Learning While Working Podcast

In this episode of the Learning While Working Podcast, Bianca Baumann and Mike Taylor share insights from their latest book, ‘Think Like a Marketer, Train Like an L&D Pro: Strategies to Ignite Learning', and dive into actionable strategies that L&D professionals can borrow from the world of marketing.Discover why shifting your mindset from “order taker” to strategic business partner is essential for today's L&D professionals. We also uncover how to personalise learning at scale, run effective learning campaigns, and apply marketing-inspired strategies to create learning experiences that resonate – and deliver results.About  Bianca BaumannBianca Baumann is a seasoned learning strategist, international speaker, and author who specialises in innovative workforce enablement solutions. With deep expertise across L&D, employee experience, performance management, and future workforce planning, she partners with global organisations to design data-driven, business-aligned strategies. Known for her work with C-suite leaders and high-performing teams, Bianca brings a sharp focus on transforming human capital into a competitive advantage.About  Mike TaylorMike Taylor is a learning consultant on a mission to eliminate boring, ineffective training. With hands-on experience across nearly every role in L&D, he combines practical know-how with a passion for finding smarter, more engaging ways to help people learn. A self-described “recovering bad student,” Mike brings deep empathy for learners and a talent for simplifying complex topics. He helps organisations design impactful, tech-savvy learning experiences that connect with today's distracted workforce.Key takeaways:Start small and don't be intimidated: You don't need a big budget or fancy tools to bring marketing thinking into learning. Simple, actionable steps – even with no-cost tools – make a difference. (And, get others excited to join in!)Adopt a learner-centred mindset, not just content creation: Marketing excels at understanding audiences. Use tactics like research-based personas and journey mapping to make learning experiences resonate and drive business outcomes.Think in campaigns, not just courses: Like marketers, L&D should use content strategically – spread it across multiple channels, personalise when possible, and align everything to the bigger business workflow.Chapters:(00:00:00) Introduction(00:06:11) Design learning for cognitive understanding(00:07:19) From order taker to partner(00:11:13) Prioritising actionable sales metrics(00:14:39) Marketing funnel concept for learning(00:17:43) Reframing persona use in design(00:23:25) Evolving learning journeys(00:27:25) Personalisation in marketing technology(00:29:01) Content organisation for enhanced learningLinks from the podcast:Connect with Bianca Baumann on LinkedInConnect with Mike Taylor on LinkedInTrain Like A Marketer WebsiteThink Like a Marketer, Train Like an L&D Pro – Book  

In this episode of the Learning While Working Podcast, Dr. Alaina Szlachta, founder of Design by Development Solution, explores measuring success in learning and development. She guides us in thinking like researchers to effectively gather data from stakeholders and align training solutions with business outcomes.Tune in as she highlights starting with simple, relevant data points and introduces 'Return on Expectations' to evaluate if training meets stakeholder goals. We'll also discuss the challenges of measuring soft skills, the pitfalls of satisfaction metrics, and the importance of understanding the core problems training aims to address.About  Alaina SzlachtaDr. Alaina Szlachta creates data-enablement systems for small businesses to show the outcomes and the impact of their learning programs. She is the founder and creator of Measurement Made Easy, a community of practice which uses microlearning, mentorship, and real case studies to create simpler solutions to common measurement and evaluation challenges. An academic turned entrepreneur, Alaina Szlachta, PhD, is the founder of By Design Development Solutions, a consulting firm specialising in data enablement. Drawing on her background as a researcher and public health educator, she partners with learning and operations teams to integrate measurement and evaluation systems into their daily practices, providing continuous feedback loops that enhance quality, efficiency, and profitability. She generously shares her expertise through writing and speaking engagements, and as the host of Measurement Made Easy, a free community of practice that guides practitioners in refining their impact measurement strategies.Key takeaways:Think like a researcher: Effective measurement starts with forming hypotheses and gathering relevant data. Approach your L&D projects with a research mindset for valuable insights.Focus on business Impacts: Align your learning solutions with business goals and measure the impact on those outcomes. Rather than fixating on satisfaction scores, emphasise whether the training achieves its intended goals.Start simple: Begin with a single, manageable data point to make the data analysis process approachable. Ask stakeholders about their expectations before and after the training to measure 'Return on Expectations.'Chapters:(00:00:00) Introduction.(00:05:56) Monitor one data point over time for insights.(00:08:01) Delegation clarifies priorities and reduces burnout.(00:13:18) Start small and utilise existing data creatively.(00:14:51) ‘Return on Expectations': Measuring program investment outcomes.(00:20:17) Don't assume learning solves every performance problem.(00:21:43) Show value by aligning with business goals.(00:27:49) Methodology is essential for academic success, not engaging.(00:29:33) Use data to learn and improve strategies.Links from the podcast:Connect with Alaina Szlachta on LinkedInAlaina Szlachta's WebsiteRead Alaina Szlachta book Measurement and Evaluation on a Shoestring  

In this episode of the Learning While Working Podcast, we are joined by Dwayne Wood, an associate professor at National University and an expert in instructional design for workplaces. As the landscape of AI, especially generative AI like ChatGPT, rapidly evolves in higher education, Dwayne shares his unique perspective on how this technology is reshaping learning experiences. From the ethical implications to the challenges of maintaining critical thinking and creativity in students, this episode unpacks the complexities and opportunities AI brings into the educational sphere.About Dwayne WoodDwayne Wood, Associate Professor at National University, is a renowned educator and instructional designer. His expertise lies in creating highly effective and engaging pedagogical methods, designing effective and engaging curricula, creating learning materials tailored to diverse audiences, and designing educational experiences for adult learners.With a distinguished background in military service, Dwayne brings a unique perspective to the world of education, blending discipline and innovation to create transformative learning experiences.Key takeaways:Applying learning to the workplace: Dwayne emphasises the importance of helping students transfer their academic knowledge to real-world work environments. This practical approach is crucial in preparing better citizens and a workforce ready for modern challenges.The impact of generative AI on higher education: Generative AI, such as ChatGPT, is revolutionising traditional assessments and learning models. While it can make tasks like writing research papers more efficient, there is concern over whether the cognitive effort required for genuine learning is being diminished. Dwayne discusses the balance universities need to find in leveraging AI tools responsibly.Experiential learning and AI literacy: In his own instructional design courses, Dr. Wood uses AI technologies as both instructional tools and as subjects of study. Students engage in project-based learning, reflecting on how AI affects their task completion and overall learning experience. This method fosters transparency and critical discussion about AI's role in education and the workplace.Developing human skills: Despite AI's growing presence, certain skills remain uniquely human. Dwayne highlights critical thinking, creativity, and cultural awareness as irreplaceable by AI. He advocates for educational strategies that emphasise these human aspects, ensuring students are well-rounded and versatile thinkers.Segmented time stamps:(06:43) Education must enable workplace skill transfer.(07:46 Teaching AI tools for instructional design experience.(11:44) Technology confirms biases; critical thinking requires multiple perspectives.(15:55) Teaching responsible technology use remains challenging.(19:20) Reframing discussions as experiments for leadership development.(22:22) AI enhances learning, not replacing human thought.(24:53) Cultural literacy and creative thinking are essential.Links from the podcastConnect with Dwayne Wood on LinkedIn  National University Website

In this episode of the Learning While Working Podcast, Anamaria Dorgo Anamaria Dorgo, the founder of Handle With Brain, shares her innovative "No Course" approach to learning design. Learn how to create sustainable learning communities, encourage participant-led experiences, and leverage curiosity and adaptability in the learning process.About Anamaria DorgoAnamaria Dorgo is a Learning Experience Designer, Facilitator, and previously the Head of Community at Butter. With degrees in psychology and human resources, she has a lifelong commitment to learning, resulting in her creating engaging learning experiences for a global community. ​​She is the founder of Handle with Brain, an experience design consultancy.Key takeaways:Collaborative Learning: The "No Course" approach is based on peer-to-peer interaction and mutual support, encouraging participants to learn by doing and sharing real-time feedback. Ideal for projects involving new technologies, such as AI.Community Building: Start small with passionate peers, prioritise co-creation, and let the community grow organically. Shift from a service provider mindset to a collaborative, participant-led approach for sustainable development.Action-Based Learning: hands-on, context-specific projects help participants focus on their personal and professional growth. Bi-weekly sessions with peer coaching and practical workshops ensure continuous progress and learning.Segmented time stamps:(00:00) Introduction(05:08) Experimenting with peer coaching and the liberating structure called Troika consulting(12:40) Switching meetings to weekly, adding workshops and speakers.(15:04) How content is enhanced by peer sessions.(18:04) Auditing requires thorough individual analysis first.(21:45) Having a Slack channel for communication and cohort updates.(24:24) Collaborative learning fosters accountability and progress.(30:04) Communities start small and grow through shared value.(31:20) Collaborative learning is about inviting questions and finding answers.Links from the podcast:Connect with Anamaria Dorgo on LinkedInCheck out her website More about the courseLearn more about Liberating StructuresListen to Mapping Ties

In this episode of the Learning While Working Podcast, Rance Green talks about the transformative power of storytelling in learning. He shares his "instructional story design" method, emphasising the need to understand the learning audience deeply and integrate conflict effectively into training narratives. Rance also provides practical advice on creating impactful training stories that act like flight simulators for the brain, driving both context and action.About Rance GreeneRance Greene is a story designer, author and speaker. Rance helps leaders connect with, inspire, guide and persuade their people through story-based messaging. He also equips talent development professionals to reach business outcomes through story-based training. A leader, consultant, coach and frequent speaker in live and virtual sessions on leadership storytelling, story-writing and instructional story design.Key takeaways:Understand your audience: Rance emphasises the importance of deeply understanding your learning audience to create relatable characters and scenarios. This ensures the training is tailored to their specific needs and resonates on a personal level.Incorporate conflict: One of the essential elements of a compelling story is conflict. It engages the audience and drives the narrative forward. Rance highlights that stories in training should end at the height of conflict to leave a lasting impression and a desire for resolution.Story design as a process: Rance's "instructional story design" method combines analytical and creative steps, making storytelling accessible to everyone, even if you don't see yourself as a natural storyteller. By focusing on behaviours and actions, training stories become both relatable and actionable.Segmented time stamps:(00:00) Introduction.(06:12) Scenarios compared to stories.(11:08) Training stories need relatable characters and conflict.(16:07) Encourage stakeholder responsibility through system-based thinking.(18:22) How will training benefit individuals personally?(25:21) Start a story, resolve conflict, and ask reflective questions.(28:39) Efficiently teach storytelling: conflict, action, brevity.Links from the podcast:Connect with Lance Greene on LinkedInRead ‘Instructional Story Design'Visit NeedAStory.com

In this episode of the Learning While Working Podcast, Lisa Bodell, CEO of FutureThink and a global leader in simplification and innovation, explores the vital role of curiosity in our rapidly evolving AI landscape. Robin and Lisa discuss the power of asking "killer questions," fostering a culture of curiosity, and the irreplaceable human touch in creativity and problem-solving. Lisa also shares practical examples and insights on how diverse questioning can lead to innovative solutions in both work and personal life.About Lisa BodellLisa Bodell is an award-winning author and CEO of FutureThink. She has repeatedly been selected as one of the Top 50 Keynote Speakers in the World and recognized as one of the top 50 futurists. As a futurist and expert on the topic of innovation and simplicity, she serves as a global council member of the World Economic Forum, and has helped thousands of senior leaders ignite innovation at Bloomberg, Pfizer, Lockheed Martin, and more.Key takeaways:Curiosity as a Skill: it is not just a natural trait; it's a skill that can be taught, practised, and sharpened. Organisations must foster a culture where asking questions is encouraged and safe. The Power of Better Questions: in the age of AI, the quality of answers is directly tied to the quality of questions. Instead of defaulting to straightforward queries, try "question storming" to expand your thinking and uncover new possibilities.Thinking Time is Crucial: Lisa emphasised the importance of carving out time for deep, uninterrupted thinking. This isn't just beneficial for innovation at work but for personal growth too.Segmented time stamps:(00:00) Introduction(03:54) How brainstorming problems unlocks creative solutions.(08:28) Innovation involves uniqueness, not identical prompts and answers.(10:42) Use provocative questions to inspire disruptive innovation.(13:05) Lack of preparation and time stifles creativity.(16:32) Progress comes from creating multiple iterations.(22:05) How ‘The Artist's Way' nurtures creativity through daily writing.(23:04) Monthly thinking day eases personal and business challenges.Links from the podcastConnect with Lisa Bodell on LinkedInVisit FutureThinkRead The Artist's Way

In this episode of the Learning While Working Podcast, Sarah Hawk, co-CEO of Discourse, shares the transformative potential of chat platforms in facilitating learning and collaboration in the workplace. The conversation explores the concept of "fast lane" and "slow lane" chat environments, emphasising the significance of intentional information architecture and fostering a culture of open, transparent communication, and much more.About Sarah HawkSarah Hawk is an expert in online community building and manages the team that builds Discourse, the 100% open source discussion platform built for the next decade of the Internet. Prior to her current role, Hawk was Head of Community at community consultancy FeverBee.Key takeaways:Intentional Information Architecture: Hawk emphasises the importance of designing a well-structured information system. Ensuring people know where to post questions, how to find answers, and how to retain and document knowledge is crucial for long-term organisational growth.Mindful Cultural Building: Building a culture that encourages open communication, prolific question-asking, and transparent storytelling enriches the learning experience. It's about taking people on your journey, not just arriving at the destination.Fast Lane vs. Slow Lane in Chat Platforms: Understanding the distinct roles of real-time (fast lane) and more permanent, reflective discussions (slow lane) helps optimise chat platforms for both immediate collaboration and long-term knowledge retention.Segmented time stamps:(00:00) Introduction.(04:05) Communication in remote workplaces and its impact.(09:18) Empowerment through intentional and mindful discussion.(11:51) Archiving fast-paced conversations systematically.(14:41) Building community through setting guidelines.(18:52) The need for a flexible platform for knowledge sharing and safety.(20:55) Insights on information architecture, culture and learning.Links from the podcast:Connect with Sarah Hawk on LinkedInCheck out Discourse's Website

In this episode of the Learning While Working Podcast, Kayvon Touran shares the transformative potential of AI in skill management. Tune in as we unpack the pivotal role of context in making skill frameworks effective and the innovative ways AI can address the nuances of managing skills within organisations. Kayvon also reveals how AI can streamline data collection and enhance skill assessments through dynamic simulations.About Kayvon TouranKayvon Touran is the CEO and co-founder of Zal.ai. Kayvon has spent his entire career working in early stage technology startups, and most recently as a product leader in education technology where he created and implemented a next generation lifelong learning platform for higher education institutions.Key takeaways:Context is king: Generic skill definitions won't cut it. Kayvon shares how customised, context-specific skills frameworks are essential for genuinely impactful training.AI as a powerful tool: Artificial intelligence can streamline the collection and analysis of skill data, helping to distil massive amounts of information into actionable insights.Practice and personalisation: Realistic, role-specific simulation-based training can elevate employee performance. Explore AI-driven, practice-based assessments to provide dynamic, tailored feedback and training opportunities.Segmented time stamps:(03:15) Data analysis for actionable insights at organisational level.(07:34) Passion for skills transformation in organisations.(09:50) Importance of generative AI in product development.(14:51) How to use AI to summarise skill definitions from the web.(18:21) Having personalised dynamic training for durable skills, performance-based.(22:23) Why is context crucial for effective skill training?Links from the podcastConnect with Kayvon Touran on LinkedInZal.ai's Website

In this episode of the Learning While Working Podcast, Brant Gibbons, President of Knowledge Anywhere, shares his expert insights on the current generation of AI tools, the balance between innovation and practicality, and the critical considerations for L&D professionals when integrating AI into their workflows. We explore the exciting potential of AI, the inherent risks, and the ongoing tension between cutting-edge technology and maintaining quality human interactions in learning experiences. About David GuralnickAs the President of Knowledge Anywhere, Brant Gibbons leads a team of passionate and innovative professionals who deliver technology-based learning solutions to help their clients achieve their goals. With over 20 years of experience in the learning industry, Brant has a proven track record of driving growth, building strategic partnerships, and enhancing customer satisfaction. Founded in 1998, Knowledge Anywhere, Inc. is an award-winning company that has emerged as a leader in knowledge transfer through eLearning technology.Key takeaways:Think Big, Start Small: Embrace AI as the future but proceed with caution. Analyse its impact on your workflow and ensure it drives both performance and cost-efficiency without compromising user experience.Stay Data-Driven: Don't lose focus on analytical approaches. While generative AI can be helpful, foundational data analytics are crucial for making informed, impactful decisions.Balance Innovation with Quality: AI can make content creation faster and easier, but it's critical to maintain the human element in learning experiences to avoid alienating your audience.Segmented time stamps:(00:00) Introduction(05:55) Compliance-driven training lacks meaningful business impact(08:16) Using technology to supplement traditional instructional design(13:17) Future of learning: ongoing, personalised, interactive knowledge-seeking(14:34) Custom chatbots and generative learning(20:58) Embrace AI cautiously and align with audience needs Links from the podcastConnect with Brant on LinkedInKnowledge Anywhere's Website

In this episode of the Learning While Working Podcast, David Guralnick, the CEO of Kaleidoscope Learning and President of the International eLearning Association, shares the potential of AI-driven, learner-centric environments. He also unpacks the possibilities of AI as a personalised coach, and the challenges organisations face in adopting new technologies. Plus, hear David's valuable insights on moving beyond traditional constraints to dream big and scale back, ensuring that the ideal learning experience is always within reach.About David GuralnickDavid Guralnick is the current President and CEO of Kaleidoscope Learning. He is also the current president of the International E-Learning Association; founder and chair of The Learning Ideas Conference; Editor-in-Chief of the International Journal on Advanced Corporate Learning; Chair of the International E-Learning Awards; and an Adjunct Professor at Columbia University. He is the author of the book "How Organizations Can Make the Most of Online Learning”.Key takeaways:Meaningful Learning Defined: it's not just about content or information. Meaningful learning resonates emotionally and aligns with personal goals, whether in the workplace, school, or life in general.AI as a Coach: Imagine having an AI coach guiding you through complex scenarios, learning about your interests, and tailoring experiences specifically for you. David discusses the potential of AI to act as a mentor and facilitator, making learning not just efficient, but deeply engaging.The Future of Learning: David shares some strong visions for the future, advocating for a shift from traditional, constraint-bound methods to innovative, tech-enabled approaches that truly reimagine education.Segmented time stamps:(00:00) Introduction(05:38) Progressive learning techniques and leveraging technology for education(06:41) Reconsidering education in the age of AI(09:50) AI's potential and challenges in near future(14:28) Early AI work in education at Northwestern(19:03) Created specialised authoring tool for non-technical users(20:02) Online learning constrained by tool limitations and coding(25:10) Start big, think AI, and what the ideal experience looks like(26:34) Accepting tradeoffs can lead to greater satisfaction Links from the podcastConnect with David on LinkedInVisit Kaleidoscope Learning's WebsiteRead David's book ‘How Organizations Can Make the Most of Online Learning'

In this episode of the Learning While Working Podcast, Bob Mosher shares the potential of performance support to enhance learning while working. We'll explore the concept of 'the Five Moments of Need' and how they revolutionise our approach to workplace training. Bob also sheds light on some crucial strategies like performing workflow analysis before developing training solutions, and redefining the roles of learners as performers and users.About Bob MosherBob Mosher is the Chief Learning Evangelist and Co-Founder of APPLY Synergies, a strategic consulting firm that specialises in helping learning organisations design, develop and measure effective learning and performance support strategies to meet the 5 Moments of Learning Need. Bob has been an active and influential leader in the learning and training industry for over 40 years and is renowned worldwide for his pioneering role in new approaches to learning.Key takeaways:Performance support is critical: Understanding that performance support isn't just about creating job aids or tools but developing a discipline that incorporates these tools into a learning ecosystem that supports work as it happens.Focus on the workflow: Start with a workflow analysis to understand the tasks and processes where performance support can be effectively integrated. This helps in designing learning that is not just informative but truly applicable.Apply over theory: Shift the focus from theoretical knowledge to real application. Learning should be anchored in real-life tasks and designed to support the actual application in the workplace, enhancing both learning and performance outcomes.Segmented time stamps:(00:00) Introduction(05:43) Portfolios as professional reflective documents are essential(07:06) Consumption vs performance – the key difference(11:18) Why workflow analysis is essential for designing effective solutions(16:17) Giving new leaders practical guidance for success(23:02) Evaluating learning outcomes and impacts with technologyLinks from the podcast:Connect with Bob Mosher on LinkedInAPPLY Synergies' Website

In this episode of the Learning While Working Podcast, Danny Stefanic is a pioneer in 3D technologies and is the founder of a number of  VR-related companies including LearnBrite. We'll be exploring the challenges and opportunities of using VR and AR in learning environments, how organisations can implement these technologies effectively, and the future of immersive learning experiences.About Danny StefanicDanny Stefanic has been working in the virtual reality industry for over 25 years and created the first web metaverse back in 2008. He is the founder of a number of VR-related companies including LearnBrite, MootUp and Hyperspace, and continues to be a pioneer in VR and AR in learning environments.Key takeaways:The practical applications of VR and AR in corporate learning: provide hands-free operation for on-the-job training and enhanced real-world simulations for skills like objection handling and customer service.Be aware of cross-device compatibility: develop experiences that operate across multiple platforms, and make sure you choose a platform that supports cross-device functionality.Future trends and considerations in immersive tech: there will be an evolution toward more user-friendly and integrated AR/VR technologies. There is also potential for mainstream adoption as hardware becomes more accessible and user-friendly. The best recommendation to get started is to use no-code platforms and existing skills for creating immersive learning experiences.Segmented time stamps:(00:00) Introduction(05:54) The Apple Vision Pro being a high-quality, heavy headset(07:51) Immersive experience enhances learning and comprehension(13:23) Challenges of deploying VR in organisations(16:44) New technology allows for widespread accessibility and usage(19:16) Transition to using spectacles as user interface(25:24) Tool for instructional designers with existing skillsLinks from the podcast:Connect with Dany on LinkedInVisit LearnBrite's websiteCheck out Hyperspace  

In this episode of the Learning While Working Podcast, Stella Lee unpacks her comprehensive competency framework for AI, crafted especially for learning and development professionals. The conversation covers everything from the AI fundamentals to the crucial aspects of data fluency, and the ethical implications to know about. Stella's framework emphasises the need for a mindset that balances adaptability and critical analysis.About Susan Stocker    With over 20 years of experience in the e-learning and edtech industry, Stella Lee is a director at Paradox Learning, a consulting firm that provides and evaluates innovative learning solutions across multiple devices, cultures, and platforms. Stella works with clients from various sectors, such as government, education, non-profit, and corporate, to help them achieve their learning and development goals with data-driven and technology-enabled approaches.Key takeaways:The AI Competency Framework: covering seven areas, it is designed to deepen our understanding of artificial intelligence and its implications in the learning and development sector. The concepts cover: data fluency, diverse use cases, critical thinking, ethics, AI in education, and the future of work.Cultivate a deeper understanding of AI's implications, which includes ethical considerations, and its potential impact on future work structures, which would allow L&D professionals to prepare and adapt accordingly.Having multiple mindsets towards AI, such as adaptability and openness, and the value of starting from one's current level of understanding to contribute to collective learning in AI. Be aware of individual responsibility in fostering an environment of ongoing education and critical engagement with emerging technologies. Segmented time stamps:(00:00) Introduction(04:16) Thinking ethically about AI and preparing for future(08:21) The AI competency framework: 7 areas of focus(10:30) Future collaboration with AI(16:34) Using AI to develop strategy and educational piece(20:24) Reflecting on work and considering broader implications(25:39) Embrace multiple mindsets and experiment(27:24) Health care innovation will influence other fields Links from the podcastConnect with Stella Lee on LinkedInVisit Stella's WebsiteDownload the AI Literacy Competency Framework for Educators & L&D ProfessionalDownload the AI Adoption Framework for L&D   Read ‘AI Literacy: Implications for L&D' 

In this episode of the Learning While Working Podcast, Terry Pearce, the founder of Unfold Play, joins the show for a discussion on engaging learning through play. Terry shares strategies for game-based learning and the six levers that make games effective for learning. He also gives examples of how putting learners at the centre of the learning experience can transform seemingly dry content into engaging and effective learning activities.About Terry PearceTerry Pearce founded Untold Play to bring together his twin passions of learning design and games. Terry leverages the power of games and gamification in learning, and he regularly weaves the principles of game-based learning into the learning experiences he creates. He has won awards, through the London NHS Modernisation Agency, Reed Learning and the Healthcare People Management Association, for the services I deliver to clients, including HSBC, Imperial College Hospital, Thames Water and Zurich.Key takeaways:Putting learners at the centre: Games engage learners by making them the protagonists, setting open challenges, letting them explore, embracing failure, offering meaningful choices, and nudging them towards desired behaviours. This shift places the focus on the learner and encourages active participation in the learning process.Debriefing for reflection: Terry stressed the significance of debriefing in learning experiences. The "What happened, So what, Now what" framework allows learners to process their experiences, make generalisations, and consider behavioural changes as they apply their learnings to real-world scenarios.Transform Deck: Terry introduced the Transform Deck of learning design cards, which is a valuable tool for creating engaging, learner-centred activities. The deck serves as a point of inspiration for turning content into interactive, experiential learning experiences, providing a spectrum of options beyond traditional games and gamification.Segmented time stamps:(00:00) Introduction(04:56) Games thrive on failure, meaningful choices and nudges(09:18) Embrace play and games for healthy benefits(11:08) Creating engaging learning experiences through interactive games(14:54) Virtual escape room featuring games-based learning(18:41) Dice game simulates cultural immersion and adaptation(22:15) Deck of cards for inspiring learner-focused activities(25:12) Align objectives, culture, and methods for learningLinks from the podcast:Connect with Terry on LinkedInVisit Terry's WebsiteCheck out The Transform DeckRead more about The Six Levers

In this episode of the Learning While Working Podcast, Gregg Eiler, Senior Manager for Learning and Development at Powin, unpacks how motivation, clarity, and leadership interact to boost employee performance. Gregg also dives into the art of coaching, sharing actionable insights from his own experiences that redefine how to build expertise within L&D teams. Find out why it's about being more than just an instructional designer – it's about being a business problem solver with a curious mindset.About Gregg EilerGregg Eiler is the Senior Manager for Learning and Development at Powin, where he built the company's L&D operations from the ground up. He is an experienced Instructional Designer and Performance Improvement Expert with over 15 years of expertise, collaborating with global industry leaders to create impactful learning solutions. Greg's particular passion lies in optimising performance ecosystems, focusing on elements such as motivation, bandwidth expansion, deliberate practice, coaching, and feedback.Key takeaways:Embrace the problem-solver mindset: Learning and Development goes beyond training; it's about being a strategic problem solver who aligns with business objectives.The power of coaching: Gregg leverages coaching to unlock the potential of industry experts, building their capability to ask challenging questions and pivot their perspective.Curiosity as a capability: Encourage curiosity within your L&D teams – it's the driving force that fosters accountability and a sharp focus on solving core business problems.Segmented time stamps:(03:58) Accountability, progress, and curiosity in sports coaching.(07:40) Consider multiple factors before investing time.(13:00) Encouraging curiosity, coaching and using templates.(15:52) Question to envision future success and set expectations.(18:29) Advocates design thinking for a user-centred approach.(20:12) Prototyping and testing essential for effective solutions.(24:29) Improve business skills through coaching.(27:10) Respecting opinions and styles while offering feedback.Links from the podcast:Connect with Greg on LinkedInVisit Greg's Website

In this episode of the Learning While Working Podcast, Andrea Laus explores the importance of role plays for developing crucial human skills, the potential pitfalls in traditional role play designs, and the transformative impact of a digital approach to role plays guided by technology. Andrea als unpacks how AI can enhance role plays, improve the feedback process, and ultimately revolutionise the L&D landscape.About Andrea LausAndrea Laus has spent the last 20 years developing effective strategies for talent development. He is the CEO of SkillGym, which designs state-of-the-art digital role plays for rebalancing knowledge-based training approaches with actionable practice. He regularly shares his ideas about effective training methodologies and strategies through his blog, and speaks at several HR and L&D conferences around the world on these fascinating subjects. Key takeaways:The importance of role plays in learning experiences: Andrea shares how it's crucial for developing human skills such as communication, collaboration, and problem-solving. It also creates a safe environment for practising real-life scenariosOn the challenges and misconceptions about role plays: Learners often feel judged and uncomfortable during role plays. There is a common misconception too that soft skills are “soft” – in reality they require dedicated effort and practice. It helps to understand these barriers so you can create the best learning environment.The application of technology and AI: Andrea highlights that, when used thoughtfully, technology can have a very positive impact. AI can help generate dialogues and responses, standardised and effective feedback, and it can assist in tracking and analysing learner actions. However, it is vital to select the right technology for specific learning objectives. Segmented time stamps:(00:00) Introduction(04:05) Handling the feeling of judgement in role plays(07:06) Leveraging role plays for sense making in learning(12:15) Practice with digital standardised and accelerates improvement(17:50) Supervise generative AI for writing dialogues(23:39) Measure and improve with technology-driven feedback(26:37) Utilise strategies, trust the process, embrace technologyLinks from the podcastConnect with Andrea Laus on LinkedInCheck out SkillGymWatch the recording of the Upskilling Using Artificial Intelligence: AI Digital Role Play webinar      

In this episode of the Learning While Working Podcast, Susan Stocker uncovers the world of computational thinking and its relevance in the age of artificial intelligence. With the skills gap becoming a concern in the era of AI and data-driven decision making, Susan's research on computational thinking in the workplace is timely and informative. Listen, as we explore what computational thinking is, the importance of critical thinking, and how these skills can shape our approach to problem-solving in the age of AI.About Susan Stocker    Susan Stocker is a Digital Transformation L&D Consultant where she helps organisations quickly change and get ahead of the skills and capability curve. She is committed to hands-on learning that enables teams to accelerate their success and companies to retain their people. She is also a certified Lean Six Sigma Master Black Belt, Certified Product Owner, Certified Scrum Master, and Certified BADIR Citizen Analyst.Key takeaways:Computational Thinking and AI in the Workplace: Computational thinking is a key skill in the age of AI and data-driven decision-making, so reflect on how you can build the relationship between these skills.Reimagining Work and Learning with AI: it's an exciting time to rethink work in strategic areas for impactful organisational change as we are incorporating AI in day-to-day work and collaborating with the business.The skills gap in computational thinking is a real concern. According to Susan's research, a significant percentage of people in the workplace lack critical and computational thinking skills. As professionals, we need to develop these skills to effectively work with AI and data.Segmented time stamps:(00:00) Introduction(04:46) The struggle with critical and computational thinking(10:01) Value drivers for AI transformation in business(11:33) Understanding AI's use cases and problem-solving approach(15:09) Moving beyond technical AI to include critical thinking and behavioural responses(20:29) Rethinking work Links from the podcastConnect with Susan Stocker on LinkedInVisit the Aryng WebsiteRead Boston Consulting report Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and QualityRead Ethan Mollich thoughts the Boston Consulting report Centaurs and Cyborgs on the Jagged Frontier 

In this episode of the Learning While Working Podcast, Eliza Cani, a learning designer at LearnWorlds, explores the topic of using ChatGPT for learning designers. Eliza shares valuable insights on how AI can be integrated into course design, the importance of prompting skills, and the future trends that can revolutionise the fieldAbout  Eliza CaniEliza Cani is an eLearning Designer at LearnWorlds, and an experienced public speaker with a background in IT. She started her career at LearnWorlds as a member of the support team where she demonstrated an in-depth knowledge of the platform and the ability to solve customer issues fast and efficiently. Over the years, Eliza has helped hundreds of trainers and course creators create engaging learning materials and deliver them effectively.Key takeaways:Prompt engineering and engaging with ChatGPT: there is a need for precise and specific prompts, e.g. specifying course duration, target audience, tone of voice, key takeaways, etc. Consider also the audience needs and preferences in prompts, as well as regularly reflecting on prompts over time to improve outcomes.Future trends in course design: expect more integrations of AI with platforms, including learning management systems and learning content systems. There will be less use of conversational interfaces, such as ChatGPT, and conversational AI will become more embedded in tools and platforms, to make AI more accessible to all users.Overall advice for Learning Designers working with AI: don't be afraid to use AI tools. Start with simple tasks and gradually explore more capabilities so you can understand how AI complements and enhances the work of learning designers. Segmented time stamps:(00:00) Introduction(02:22) ChatGPT as an efficient and creative tool for content summarisation(04:22) Simplifying learning theories for all(09:59) How to talk to AI tools by being advanced and precise(13:26) Having a customised approach based on audience and goals(15:14) How AI tools enhance learning design and why you need to understand their impact(18:15) Tools that facilitate course design and integration seamlessly(21:32) How AI won't replace designersLinks from the podcast Connect with Eliza Cani on LinkedInFind out more about LearnWorldsDo the free Master ChatGPT: Supercharge Your Course Design With AI course   

In this episode of the Learning While Working Podcast, Pedram Parasmand shares his insights on using AI tools for workshop designs and emphasises the importance of not relying on AI to do the creative work for you, but rather using it as a thought partner and brainstorming tool. He shares his experience with Chat GPT and Copy AI, highlighting how he trains these AI generative tools on his own methodology to support workshop design. He also explores the potential of using AI-powered transcription tools like Otter AI for analysis and evaluation.About  Pedram ParasmandPedram Parasmand is The Co-Founder and CEO of Skills Lab and has over 11 years experience working with executive teams to new entrants in the corporate, public, third and education sectors. Pedram has partnered with clients such as Accenture, Barclays Bank, Mind, Ministry of Justice, Red Bull, The European Union Commission, and The British Council. Previously, Pedram worked in Leadership Development at the education charity Teach First and started his career as a high school Science teacher.Key takeaways:Don't rely on AI to do the creative work for you: Pedram emphasises the importance of trusting your own human instincts and using AI as a support system or brainstorming tool. AI can enhance your workshop design process, but it can never replace your skills as a facilitator.Align AI with your specific challenges: When incorporating AI into your workshops, consider your pain points and processes. Explore how AI can assist you in addressing those challenges and improving your facilitation techniques. AI should complement your objectives, not replace them.Train AI in your methodology: Pedram shares his experience with training AI tools like Copy AI in his own workshop design methodology. By giving detailed prompts and instructions, you can teach AI to analyse transcripts, identify pains and gains, and generate audience-friendly content.Segmented time stamps:(00:00) Introduction(01:53) AI aids in designing workshops for newbies(05:46) Using tools like Otter AI that summarise, analyse, and evaluate conversations(07:01) How evaluation is flexible with various data points(12:57) Generate ideas for workshop objectives and refine later(16:44) Workshop structured like a story for growth(19:22) Finding ways to removes manual tasksLinks from the podcast Connect with Pedram on LinkedInVisit the Skills Lab's Website  Check out Copy AICheck out Otter AI 

In this episode of the Learning While Working Podcast, Marco de Rossi discusses the current issues with digital learning in workplaces, such as the misalignment between how we naturally learn as lifelong learners and how organisations push out content-driven learning. Tune in as we delve into social learning, synchronous vs. asynchronous activities, and how Generative AI is proving to be a valuable tool for L&D experts.About  Marco de RossiMarco de Rossi is the CEO of WeSchool, a learning platform that helps teams launch effective training in a user-friendly environment no matter their technical skills.Key takeaways:The challenges in digital learning in workplaces: there is a misalignment between how people learn in workplaces and how they naturally learn as lifelong learners. Learning is often seen as a buzzword, but not integrated into daily behaviours, so there needs to be a shift where learning becomes the responsibility of every team, not just HR.The people-centric approach: learning should be woven into everyday tasks and the focus should be on building communities and fostering social learning. Balancing cost-effectiveness and effectiveness: on-demand, self-paced learning may be cheaper, but it is not always effective. Cohort-based models and synchronous structures are important for critical learning experiences, like onboarding. Think about how a mix of cost-effective and quality-focused solutions can coexist.The role of AI can be a valuable tool for supporting learning design skills. E.g. conversational generative AI makes it easier for everyone to design engaging  learning experiences. Segmented time stamps:(00:00) Introduction(01:50) What is wrong with digital learning?(03:21) Marco's vision of what great digital learning looks like(06:27) Why self-paced learning is not always the best solution(08:19) Conversational generative AI(11:16) The importance of instructional design skills(15:13) Adaptive learning(18:00) AI make it easier for more people to access learning experiences(19:23) Overcoming the current problems of digital learningLinks from the podcast Connect with Marco de Rossi on LinkedInVisit WeSchool Learn more about WeShool by watching this video      Read Robin blog post on What would happen if digital learning were more expensive than face-to-face training? 

In this episode of the Learning While Working podcast Rustica Lamb and Robin explore how to leverage AI as a powerful tool to enhance your productivity and creativity, learn how to effectively prompt, and stay conscious of the ethical implications of AI in the learning and working sphere. She has recently run the Elab AI program, which aimed to introduce a series of AI tools to learning professionals. It tested and evaluated various AI tools and discovered their potential to save significant amounts of time for learning designers.About Rustica LambRustica Lamb is a hands-on learning professional who is passionate about experimenting with new technologies and exploring how they can transform learning.  She 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:Learning Designers can save about 40-60 hours per month through AI tools. By using this saved time, L&D professionals can focus on improving quality and fostering creativity. It  is important to remember that AI does not replace the expertise and insights of learning designers, so there needs to be human involvement along the process.Embracing AI in workplace learning is crucial for staying relevant, and Rustica points out that it is similar to the transition from traditional to e-learning.There is a need for expert guidance and coaching when using AI, to ensure accurate and reliable results from AI systems and maximising their potential in learning design.Segmented time stamps:(00:00) The importance of spending time playing with the tools(01:19) What is the eLab.ai program?(02:23) Key takeaways and insights from eLab.ai(04:13) Why humans won't be replaced by AI(06:41) Generating the ‘core skeleton'(11:25) Where creativity sits in the world of AI(15:25) The importance of coaching(18:23) Rustica's greatest gem of wisdom about using AI tools for learning designLinks from the podcast Connect with Rustica on LinkedInVisit the Bloom Technologies websiteFind out more eLab.ai Read ‘Scary Smart' by  Mo GawdatExplore FuturepediaListen to Moonshots & MindsetsListen to Augmented reality for learning with Rustica Lamb 

In this episode of the Learning While Working Podcast, Markus Bernhardt explores AI discussions with learning technology vendors, and the important topics of understanding the different types of AI being deployed and the value they add. We also touch on the critical role of training data and its reliability in AI solutions, and the rush toward generative AI and its impact on long-term strategic thinking.About  Markus BernhardtAs a Fellow of the Learning Performance Institute (LPI) and member of both the Forbes Technology Council and HBR Advisory Council, Markus Bernhardt is recognised as a global authority for AI and Learning. Markus is an accomplished author, panellist, and speaker. His leadership experience as CEO spans the direction of a for-profit educational institution as well as the stewardship of a charitable educational institution in the UK, with significant contributions in both executive and non-executive board roles.Key takeaways:Discerning between generative and non-generative AI deployment is essential for understanding AI's contribution to learning. It is beneficial for instructional designers, expediting tasks like summarising content, crafting questions, and facilitating collaboration with subject matter experts.The ideal landscape has AI-powered tools that offer real-time support, drawing from an organisation's internal data to provide personalised performance assistance.Adaptive learning journeys emerge as an exciting application, using AI to tailor learning experiences to individual strengths and weaknesses, thus enhancing learning outcomes.Segmented time stamps:(00:00) Introduction(01:38) Navigating the marketplace for technologies and solutions for the learning space (05:22) The impact of the ‘sudden' rush of AI(09:46) Internal training of data(15:23) The way we work with language models in organisations and workplaces(19:13) interesting AI applications in L&D at the momentLinks from the podcast Connect with Markus Bernhardt on LinkedInRead Markus article on 5 Key Questions to Ask AI Vendors & How to Understand the AnswersRead all of Markus Learning Guild articles   

In this episode of the Learning While Working Podcast, we explore how AI technologies can be used to increase the efficiency of instructional designers. We tackle the challenges and ethical concerns of using AI-generated tools, focusing on their limitations and potential misinterpretations. Get insights into the importance of maintaining the human element in instructional design, especially in areas like assessment design.About  Cara NorthCara North has worked in the instructional design field for more than a decade and has won multiple awards for her learning experiences. Cara has worked in both higher education and corporate, and runs her own consulting business, The Learning Camel. Some of the clients The Learning Camel has served include Universal Records, WesBanco, NASA, Daisy and the National Association for Talent and Development (ATD).Key takeaways:Generative AI can be used for brainstorming and translation. Tools like Chat GPT are valuable for creating first drafts, but they lack the ability to capture context-specific language and formality. As such, human input is required for this purpose.There are tools that are useful in the localization and translation of content. Cara gives examples of Microsoft PowerPoint's built-in translation tool and Sonix.ai, which help in rapidly reproducing content in different languages, improving efficiency in the learning design process.The use of AI avatars for role-playing exercises in instructional design helps avoid logistical challenges associated with producing videos. However, these AI avatars require human input for more nuanced performance.Segmented time stamps:(00:00) The importance of focusing on making the best learning experience possible and not the tools(01:13) How Cara uses AI in her learning design process(04:42) Some key AI tools to check out (06:25) What human input is needed from AI translation tools(10:19) AI-generated avatars(15:39) Authenticity in art and AI(20:16) Cara's advice for instructional design and using genetic AI nowLinks from the podcast Connect with Cara on LinkedInCheck out The Learning Camel 

In this episode of the Learning While Working Podcast, Britt Andreatta is back to discuss the impact of AI on organisations and the skills needed to navigate this shifting landscape. As an expert on brain-driven approaches to learning and a leading voice in the field, she shares some truly valuable insights. Tune in to learn more about the need for a clear strategy in L&D, developing strong change management skills and why we need to hone in scientific literacy and verification skills.About  Brit AndreattaDr. Britt Andreatta is an internationally-recognised thought leader who creates brain science-based solutions for today's challenges. As CEO of Brain Aware Training, Inc., Britt Andreatta draws on her unique background in leadership, neuroscience, psychology, and learning to unlock the best in people and organisations.Key takeaways:AI's influence calls for robust change management skills, and the technology's verification will need to be a key quality in job requirements – on par with communication and time management.The imperative of reskilling is gaining prominence, with the World Economic Forum identifying a substantial global workforce needing retraining.AI-driven misinformation highlights the need for critical thinking and science literacy skills. The role of learning professionals will become ‘verifiers', ensuring that AI-generated content is reliable while embracing the adaptability in a dynamic environment.Segmented time stamps:(00:00) Introduction(01:57) How will AI change the types of skills that organisations need?(03:11) Change management skills(05:12) Why is change not always successful?(07:00) Science literacy skills(12:27) Become verifiers(20:12) What should L&D be doing now to prepare for the future? Links from the podcast Connect with Britt on LinkedInVisit Britt's WebsiteRead Wired To Resist 

In this episode of the Learning While Working Podcast, Megan Torrance joins the show to share what she is learning about using Chat GPT.  We focus on using Chat GPT to enhance the learning experience itself, and just using AI to generate content.About  Megan TorranceMegan Torrance is CEO and founder of TorranceLearning, which helps organisations connect learning strategy to design, development, data, and ultimately performance. Megan has more than 25 years of experience in learning design, deployment, and consultingKey takeaways:Chat GPT can act as an assistant for learning designers. It aids in structuring content and generating examples, particularly when subject matter experts may tire of providing numerous case examples. As a result, it helps designers craft more thorough and comprehensive learning materials.In the context of medical education, AI is employed to provide detailed feedback on learners' responses to case scenarios. This feedback is compared against expert responses to provide meaningful insights to learners. However, it's crucial to ensure that the AI never gives direct medical advice – the final decision must always be left up to the learner.Inform learners if the feedback they're receiving is AI-driven. This transparency ensures that learners understand the nature and source of their feedback and approach it with a degree of scepticism, especially in sensitive areas like medical education.Segmented time stamps:(00:00) Start exploring AI but be careful(01:11) What are some of the ways that ChatGPT can be used by learning designers?(02:40) Taking a simple approach(07:39) Using AI in complicated areas in medical education and legal training(10:46) Other ways AI is being used to put in a learning experience(14:44) Using ChatGPT as an assistant(16:46) Mitigating bias in AI(18:37) Megan's greatest general advice for learning designers in using ChatGPTLinks from the podcast Connect with Megan on LinkedInTorranceLearning's WebsiteDownload Megan's one-page practitioner's guide job aid to using ChatGPTWatch a recording of the ChatGPT Driven Instructional Design: Dreams, Results, and Horrors webinar  

AI tools like ChatGPT are being used in various industries, including marketing and learning. In this episode of the Learning While Working podcast, we are joined by Lynne McNamee to explore the fascinating and evolving world of AI tools for content creation. Robin and Lynne unpack how the quality of the generated content varies, applications of ChatGPT in L&D work, and why privacy and data sources are also limitations for generative AI tools.About  Lynne McNameeLynne is a creative and strategic thinker who leverages data and technology to lead innovative organisations to measurable results through inbound, social, content, video and traditional marketing. She is the president of Lone Armadillo Marketing Agency, where she has managed marketing campaigns for companies such as Avis, HP, and Bank of America. She was cited by The New York Times for innovations in marketing.Key takeaways:Ways to leverage ChatGPT for marketing: Lynne shares how she uses ChatGPT in her work, specifically in writing copy for blog posts and websites. It's important to understand the search engine interface and user intent to generate effective content, to align with SEO strategies. Be aware of the language AI generates, as tools like ChatGPT tends to provide overly literal keywords, which can result in keyword stuffing and impact your SEO score negatively. Try out some other key AI tools, like Lumen5 and SonixAI. Lynne has been using these for tasks in video creation and transcription. She also reflects on why ChatGPT has gained the most attention compared to other tools, which is due to social proof and practical applications. Segmented time stamps:(00:00) The changing nature of marketing work (01:25) How Lynne is using ChatGPT on a daily basis(02:51) Lynne's process of writing a blog post with the help of AI(03:42) Considering SEO when using AI generated content(06:25) The impact of quality from using ChatGPT(08:12) Training AI to write learning material(12:43) Some of the weaknesses of using a tool like ChatGPT (19:28) Why has ChatGPT gained so much attention and widespread adoption?(20:38) Lynne's main bit of advice around using AI at the momentLinks from the podcast Connect with Lynne on LinkedInLone Armadillo Marketing Agency's WebsiteListen to Using learning campaigns to effectively drive behaviour change with Lynne McNameeCheck out Lumen5Try out Sonix AI  

In this episode of the Learning While Working Podcast, Ray Jimenez talks about how employees are using AI for learning. Ray will share practical examples of incorporating ChatGPT into the learning experience, such as learner familiarisation, troubleshooting, and coaching. About  Ray JimenezRay Jimenez Ph.D. is the Chief Learning Architect at Vignettes Learning, trainingmagnetwork.com and situationexpert.com. He has worked with the American Bankers Association, Neiman Marcus, the US Air Force, NASA, Blue Cross, Goodwill Industries, Pixar Studios, among others. Ray's expertise is in microlearning, story-based learning design, scenario-based learning design and creative problem solving.Key takeaways:There have been successful experiments using ChatGPT's integration in learning platforms, such as rapidly familiarising technicians with new subject matter, accelerating ISO certification processes, and enabling coaches to provide targeted prompts and expand learners' growth mindset.The potential for private data integration in ChatGPT offers exciting opportunities for companies, allowing learners to explore and interact with their own proprietary information, creating a closer connection between learning and real-life work situations.Working with AI involves recalibrating the way we think about learning, moving away from a reliance on content delivery and toward nurturing critical thinking, questioning, and debating skills, thus enabling learners to become more autonomous and better equipped to navigate the complexities of the modern workplace.Segmented time stamps:(00:00) We need to recalibrate our thinking in learning away from content(01:56) How ChatGPT can be used by learners(05:04) On workplaces having their own Generative AI tools(11:08) The idea of templates for learners(16:00) Using AI for more hands-on and physical work(19:34) Examples of using critical thinking alongside AI(27:14) ChatGPT being more generalised than specialised Links from the podcast Connect with Ray on LinkedIn5 Experiments in ChatGPT/Situation Expert  

In this episode, Robin is joined by Lars Hyland and Matt Linaker from Totara to discuss rethinking workplace learning in an AI-Driven World. The conversation focuses on the importance of shifting from content-driven strategies to more context-based and collaborative learning environments. About  Lars HylandLars Hyland is a seasoned expert in learning technology with over 27 years of experience. He has worked with various international organisations and educational institutions, including the University of Oxford and Deutsche Bank. Currently, he leads Totara's EMEA operations, focusing on talent development and productivity. About  Matt LinakerMatt has a multifaceted career in the field of learning and education, with a focus on technology-enhanced learning.  He is currently the Partner Onboarding and Enablement Lead at Totara Learning.Key takeaways:AI tools have gone mainstream. It is impacting creative arts and we can see how it has helped improve the way we work. There is potential for governments and organisations to have their own large learning models and AI to enhance learning while working.Content-driven models in the workplace have caused a disconnect between business goals and training outcomes. New technologies can assist in connecting people to the right people at the right time, and automated feedback can aid development.Easy access to the right content to the right people can help contextualise the learning process, and conversations and collaboration can help people come together quickly to solve problems and meet goals. Providing feedback and rewarding people in an intentional way, contextualised to the situation, can help motivate them to learn and to apply their knowledge effectively. Segmented time stamps:(00:00) One of keys to the future of AI is open source  (01:35) What does the future of work look like?(04:59) How AI has gone mainstream(10:13) Moving away from content-driven approaches (15:32) L&D in Totara(19:19) Building learning platforms for talent experience(24:04) How can we make this future of learning happen now? Links from the podcast Connect with Lars on LinkedInConnect with Matt on LinkedinTotara's WebsiteRead more about Matt's thoughts on Rethinking workplace learning in an AI-Driven World  

In this episode Robin and Danielle discuss the influence of AI on learning design, its potential to standardise educational experiences, and the importance of maintaining human skills like critical thinking in AI applications. It's a fascinating discussion which delves into the creative potential of AI and self-learning. The recent ‘hype' surrounding AI calls for continual learning and community collaboration to understand and leverage this technology effectively.About  DanielleDanielle is a Learning & Development and business professional with Fortune 100 experience. As a passionate learner and critical thinker, She has dedicated herself to navigating through the hype and staying up-to-date in the world of learning development. She is currently Chief Learning Strategist at Beyond the Sky: Custom Learning Solutions.Key takeaways:Embrace neural networks for creativity: Danielle highlights how neural networks excel at making unexpected connections and providing creative ideas without bias. By leveraging AI as an assistant, we can tap into new perspectives and unlock innovative solutions.Human skills in the AI Age: Critical thinking is an invaluable human skill that AI lacks. It's important to nurture our critical thinking abilities and leverage our unique human qualities to complement AI technologies.Staying ahead in Learning & Development: The learning and development field must keep pace with technological advancements. There is a need for continuous learning, networking, and embracing new knowledge to create effective solutions. By staying informed and sharing expertise, we can shape the future of learning and development.Segmented time stamps:(00:00) Looking beyond the hype (01:32) Running an AI and L&D community of practice: what does that look like? (02:45) Common trends and questions people are asking in the community(03:33) The risks of unregulated usage of AI within organisations(07:43) Some great examples of leveraging AI(15:58) Reassessing what it means to be human(17:03) Using AI in creative work(20:15) Danielle's key piece of advice around using generative AI Links from the podcast Connect with Danielle on LinkedInListen Daniellele's podcast You in 2042 ... The Future of WorkFind out more about the AI in learning community of practice   

In this episode of the Learning While Working Podcast, David James joins the show to share his expertise and insights in Generative AI. David sheds light on why Generative AI is not simply a shortcut to faster and cheaper courses, but rather a disruptive force. He also talks about reinventing the learning process, the role of reflection, and how to not make your job redundant. About  DavidJosh Cavalier has been creating learning solutions for corporations, government agencies, and secondary education institutions for nearly thirty years. He is an expert in the field of Learning & Development. He has applied his industry experience to the application of ChatGPT and other Generative AI frameworks for business and life skills.Key takeaways:The big risk of relying solely on AI for producing course content is that it might render learning and development redundant. Instead, David encourages professionals to embrace the unique value they bring to address specific skills gaps in their organisation.Administrative tasks, be gone! Generative AI streamlines the learning experience by taking care of the administrative aspects, allowing educators and learners to focus more on effectively addressing real organisational challenges. By using internal data sets, Generative AI can help tackle the root of my performance  problems.It's about the learning process. Instead of relying solely on delivering information, the emphasis should be on enhancing the learning journey through practice, reflection, and behaviour change. Segmented time stamps:(00:00) AI is the path to making courses faster and cheaper. Doing this will make you redundant.   (01:38) What does Generative AI mean for L&D in the future?(05:08) How Generative AI can help us improve the actual learning process(11:03]) Viewing AI as a co-pilot(13:27) Distinguishing what L&D is(17:18) What will be talking about AI in 10 years time?(21:38) David's main piece of advice for leveraging Generative AILinks from the podcast Connect with David on LinkedInFind out more about Learning360Read David's article on What Future Does Generative AI Signal For L&D? 

In this episode, we explore the concept of using AI to enhance our strengths and compensate for weaknesses, prompt engineering techniques for L&D. Today's guest is Josh Cavalier, who is helping people in L&D utilise AI tools effectively.  About Josh Josh Cavalier has been creating learning solutions for corporations, government agencies, and secondary education institutions for nearly thirty years. He is an expert in the field of Learning & Development. He has applied his industry experience to the application of ChatGPT and other Generative AI frameworks for business and life skills.Key takeaways:AI is a tool, not a replacement: Josh highlights how AI, specifically large language models like GPT, can augment traditional processes within L&D. Its powers are not in replacing humans, but as an aid to boost productivity and creativity.L&D professionals need to have a baseline knowledge of AI: It's important for L&D practitioners to have an understanding of how large language models and AI tools work. This will be essential as these tools become increasingly integrated into L&D processes.Where to begin with learning to use AI tools: be prepared for the learning curve associated with using AI tools effectively. Josh suggested starting with an AI like GPT and learning how to prompt it effectively. Using prepared prompts (like his ‘150 prompts for L&D') can be a helpful starting point.Segmented time stamps:(0:00) Everyone in L&D needs to understand AI(01:18) AI augmenting our superpowers(04:21) Shadow tech and security risks (09:14) Scale and graphics card limitations(12:33) Prompt stacking technique(17:23) Difficulties of evaluating AI tools(22:00) Workflow and AI prompts(26:42) AI tools in L&D Links from the podcast Download Josh Cavalier's 150+ Prompts for EducationConnect with Josh Cavalier on LinkedInVisit Josh Cavalier Website 

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 contentSegmented time stamps:(00:00) We need the think about how AI shift what organisations do(02:43) What AI means for the future of work(07:47) What AI means to be human(10:39) What is L&D's role in AI technology?(15:32) Why trust in technology is crucial for future success(19:38) Skills in trust, critical thinking, and human decision-making(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.Segmented time stamps:(00:00) The argumentation of human lead learning(01:58) AI in workplace learning(05:35) Adaptive learning experience pathways(08:15) On-demand learning for safety leadership(11:41) Content curation and updates(16:07) The risks of using AI in L&D(21:33) The role of humans and AI in the workplace(24:53) Balancing the use of AILinks 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.Segmented time stamps:[01:46] Insights from his book ‘The Modern Learning Ecosystem'[04:44] A framework to help connect tools for learning solutions[09:19] The disconnect in organisations hinders problem-solving and learning[13:19] Differentiating shared knowledge vs. performance support[17:46] How to influence everyone in the organisation[24:00] Embracing learning as a constant, and why reinforcement is vital[30:56] Replacing the word ‘Learning' with ‘Helping' in our job titlesLinks from the podcast:Read the The Modern Learning Ecosystem - A New L&D Mindset for the Ever-Changing Workplace  Connect 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.Segmented time stamps:(01:53) The possibilities of leading with change(05:01) Creating a sense of belonging when working remotely(06:37) How to successfully navigate change in organisations(11:35) Understanding people's relationships with stress and change(13:14) Addressing the gap many managers have in their capabilities around change(19:48) Building equal relationships and the people-side of business(22:55) What to do with unexpected change in the workplace(26:26) How L&D managers can help support the change processLinks 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.    Segmented time stamps:(01:46) What do we mean by organisations being adaptive?(05:16) How Nous Group are designing learning experiences(10:17) Implementing the case-in-point approach(13:46) The importance of debriefs(16:34) How L&D can help people become more adaptive in their cultural behaviour(23:06) Advice to L&D teams to be more adaptive themselvesLinks 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.Segmented time stamps:[01:59] What learning retention means to Sheila[02:53] The universal aspect of learning retention[04:00] Ways to increase retention[07:18] The problems with the ‘Testing Effect'[11:10] The role of demonstration during training sessions[13:45] Understanding the ‘Spacing Effect'[19:51] Having a module to inform students about learning retention[21:13] Sheila's advice for increasing retentionLinks from the podcast  Connect with Sheila B. Robinson on LinkedInFind out more about ​​Custom Professional LearningCheck out the Head First series series of books   Check 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.Segmented time stamps:[02:31] Some of the key benefits of learning campaigns[04:03] Understanding the differences between advertising, marketing, and PR[07:56] Using personas to enhance learning campaigns[10:25] How to personalise learning experiences for different learner personas[19:07] Exploring tools for engaging learning experiences[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.Segmented time stamps:[01:10] Why the Met Office established the People Framework[04:55] The current leaders and their backgrounds[06:34] Guiding the professional leaders[09:39] The role of a Community of Practice Manager[10:19] Creating content for the community of practice[12:28] Building a safe environment[16:41] Evaluating the impact of the community of practiceLinks 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.Segmented time stamps:(01:55) The challenges of L&D delivery(03:13) Overcoming some of obstacles with collaborative learning(05:59) The link between collaborative learning and performance outcomes(09:57) Performance consulting for L&D and overcoming blockers(14:48) Examples of good collaborative learning(22:53) Embracing the upfront efforts with collaborative learning and development(24:37) Leveraging technology to improve leadership and management skillsLinks 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.Segmented time stamps:(02:01) Rustica's personal learning experience of using Augmented Reality(07:36) Her process of finding the right AR technology to use(08:29) What is the learning potential with AR?(12:54) The costs associated with AR technology(14:26) The three phases of her process/ product development(18:53) How does AR change the instructional design process?(23:35) Where L&D experts can get started with ARLinks from the podcast  Visit Bloom Learning TechnologiesConnect with Rustica on TwitterCheck out UnityCheck out NianticCheck out LightshipCheck out STEPN

Todd Moran joins the show to talk about the social aspect of assessment including peer assessment, handling pushback from learning designers and other stakeholders, and some more effective methods of online assessments that quizzes.About Todd MoranTodd's professional career has spanned start-ups to non-profits and large multinationals, and his current role at NovoEd as the Chief Learning Strategist. From the megatrends in learning and enterprise collaboration to technology evaluation and implementation, to the ‘people' side of organisational change and talent development, he covers the gamut of understanding what it takes to enable a successful digital workplace and deep employee engagement.Todd holds a B.A. in Organisational Psychology from Middlebury College, and an M.A. in Information & Learning Technology from the University of Colorado. Key takeaways:Assessment needs to be completely relevant and incorporates socialisation. Firstly, we often miss the nature of embedding some of those assessments in the specificity of the context they should reside within. Secondly, the social aspect gives a more holistic view of assessment, that is not just individual knowledge.Consider the gradient of effort when scaling assessment across an organisation. Think about lower points of entry that still return big value when it comes to casting a net wider socially, e.g. about who could assess one's work, products, tasks, etc.Learning about work should be a team activity and we need to shift the perspective of learning designers and other stakeholders who think it's just for individuals. Ask them questions such as “how applicable is the scenario or the experience or the intervention you're designing?“, and tie in the alignment to how that individual can then perform in a work setting.Segmented time stamps:[01:54] More effective ways of online assessments[04:41] Considering the social aspect of learning[08:14] What we mean by ‘assessment'[10:46] Working with learning designers and other key stakeholders to shift their perspective[14:52] Having an education mindset[18:33] Making assessment more socialLinks from the podcast  Connect with Todd on LinkedInLearn more about NovoEdListen to NovaEd's Wildly Capable podcast Join NovodEd's free Learning Experience Design: From Ideas to Impact course  

About Geoff RipGeoff Rip is the Founder and Principal Designer at Training That Works. He is a highly experienced and passionate learning professional with rich and diverse knowledge. He specialises in quality production of end to end learning, utilising social learning and technology, with a dedicated focus on increasing capability resulting in performance uplift.Key takeaways:Transfer is a learning process. L&D experts tend to brush over this part, but they need to view it as a fundamental part – we need to be designing for transferRetrieval practice is about pulling learning from the brain as opposed to pushing information into the brain. Techniques include mind-mapping, multiple choice questions and storytelling.Reflection is a key skill for each step, so it shouldn't be left to just the end. This is a great way to help people become ‘self-directed experiential learners', and can be done through a variety of ways including coaching.Segmented time stamps:(01:56) The main challenges with transferring learning into practise in the workplace(05:10) Fitting in formative assessment with learning transfer(06:33) What is retrieval practice?(12:25) The definition of ‘spacing'(13:34) Why it's so important to help people apply what they have learnt(19:01) How to design cycles into the learning experience(27:02) Geoff's top advice for increasing the transfer of learningLinks from the podcast:Connect with Geoff on LinkedInRead ‘How I Obsessively Learned 90 Skills in Only 3 Years'

About Keith Keating    Keith Keating  is a workforce futurist and his mission is to empower, enable and encourage our workforce to prepare for the future. He is currently the SVP, Chief Learning Officer at Archwell, which provides cross-functional support to the greater mortgage industry. He is the former Head of The Global Learning Network for General Motors.Key takeaways:Learning transfer doesn't always occur as many of us learn in safe environments, such as universities, but they don't prepare us for the ‘real' world.The principles of Science of Learning works and teaches us about elaboration, generation, spacing and nesting. It's an area L&D experts need to learn more about and leverage from. We should be trusted advisors in L&D about how adults learn.What happens after the nesting period is very powerful. Archwell conducts ‘assessments' about a month after nesting, through reflective questions such as how relevant the information has been, how prepared people have felt after the course, etc. It's more of a reflection piece and not a test. Segmented time stamps:(03:31) The greatest challenges with learning transfer(07:17) Adopting academic capabilities as an approach at Archwell(09:23) Understanding the science of learning for L&D professionals(12:27) Getting people to reconnect with learning(16:32) The nesting process(23:47) Evolving your post-assessment questions(25:24) Advice to people who want to use assessment to drive learning transferLinks from the podcast  Visit Keith's WebsiteConnect with Keith on LinkedInCheck out ArchwellCheck out The Learning-Transfer Evaluation Model (LTEM)Read ‘Make It Stick'Read ‘​​Performance-Focused Smile Sheets'​

About Cara NorthCara North has worked in the instructional design field for more than a decade and has won multiple awards for her learning experiences. Cara has worked in both higher education and corporate, and runs her own consulting business, The Learning Camel. Some of the clients The Learning Camel has served include Universal Records, WesBanco, NASA, Daisy and the National Association for Talent and Development (ATD).Key takeaways:There are many engaging and impactful ways of conducting assessments. Go beyond just providing formal multiple-choice questions, and try out different types of workplace assessments. Many people get anxious when they hear the word “assessment”, so make it user-friendly.It's important to ask the right questions. When creating your own L&D material, get really clear on what can be achieved. Ask your clients questions such as what are the business needs? What is the desired state? Can training fulfil this? View your role as a consultant, not just content generators, to drive impact.Engage stakeholders: your work is more than just a report card. Begin with the basics and find alignment with stakeholders. Then start with the basic tasks to provide hands-on experience that people can learn from, then build up. This is great for task-based assessments.Segmented time stamps:(02:12) The opportunities with digital learning development(04:50) Handling people's previous experiences of assessment(08:52) Assessment learning can help focus teachers and efforts(13:25) The right questions to ask when putting together workplace training(21:24) Advice on engaging stakeholders(27:31) How to improve your assessment practicesLinks from the podcast:Connect with Cara on LinkedInCheck out The Learning CamelRead about the Four Levels of EvaluationListen to the interview with Jeff Kortenbosch

About The Assessment SummitThe Assessment Summit brought together some of the world's most accomplished learning experts to share a smorgasbord of practical, actionable advice on assessment – and about 80% of the speakers have previously been on the podcast.Key takeaways:Why do people have such negative associations with assessment? Paul Kearney, Enterprising Education Specialist at Enterprise Design Consultancy presented an interesting talk on ‘The Myths Of Assessment', and he reflected on why so many people have had bad experiences, through exams, etc. As L&D experts, we need to shift our thinking about this term – it's about feedback and moving forward.Assessment design. Often in our practices multiple choice questions are our default as a type of assessment tool and strategy. Jenny Saucerman, Online Learning Instructional Design Manager at Credit Union National Association demonstrated how scenario questions are a great way to predict someone's future performance. We also learnt about VR assessment tools and embracing that assessment happens over time.Assessment in the creative industries. Learning is quite often the process of solving a problem, and the evidence to the solution then becomes the assessment. It's about not giving the answers, but delivering collaborative approaches and peer work assessment.Digital Assessment. Cheryle Walker, Founder, Innovator, Consultant and Facilitator at Learn LIVE Online touched on some technical considerations such as running verifiable virtual assessments. Dan McFadyen, MD at Edalex, spoke about using micro credentials as a way to connect, recognise and uncover skills. It was also fascinating to learn more about the rich source of data you can obtain from assessments, which Bikram Kawan, Software Engineer at Sprout Labs delved into.Segmented time stamps:(02:16) Why so many of us associate ‘assessment' with fear(04:17) Measuring the impact of our work(06:12) Assessment design(09:07) Using VR(11:18) The role of assessment in creative industries(15:28) The opportunities and challenges that come with digital assessment(17:06) Leveraging from your rich sources of dataLinks from the podcast:Access all talks from The Assessment Summit

About Ray Jimenez Ray Jimenez Ph.D. is the Chief Learning Architect at Vignettes Learning, trainingmagnetwork.com and situationexpert.com. He has worked with the American Bankers Association, Neiman Marcus, the US Air Force, NASA, Blue Cross, Goodwill Industries, Pixar Studios, Edison Missing Group, Dendreon, Netafim, Progressive Insurance, Bridgepoint Education, and the California Institute of Technology among others.  Ray's expertise is in microlearning, story-based learning design, scenario-based learning design and creative problem solving. Key takeaways:The frontline leader is someone who coaches and troubleshoots on the job. Ray explains that workers need to focus on developing their skills in troubleshooting and thinking on the spot. Frontline workers day-to-day experience unpredictable environments and unique problems, so we need to empower them to think more.The most important tool is to have a dynamic thinking process for every worker – it's not about having all the answers. This redefines what we mean by working, which is about facing constant trial and error and discovering solutions. By applying tools like consequence thinking, learning becomes a natural byproduct.The role of assessments. Ray questions why there needs to be formal assessments alongside the learning process. It's natural to assess and recalibrate all the time, so assessment becomes a built-in process. It's not about proving your knowledge to anyone, it's there to demonstrate if something is working or not working.Segmented time stamps:(02:46) What is a frontline leader and how they can become learning accelerators(07:58) Why Ray is focusing on the frontline worker(11:56) Some tools to help frontline managers become learning accelerators(16:58) Informal versus formal learning(18:56) The role of L&D in this new way of workplace learning(22:05) Rethinking the role of assessmentLinks from the podcast:Visit Ray's WebsiteConnect with Ray on TwitterCheck out Situation ExpertRead ‘25 Thinking Tools'Listen to our previous interview with Ray Jimenez Sign up to Training Frontline Leaders as Learning Accelerators

About Jeff KortenboschJeff is the author of the acclaimed book ‘20 Questions Learning and Development should ask before talking about training', in which he advocates measurable performance and business outcomes and relevant solutions that go beyond training. He is also an illustrator of digital explainer visuals. Since he started visualising ideas, his work has been seen by millions of people online.Key takeaways:Drawing and producing graphics is a great way to learn. It has been a great creative outlet for Jeff as it has helped him visualise ideas through simple graphics – ranging from graphs to icons. Investing in courses has helped him develop some foundational skills in drawing. Jeff's best advice is to be minimal with your design, and see what you can draw from quotes, thoughts or visual metaphors.Sticking to a daily habit of drawing has helped Jeff develop his drawing style. He started off with a target of drawing for 100 days, and kept a notepad to hand for whenever he got inspiration. The daily habit ensured he wasn't fixated on perfection but simplicity: “create fast and publish fast”. The key is to start small, whether this is through length of time to draw or finding a good time slot that you can stick to daily.The power of visuals: as the adage goes, "a picture is worth a thousand words", so being able to harness your visual skills is powerful as a learning designer. From presentations to your own personal learning process, visual design is a powerful method. It can also give you a great reach online, as visuals help draw people into your blog posts, newsletters, courses, etc.Drawing teaches you additional skills: Jeff found that by drawing regularly, he also learnt more about publishing, social media marketing, ideation and finding new ways to keep ideas flowing.Segmented time stamps:(02:44) Regularly publishing graphics(06:17) Some of the most well-received graphics Jeff has designed(07:32) How to stick to a daily habit(09:48) Why drawing diagrams is a great way to learn(14:22) Using drawing as a micro-learning strategy(16:30) What to incorporate in a visual email marketing course(19:16) How to build a regular habit of drawingLinks from the podcast:Visit Jeff's WebsiteConnect with Jeff on LinkedInRead ‘Atomic Habits' by James ClearCheck out FigmaCheck out Blair Rorani's workRead ‘20 Questions Learning and Development should ask before talking about training'Listen to our previous interview with Jeff Kortenbosch

About Joshua GillinghamJoshua Gillingham is an author, game designer, and editor from Vancouver Island, Canada. His fantasy trilogy ‘The Saga of Torin Ten-Trees' is an adventure inspired by the Norse myths and the Icelandic Sagas. Joshua is also the co-author of ‘Old Norse for Modern Times' alongside Ian Stuart Sharpe and Dr. Arngrimur Vidalin.In partnership with Outland Entertainment, Joshua is the founding Worldsmith of the trans-media Outland 'Althingi' World set in Viking Age Iceland, featuring his original card game Althingi: One Will Rise and the groundbreaking anthology Althingi: The Crescent & the Northern Star.Key takeaways:Give learners/ players agency: Learning is an internal process, so figure out how learners can take the information you're providing, and make it a part of their lives. Learners need flexibility and relevant information so that what they learn can be applied for the long-term. To understand different perspectives within the company, consider conducting small group discussions. Prompts and reflective questions are a great way to give agency.The role of ‘randomness' in games has the advantage of surprise and chance. It frustrates the stronger skilled player, whilst the less-skilled player can see an opening and a chance. In learning design, this could be done through suprise questions. Strategically, make sure you give learners a bounded space, e.g. a physical game, to keep them on task, but provide enough agency so they are engaged.Leveraging physical space on game boards: Learning Designers can build a physical space for people to learn from. For game designers, every piece on a board has a cost attached to it, so ask yourself “is this enhancing the experience?”. Be clever with using the most from as little as possible. Segmented time stamps:(02:13) What do we mean by ‘space' in game design?(04:39) How Learning Designers can give players first-level agency(07:52) The notion of ‘roles', and why Learning Designers need to consider this more in their strategy(09:50) Strategies for building ‘randomness' in game design(13:07) Learning from the rule books of the most popular games(16:10) On the space of physical boards(20:29) Multiple pathway learningLinks from the podcast:Visit Joshua's WebsiteConnect with Joshua on TwitterListen to the Learning While Working Podcast interview with Warren KennardCheck out Magic: The GatheringCheck out BoardGameGeek

Michelle Ockers is an organisational learning strategist and modern workplace learning practitioner. She helps organisations build high-impact L&D functions by developing and implementing their learning strategy, mindset and skills – and helping L&D professionals become business partners that create value. In this episode, we reflect on what are some of the critical skills for L&D teams, being mindful of our blindspots, how L&D experts are ‘impact explorers', and some key insights from her podcast, Learning Uncut. About Michelle OckersMichelle spent close to three decades in learning and development. After 16 years in the Royal Australian Air Force, she brought her training and project management experience into the corporate sector. In 2018, she started her popular podcast, Learning Uncut, helping L&D professionals share real stories about their work. The podcast became a global go-to source for examples of leading edge industry practice, matching her vision for the industry's potential – and how we can achieve that together. She then made Learning Uncut into a network to offer L&D leaders everywhere the opportunity to thrive, with the support of leading experts.Key takeaways:There are some critical skills needed for L&D teams to be relevant. Michelle highlights some ‘human skills'' like leadership, critical thinking and communication, as key skills to develop within your L&D team. We can't master every skill ourselves, but if we ensure some of the most critical skills across our team are covered, we are able to watch out for any blindspots.Performance consulting is a must-have skill in particular. A successful L&D team is able to demonstrate business impact, not just learning impact. Michelle best describes this skill from the Learning and Performance Institute definition: “it's about partnering with customers and clients, to analyse performance gaps, recommend appropriate interventions and measure the outcomes.”Consider some mindset shifts for your L&D team. If we do a good job with our learning programs, we don't need to be there the whole time. L&D teams are very supportive, but they need to know when to let go. Review how we can partner and equip with the rest of the organisation – and how we can effectively support learning.Segmented time stamps:(02:45) What are the key capabilities that L&D professionals need to demonstrate?(07:46) What we mean by ‘soft skills' - Rethinking these as ‘Human skills'     (12:21) On speculative learning(13:18) What is ‘performance consulting'?(19:11) Not being tied to one learning technology(20:52) Some key mindset shifts for L&D professionals (25:39) Michelle's Gap finder tool(28:25) The art of role modellingLinks from the podcast:Connect with Michelle on LinkedInListen to the Learning Uncut podcastDownload Michelle's Gap Finder Tool  Capability Gap Finder resourceFind more about Learning UncutCheck out The Future of Jobs Report 2020Listen to the Learning While Working Podcast interview with Jeff Kortenbosch Check out The Learning and Performance Institute MapCheck out Emerging StrongerCheck out RedThread's Research on Learning Technology EcosystemsListen to the Learning While Working Podcast interview with with Dani Johnson 

About Ant PughAnt is a self-employed learning design consultant and instructional designer, with a career in learning and development spanning twenty years, with experience working in several continents, and global clients including ANZ, Westpac, Link Group, Microsoft and Carnival. He is renowned for using a performance-based approach to design training, passionate about implementing human-centred solutions to change behaviour, improve performance and deliver measurable business results.Key takeaways:The vast majority of learning is ineffective. Ant unpacks how a great learning designer questions everything and trusts their instincts. It's very easy to just copy what others are doing, but if you ‘break out' of the L&D world and review how else you learn in your day-to-day life, it's easier to think outside of the box.Writing is a great way of teaching (and learning). From writing a daily email to his mailing list, Ant has become a better writer and has learnt a lot more about learning design. Find your medium where you can capture – or report – daily on what you have learnt or thought about to a community, no matter how small.Some of the biggest blockers for writing are not knowing who you are writing to and your mindset around writing. Ant has reframed what writing is to him – it's about documenting, not creating content. This has been a powerful way to beat overwhelm for Ant, which enables him to write so frequently in a flow state. Focus on being a reporter rather than a leader or teacher, and simply share with others what has worked for you so far.Segmented time stamps:[02:26] How to become a better learning designer[04:34] Ant's strategy to seeing things differently[07:10] How to move forward in new ways of thinking[13:57] Why learning designers should write more[17:41] Making the time to write daily and Ant's writing process[21:20] Some of the biggest blockers for writing – and how to overcome themLinks from the podcast:Subscribe to Ant's daily newsletterConnect with Ant on LinkedInFind more about Ant PughCheck out GaryVee's YouTube channel,  Watch GaryVee's ‘Document, Don't Create' video on youtubeWatch recording of Sprout Labs webinar ‘Creative thinking for learning designers'