how it links with personalised learning

Episode SummaryAmanda Page is a change expert and coach. She works with leaders across different industries to accelerate change. She joins the show to discuss the possibilities of leading change in hybrid work environments. Tune in as we unpack strategies for change management, building a sense of belonging in the workplace, setting boundaries, and change management training.About Amanda Page  As a certified coach and change expert, Amanda supports leaders, teams and individuals who are seeking to unlock their passion and potential. She helps them find new ways, drop old habits and create new rituals that will create momentum and establish new rhythms for success. With a successful career in Fortune 100 high-tech organisations, she has also developed a keen understanding of the key levers needed to successfully transition and transform. She is the founder of Change Tempo, with a mission to make change easier for everyone.Key takeaways:How can leaders best navigate change? The principles of change leadership are about being very clear about the outcome of where everyone's going. If not, members of the team can feel isolated and unheard.It’s important to understand our stress response: The Change Cycle helps demonstrate the different stages of change. It brings an opportunity to be more proactive, creative, collaborate and engage with people.The role of Change Managers: they help everyone in the organisation build healthy relationships with change. It is an organisational change imperative where they go beyond just a presentation. People who are responsible for the change management plan need to focus as much on the change management plan for managers as they do for employees.Chapters:(00:00:00) Introduction.(00:01:53) The possibilities of leading with change.(00:05:01) Creating a sense of belonging when working remotely.(00:06:37) How to successfully navigate change in organisations.(00:11:35) Understanding people’s relationships with stress and change.(00:13:14) Addressing the gap many managers have in their capabilities around change.(00:19:48) Building equal relationships and the people-side of business.(00:22:55) What to do with unexpected change in the workplace.(00:26:26) How L&D managers can help support the change process.Links from the podcastConnect with Amanda Page on LinkedInDownload The 6 Trade Secrets that will transform how you lead changeThe Change Tempo websiteCheck out the The Change Cycle

Episode summary/descriptionIn this episode of the Learning While Working podcast we explore adaptive leadership with Greg Evans from the Nous Group. We will delve into the challenges organisations face in developing adaptive capabilities and how learning and development professionals can play a pivotal role in addressing these challenges. Greg shares his insights on designing effective learning experiences, fostering a culture of adaptability, and leveraging techniques like the case-in-point approach for meaningful growth.About Greg Evans    Greg Evans is currently a Principal at Nous Group, an international management consultancy with over 750 people operating across Australia, New Zealand, the UK, Ireland and Canada. He has experience in various sectors such as defence, education, health, financial services, resources, and emergency management.Key takeaways:Being adaptive requires organisations to internalise the need for change and equip themselves with the tools to identify the issues and hold a meaningful dialogue among stakeholders around change.The learning experience takes time and involves mobilising stakeholders who may be less powerful within the organisation. Take the teams out of the workplace, by running case-in-point approaches and workshops, to provide rich learning experiences that help provoke new ideas. Help individuals promote their own growth from the self-authoring to the self-transforming mindset.There is an emerging demand for developing adaptive capabilities and L&D experts can help provide early warning signs, ask powerful questions, and ultimately become the “unseen” stewards of learning within the organisation. Think about how you might build those capabilities for diagnosing and responding to adaptive challenges not just in your team, but across your organisation.Chapters:(00:00:00) Introduction.(00:01:46) What do we mean by organisations being adaptive?(00:05:16) How Nous Group are designing learning experiences.(00:10:17) Implementing the case-in-point approach.(00:13:46) The importance of debriefs.(00:16:34) How L&D can help people become more adaptive in their cultural behaviour.(00:23:06) Advice to L&D teams to be more adaptive themselves.Links from the podcast:Connect with Greg on LinkedInVisit Nous GroupRead the book The Practice of Adaptive Leadership: Tools and Tactics for Changing Your Organization and the World

Episode summary/descriptionRetrieval practice is a technique used in teaching as a way of getting people to generate ideas and think actively. Today we are joined by an expert in this field, Sheila B. Robinson, who is a speaker, educator, and consultant. Tune in to this episode as we discuss some key retention strategies, how to incorporate them into your training, the benefits of the ‘Spacing Effect’, and Sheila’s top advice with where to begin.About Sheila B. Robinson      Sheila B. Robinson, Ed.D., of Custom Professional Learning, LLC, is a speaker, educator, and consultant with a passion for the science of teaching and learning, presentations, and asking good questions. Through her talks, professional development workshops and university courses, Sheila teaches people how to make learning stick and how to ask good questions, along with program evaluation, survey design, data visualisation, audience engagement, and presentation design.Sheila is author of Designing Quality Survey Questions (SAGE Publications, 2018), and writes a popular blog with numerous articles on survey design, learning, presentations and other topics. Sheila is also a Certified Presentation Specialist (CPS)™, Vice President of the Presentation Guild, and Senior Design and Facilitation Consultant with Evergreen Data.  Key takeaways:Why learning retention is our ultimate goal: it encompasses all universal aspects of learning, from school to work. It is about being able to pull from your brain what's there, because you've learned something. It’s a great way to empower your learners with this skill so they can make the most out of your program.Testing evokes negative emotions and Sheila is reluctant to use the word ‘testing’ because it leads us to think about assessment. People think they are being judged, which makes them anxious and not optimal. The idea of retrieval practice as self-testing is a chance to help you process newly learned material and integrate it with prior knowledge.Apply the spacing effect: it demonstrates that learning is more effective when study sessions are spaced out. It gives learners time and a chance to embed long-term memory. We have been doing this since our childhood at school, e.g when you first learn the times tables, then it spaces out over time until you no longer forget them.Chapters:(00:00:00) Introduction.(00:01:59) What learning retention means to Sheila.(00:02:53) The universal aspect of learning retention.(00:04:00) Ways to increase retention.(00:07:18) The problems with the ‘Testing Effect’.(00:11:10) The role of demonstration during training sessions.(00:13:45) Understanding the ‘Spacing Effect’.(00:19:51) Having a module to inform students about learning retention.(00:21:13) Sheila’s advice for increasing retention.Links from the podcast  Connect with Sheila B. Robinson on LinkedInFind out more about ​​Custom Professional LearningCheck out the Head First series series of booksCheck out Sheila’s Blog

Episode summaryLynne is a learning experience designer and marketing professional. She joins the show to discuss the intersection of marketing and learning, and how the principles of marketing can be applied to learning. It is a fascinating topic where we also delve into the role of learning campaigns, ways to personalise learning from personas, and catering for the next generation.About Lynne McNameeLynne McNamee is the president of Lone Armadillo Marketing Agency. She has managed marketing campaigns for companies such as Avis, HP, and Bank of America, and recently was the marketing director for Bluewater, consultants for learning, talent, and human capital management. Lone Armadillo Marketing Agency, which Lynne founded in 2008, specialises in strategy, plans, processes, and tactical execution of multi- and omni-channel marketing programs for B2B entrepreneurial companies. She has been a HubSpot partner since 2011. She was cited by The New York Times for innovations in marketing.Key takeaways:Marketing plays an important role in learning as it  raises awareness, generates interest, and can motivate learners. Ensure you understand the learner's motivation and preferences, so your message resonates with them on an ongoing basis.There are three stages of a learning campaign: awareness, consideration, and decision. Connect with your learner and help them understand why the learning matters to them, so tune in to their emotional drivers. Consider tools like email segmentation, landing pages, and integrating learning tools with platforms such as HubSpot.Keeping an open mind with the next generation of learners: Lynn describes the next generation in the world of work will be Gen Z – and they are learning informally from TikTok and ChatGPT – so they will have learnt to learn differently than Millennials and Gen X. The best strategy is to be adaptable and experiment with different approaches to see what works best for your learners.Chapters:(00:00:00) Introduction.(00:02:31) Some of the key benefits of learning campaigns.(00:04:03) Understanding the differences between advertising, marketing, and PR.(00:07:56) Using personas to enhance learning campaigns.(00:10:25) How to personalise learning experiences for different learner personas.(00:19:07) Exploring tools for engaging learning experiences.(00:22:19) If Lynne could use a magic wand in L&D, what would she wish for?Links from the podcast:Connect with Lynne on LinkedInLone Armadillo Marketing Agency’s WebsiteFind out more about Lynne’s workshop on Building Learning Campaigns: Why, How, and Let’s Get StartedSome the platforms Lynee talks about are Hubspot and ActiveCampaign

Episode summaryToday we are joined by Malcom Taylor, the Senior People Development Manager at Met Office UK, where we explore the practices of a community of practitioners in a public sector organisation. The Met Office has established the People Framework as a way to support the learning and development of their staff. It was a fascinating conversation where we also delved into the role of openness and trust, how to be seen as more than just a training department, what makes a ‘Good Met Office Citizen’, and Conole’s 7 Cs of learning.About Malcolm Malcolm brings over 20 years’ experience working in the field of Human Resources and Learning & Development, and he is driven by a passion for learning. At the Met Office, Malcolm is currently the Senior People Development Manager, and he established a number of communities with practice as well as his learning tactics.Key takeaways:The People Framework is a tool developed by the Met Office to support the learning and development of their staff. It is divided into three segments: personal effectiveness, corporate effectiveness, and professional effectiveness.The Community of Practice Manager acts as a guiding influence and is not tied to any particular community. The person under this role at the Met Office has built a maturity model to help develop the impact of the People Framework.The community of practice offers a range of activities including specialist group channels in Teams, and the platform is a great way to connect people that are geographically far apart. They also invite external speakers to speak on webinars, where they get about 60 - 70% of registrants attending recorded or live.Chapters:(00:00:00) Introduction.(00:01:10) Why the Met Office established the People Framework.(00:04:55) The current leaders and their backgrounds.(00:06:34) Guiding the professional leaders.(00:09:39) The role of a Community of Practice Manager.(00:10:19)Creating content for the community of practice.(00:12:28) Building a safe environment.(00:16:41) Evaluating the impact of the community of practice.Links from the podcast Connect with Malcolm on LinkedInRead The 7Cs of Learning Design by ConoleRead ‘The Five Dysfunctions of a Team’ by Patrick Lencioni

David James, Chief Learning Officer at 360 Learning and host of the Learning and Development podcast, joins the show to discuss the potential of collaborative learning, and the misconception that it is more difficult than other approaches to digital learning. Tune in as David shares examples of collaborative learning in practice, why collaborative learning is often the best solution in L&D, and how to use technology so it can help with performance and results.’About David James    David James has worked in People Development for more than 20 years, most notably as Director of Talent, Learning & Organisation Development for The Walt Disney Company across Europe, the Middle East & Africa. His specialism is in contemporary L&D practices and works with clients to develop and implement their digital learning strategies. David is the Chief Learning Officer at 360 Learning and host of the Learning and Development podcast. He also writes articles and speaks about L&D at conferences and events.Key takeaways:L&D teams often focus on providing learning, but not necessarily to affect performance and results. David demonstrates how collaborative learning is the best solution – but it is still being overlooked.Collaborative approaches are often seen as hard because there is an expectation from stakeholders that learning is deliveredOrganisations must identify the critical points of failure that their people are experiencing first, rather than just as a learning need, as a way to ensure that engagement is sustained, as well as help people to achieve the objectives of the organisation. Use data-driven approaches to help solve performance problems.Chapters:(00:00:00) Introduction.(00:01:55) The challenges of L&D delivery.(00:03:13) Overcoming some of obstacles with collaborative learning.(00:05:59) The link between collaborative learning and performance outcomes.(00:09:57) Performance consulting for L&D and overcoming blockers.(00:14:48) Examples of good collaborative learning.(00:22:53) Embracing the upfront efforts with collaborative learning and development.(00:24:37) Leveraging technology to improve leadership and management skills.Links from the podcast:Connect with David on LinkedInCheck out 360 LearningCheck out Looop by 360LearningListen to the Learning and Development podcastListen to the interview with Sebastian Tindall

In this episode, we delve into a fascinating AR project Rustica Lamb is creating, and how L&D experts can get started with Augmented Reality. We explore the current landscape of how you can implement augmented reality, Rustica’s own personal experience of testing out different AR solutions, and models of learning through Web3.About Rustica LambComing from a digital learning background, Rustica Lamb is the founder of Bloom Learning Technologies, an international award-winning learning technologies company that is bringing the cost of elearning way, way down. They help organisations create engaging learning experiences, whilst supporting the business and budget goals.Key takeaways:The learning potential from augmented reality: AR is getting more and more common, but it is not mainstream yet. Rustica sees some massive opportunities in induction and onboarding.The current costs: AR is treated a premium currently because it is emerging. Rustica likens it to the early 2000s with the price for a website – like web design, the costs will go down the more mainstream it will be, where there will be more DIY template solutions.Where to start: start by researching some use cases to what is possible with this technology, then reflect on how you can apply AR to your work and do mini experiments to find what works best for you.Chapters:(00:00:00) Introduction.(00:02:01) Rustica’s personal learning experience of using Augmented Reality.(00:07:36) Her process of finding the right AR technology to use.(00:08:29) What is the learning potential with AR?(00:12:54) The costs associated with AR technology.(00:14:26) The three phases of her process/ product development.(00:18:53) How does AR change the instructional design process?(00:23:35) Where L&D experts can get started with AR.Links from the podcast  Visit Bloom Learning TechnologiesConnect with Rustica on TwitterCheck out UnityCheck out NianticCheck out LightshipCheck out STEPN