Podcasts about learning while working

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 

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  

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.

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

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 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 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 Dani JohnsonDani is the Co-founder and Principal Analyst for RedThread Research. Before starting RedThread, Dani led the Learning and Career research practice at Bersin, Deloitte. Her ideas can be found in publications such as The Wall Street Journal, CLO Magazine, HR Magazine, and Employment Relations. Dani holds a Master of Business Administration and a Master of Science and Bachelor of Science degrees in Mechanical Engineering from Brigham Young University.Key TakeawaysRedThread's Next-gen Learning Method Report demonstrates that the ways people work are changing – and that the methods companies use to learn must keep pace with those changes. Their research shows that there are more than 60 methods that enable employee L&D, from the way employees consume information to how they can learn from one another.When it comes to analysing data, it's important to be able to ‘sift through' and identify actionable information. Dani gives a great example of benchmarking, and that it shouldn't be a primary influence for an organisation, but a consideration. She also stresses the importance of being tech-agnostic.Dani also shares how skills development is important as L&D roles are becoming more central to organisations. The need for durable skills such as critical thinking, communication and leadership will be needed for such roles.Segmented time stamps:[01:50] Why RedThread produced the next generation learning report[03:20] The RedThread Employee Development framework[04:46] On how they conducted their research and what surprised them most from their findings[07:54] Some key takeaways for L&D professionals[11:56] Why L&D experts are making use of what they already have in organisations[15:25] On the need for skills development[17:10] The need for mindset shifts for L&D professionalsLinks from the podcast:Connect with Dani on LinkedInFind more about RedThread ResearchCheck out RedThread's Learning Methods Infographic

About Aman Ed    Aman Eid is a social neuroscientist of learning and an organisational designer concerned with how organisations transform via learning efforts. Coming from an interdisciplinary colourful background enabled Aman to have a unique approach to tackling the challenges facing organisations. In the last 14 years, Aman led and contributed to designing and redesigning 100s of learning journeys of agile teams, leadership communities, and organisational landscapes. For organisational reinventing to work, we need to reinvent the ways we learn together in organisations, and for organisational learning to work we need to reinvent the intentions of leading the learning efforts.Key takeaways:As many of us are reimagining the world of work, we also need to reimagine how we learn. Many of us have been caught up in the traditional way of working which focuses more on task mastery, neglecting the human side of work. Aman highlights that organisations are essentially “you and me” – a place where humans work together.We can learn from big tech companies when it comes to reimagining the future of work. As they are growing at an accelerated pace, we can quickly see what their success and failures are, and apply where needed to our workplace. A common weakness of big tech companies is their lack of hiring diverse talent, often due to their pace of hiring, so this helps us stick to the path of maintaining a diverse culture.L&D experts can help organisations reimagine learning by ensuring all employees have a platform to share their voices. By nurturing the “invisible leaders”, the key decision makers can then listen and be open to change.Segmented time stamps:[01:50] Why we need to reimagine organisational learning[04:25] Redefining work relationships[06:14] What we can learn from Big Tech companies, including their struggles[12:44] Bringing diverse talent to the organisational level[15:31] How an L&D expert can help facilitate the “invisible leaders”[20:32] Aman's key advice with reimagining workplace learningLinks from the podcast:Connect with Aman Eid on LinkedInMore about Aman Eid

About Eva KeiffenheimEva Keiffenheim left teaching in Summer 2020 to become an EDUpreneur. Her life's mission is to make education fairer and better for as many learners as possible. She is a writer, and helps research, consult, and implement education projects. She also co-founded Speed Up, Buddy!, an NGO to support first-gen students. She shares in her weekly newsletter of +3K subscribers, Learn Letter, where she shares useful tools and resources.Key takeaways:Eva shares the three things that organisations can do to help their employees become lifelong learners:Provide opportunities for continuous learning. This might be a formal learning pathway that is made up of courses or collections of resources. It could be structured stretch projects, peer groups or suggested workplace learning activities.Leverage from powerful technologies. Studies have shown low completion rates come from limited engagement, e.g. just watching videos, and there are plenty of EdTech solutions that help provide more active learning, for example Maven, a cohort-based course (CBC) platform. Ultimately, adopt technologies that can help facilitate ways of engagement, e.g. testing, leaderboards and immediate feedback.Make space and time to learn and practice. It helps learners get into the flow of absorbing information, and gets them out of the ‘content consumption' trap. The main thing is to make sure that learners have enough time to repeatedly practice what they're learning.The human brain's ability to recall information diminishes, and it's no flaw of human memory, so include this fact in your corporate learning designs. E.g. revisit the topics, don't just lecture!Good grades alone don't reflect acquired learning. Having just a visual dashboard and tracking time spent are not enough. Consider accountability systems and ways to embed motivation within your learning platform.Encourage learning exchange and the concept of learning in public through feedback and connections. For example, share your notes or internal blogging.Segmented time stamps:[02:50] The three things organisations can do to help their employees become lifelong learners[05:41] Why it's important to schedule in time for learning[07:47] Key strategies to practise new skills in the corporate environment[09:12] Leveraging technology to acquire new skills[13:36] The role of dashboards and measuring real progress[20:28] How to make the most out of note taking[22:27] Applying cognitive science to your learning design[27:22] Eva's key advice to L&D expertsLinks from the podcast:Connect with Eva on LinkedInEva's WebsiteFollow Eva on MediumFind more about Roam Research  Read the book Make It StickRead the book Atomic HabitsDo a course on MavenDo the course Learning How to Learn: Powerful mental tools to help you master tough subjects with Barbara Oakley

About Trish UhlTrish works with learning & talent development professionals, people leaders, and other businesses executives on engineering dynamic ecosystems to equip and empower their people with data, analytics, and tech to enable the cultural transcendence necessary to power this kind of strategic change.Key TakeawaysOne thing L&D people get wrong when it comes to data is starting by looking at data. Instead, it should be more about starting with a business challenge or opportunity in mind—and then sourcing the data we need, whether it's already available or needs to be generated or a combination thereof.It's not about the learning function as much as it is about using data to generate the insights to drive the outcomes that allow others in the organisation to make better decisions.Data should be used to improve our processes. Data should allow us to expand our understanding and the context in which we're using data to help us make more quality decisions.The whole point of evidence-based practice is to use the best quality data we have available, and this can include:DataOur judgment and expertiseStakeholder's expertise, experience, and perspectiveScientific literature and academic researchThere are so many other data sources that we can use in addition to learning data, for example, Kirkpatrick's four levels of evaluation or smile sheets. We can line those pieces up to be able to have a journey that actually helps us over time to drive outcomes.While financial performance has been a critical indicator of organisational success in capitalist countries, the performance metrics are changing as we move into a more sustainable business world.“Even though profit is important, it can't be the sole focus anymore – it's about people, the planet, and prosperity for all” – TrishUsing existing logic frameworks and measurement scales that have been academically vetted and rigorously tested in the field can help us collect data and reach conclusions faster.We should use existing logic frameworks to answer the big questions - there are proven ways to measure qualitative data such as employee engagement, culture, safety, leadership, and much more. We just need to become aware of what tools already exist and take advantage of their reliability.“It's not just about the analyses, and it's not just about playing with data. It's also about being able to compel action. We need to take that analytical insight and actually compel action with that” – TrishLinks from the podcast:Connect with Trish Uhl on LinkedInTrish Uhl on LinktreeLearn more about Owl's LedgeUtrecht Work Engagement Scale -  for reliable, validated instrument for measuring, monitoring, managing employee engagement 

How do you find time to upskill while working full time? This episode we talk about how we keep our skills sharp while balancing work and life. Timestamps 00:01:02 - Cao's House inspection 00:03:38 - Why should you study after leaving uni? 00:10:20 - Learning through your Job 00:18:33 - Career Capital 00:28:22 - Professional Certifications 00:37:33 - Immediate benefits from a professional cerifications 00:44:44 - Building a learning plan 00:51:34 - Cao's Current Career Direction 01:00:36 - Justin's Plan 01:05:33 - Study Groups are Fun 01:09:04 - Recap 01:12:09 - Song recommendations Song Recommendations Imagine Dragons - Enemy Boy Pablo - Dance Baby

About Austin WelchAustin is the co-founder of Sage Media, a company focused on producing training and development content that is captivating and engaging for the learner audience. He combines research from behavioral psychology, cognitive science, and adult learning theory to create educational films that resonate with the audience and drive behavioral change. Through a combination of learning strategy, story design, and video production, Austin is revolutionizing the way that companies train and connect with their employees. Key Takeaways“We must create environments in which learners can find their own intrinsic motivation.” - AustinThe three key nutrients for intrinsic motivation include:Sense of autonomy: allowing free will to guide your decision makingSense of mastery: feeling good about your skills and what you doSense of relatedness: how we relate to the world and the people in oursWhen creating a mandatory course for employees, you can still create a sense of autonomy by giving them options such as what order they flow through the course or being able to choose when to take the course.A sense of mastery can be encouraged when you ask them to bring their own life experiences and lessons into the course.To boost relatedness, you can create message boards and forums where learners can bounce ideas off each other and connect around the content they're learningDeductive learning is the traditional approach where you're provided information, examples to reinforce it and are quizzed on it later. Inductive learning is where a learner is provided with examples and then they're asked what they can infer from it, really tapping into the critical thinking element. This taps into their autonomy, mastery, and relatedness.Research supports that using traditional pen and paper workbooks while learning helps commit the information to memory and behavior.  Workbooks provide an opportunity for exploration while reinforcing learning concepts and ideas. They help leverage the mastery/competence and autonomy factors.We should shift our mindset from checking if employees are completing the training just to check a box to whether they're demonstrating the results of the training. This will tell us more about whether an employee is a good fit, whether the training is effective, and if adjustments need to be made.When creating a training on sensitive topis such as anti-harassment, language like “don't do this or this will happen” tends to feel accusatory and divisive but rather, find ways to create a sense of relatedness between the learner and the content. For example, asking “As a leader, how can you step in to create a culture that feels safe for your staff?” focuses more on building relationships and fostering a healthy company culture than the laws and regulations of harassment.To learn more about learning motivation, Austin recommends reading research on intrinsic motivation and self determination theory. Links from the podcastConnect with Austin WelchLearn more about Sage MediaRead Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-BeingLearning tools for increasing Learners' MotivationExplore The Learner Engagement Summit resources

On this episode of The Shape of Work podcast, our guest is Karthik Sridharan, Co-founder of Flexiple, Remote Tools, and The Remote Clan.Flexiple- an online curated freelancing platform aiming to empower both companies and freelancers.Remote Tools - fastest growing online remote working community that features top tech, remote-first, product tool stack used by actual remote teams and insightful reads on the Future of Work among many other exciting things. The Remote Clan - a community for remote workers to build a strong career with the help of those who are pursuing the same goals. Having more than seven years of  experience across investment banking and technology, Karthik joined JP Morgan straight out of engineering and slogged for three years in the Investment Banking industry.After having enough of the IB lifestyle, he joined IIM Ahmedabad for an MBA and started exploring his passion for entrepreneurship during this phase, which led to the start of Flexiple.With a background that extensive, Karthik has plenty of expertise to share in this conversation. It's no surprise this episode covers a lot of ground.We discuss with Karthik:How effective change management empowers employees and improves business performanceHow to hire and manage your first 10 employeesOnboarding tactics that help new hires successCommon mistakes when leading remote teamsWork friendships are key for team camaraderie, but how do you cultivate them remotely?Ways to embed continuous learning when working remotelyEPISODE HIGHLIGHTS:What is effective change management related to business performance?Like Flexiple, a big name in the B2B market, there are millions of start-ups striving consistently to provide value to companies and build trust. Starting as remote work, every start-up finds a unique way to hold on to the essence of working in remote teams, cultivating friendships, and depending on continuous learning to deliver a multitude of tasks.Two Things Defining the Structure of Your Start-upClarityHave a transparent thought process with the techniques, including bootstrapping and funding sources. It determines the chances of your start-up being better placed than struggling to shuffle across the wrong fit.For instance, Sridharan was quite clear to choose B2B space rather than B2C space as it did not suit his interests. But, on the other hand, the B2C area needs funding and an enduring vision to power its functionality.Kind of Start-upSecond, what kind of start-up do you want to build? Again, it will impact your move as deciding the structure also includes financing the resources well to all the teams. It dramatically affects business performance as a product of effective change management.Remote working is the core of today's start-ups.Staying upfront in the conversations of remote working was essential for Sridharan while starting with his first team. He believes every team member must understand the responsibility to work remotely. Also, it operates as a remote bank, similar to a two-way street, for everyone to deliver their best, right from the first level.Secondly, communication needs to be in place. For instance, the modern world's chat lingos may also find a functional space for your start-up to stay updated. Also, Sridharan quoted that most of the hiring in his start-up was based on referrals: shows the trust that grows in a start-up, morally! Then comes the idea of documentation so that every person in the company finds the right solution at the right time.Follow Karthik on LinkedIn

Join us for a new episode of Learning While Working as Robin chats with John Danner from Dunce Capital – a company focused on investing in the future of learning and work. In this episode, John shares his insights as to why tech companies need to be focused on developing their own talent pipeline as opposed to continuing to bid from a dwindling supply of senior engineers.About John Danner:In the 90's John co-founded Net Gravity, which was one of the first online survey companies. He then sold it and pursued a Master of Education to become a high school teacher. Then, in 2006 John co-founded Rocketship Education, a not-for-profit charter school network focused on providing equal learning opportunities to low-income and minority students. He now runs Dunce Capital, where the focus is on investing in the future of learning at work. Through his varied professional experience, he's gained a deep expertise that crosses over technology, learning, and business.What should a talent pipeline for a tech company look like?Ten years ago, there weren't nearly as many tech companies with a need for senior engineers and the more prominent companies like Apple and Netflix were able to pay the salaries to scoop up the available ones for hire. But now, we live in a time where the demand for senior engineers is higher than ever before, but there isn't a pool of candidates big enough to fill the need.We'll see companies bring in young engineers, and then either internally or through external partnerships, train those engineers for the first couple of years so that they're not a liability. So that would be my prediction about what's going to happen in the tech industry over the next few years, and I think it'll be a big advantage  – John DannerKey takeawaysThe demand for senior engineers has far surpassed the available demand meaning that the future of hiring and training of engineers will need to change.Tech companies are going to advantage themselves by figuring out how to bring in much younger engineers and train them in their own culture and how to be an engineer.When companies invest in developing their employees and create clear career paths for them to work toward, they're likely to get better retention.It can be a challenge for both small and large companies to train from within - each size company has its own set of problems.“An earlier stage startup doesn't have the capacity to do great training because the number of senior folks they have that would be capable of mentorship is just not strong enough yet. And you have the more mature companies, which until today have just been able to use the market to get the scarce resources that they need” – John DannerIn neither case are companies really focusing on how to develop people from within.“A lot of the companies, I think look at it as somebody else's problem still, and they wish that they could just find people that were ready to hit the ground running, and I think that's been true up to maybe five to 10 years ago in tech, but it's fairly clearly not true anymore. There is not a large enough supply of hit the ground ready folks anymore.” – John DannerThe focus should also be put on bringing diversity into tech so that there can be a representative group of people that mirrors the population. Companies can't wait for the elite schools to become broadly representative and deliver them with diverse grads. And that's why some of these post-grad accelerated Computer Science programs are so important; they help promote the diversity that elite schools and companies aren't yet focusing on.The sooner companies get onboard with internal training and development programs, the better positioned they'll be. The time of bidding up senior engineers is over.Segment time stamps(00:16) Introduction to John Danner(1:51) What should a talent pipeline for a tech company look like?(6:37) Investing in employee development as a means of retention(8:13) Can smaller companies compete with the professional development larger companies can provide?(10:41) Achieving the proper ratio of junior to senior employees(12:07) Focusing on building diversity in tech(13:53) Should accelerated tech schools have a role in helping people once they start in an organisation?(16:24) John's advice for developing a talent pipelineLinks from the podcastConnect with John DannerLearning more about Dunce CapitalFollow John Danner on MediumRead Johh's post on Tech needs to stop whining about talent

The remote learning virtual conference brings together guests from the Learning While Working podcast series on virtual facilitation. It's four half-day sessions over 3 days from November 17th 2020 (Australian time zones). One of the sessions is designed for the European/UK time zone.The event is a mixture of group sessions and small breakout sessions with your peers where you will be exploring the issues and possibilities of live remote learning. If you're listening to this after November 18th, 2020 you can now buy the recordings from the event.Sign up here 

Great live virtual learning sessions happen with a combination of facilitation skills, learning design and visual design. L&D professionals often struggle with visual design. In this podcast, Sprout Labs visual design lead Iona Dierich, talks about the importance of visual design in online facilitation.  Iona has a unique set of skills, as well being a visual designer and an occasional instructional designer, she has a background in teaching design. She now runs Sprout Labs visual design for our learning lab.  In our programs on online virtual facilitation and design skills, Iona’s sessions on visual design are often what people get the most excited about. In this podcast Iona talks about a simple, practical idea on how to improve your visual design.   Links from the podcastConnect with Iona on LinkedIn and on Instagram  Iona’s Thinking Visually - presentation slides from 2019 Learning While Working virtual conferenceSprout Labs Visual design for learning lab that Iona runs

On this episode of Pints & Pizza with Professors, professors Jason Mollica and Megan Wagner chat about the WORST jobs they've ever had yet how they were able to use those skills learned to their advantage later in their careers. They also discuss the evolution of careers and why you should always keep an open mind when new opportunities arise. In the episode you’ll hear: - Why NOT getting your dream job could be the best thing for your career - Why crappy jobs can show you the best learning lessons - How students can start building businesses and growing their cash flow NOW If you enjoyed this episode and it inspired you in some way, we’d love to hear about it and get your biggest takeaway. Take a screenshot of you listening on your device, post it to your Instagram Stories, tweet or Snap and tag us, @pintspizzaprofs! Submit Your Question (Audio or Video Clip) to pintspizzaprofs@gmail.com LINKS: Where to find Pints & Pizza With Professors: Website: http://www.pintspizzaprofs.com Facebook: https://www.facebook.com/pintspizzaprofs Instagram: @pintspizzaprofs Twitter: @pintspizzaprofs Snapchat: @pintspizzaprofs Where to find Jason Mollica: Twitter: @JasMollica Instagram: @JasMollica Where to find Megan Wagner: Instagram: @MeganMWagner Twitter: @MeganMWagner Website: http://www.meganmwagner.com

In this episode Jo talks with Robin Petterd from Spoutlabs….. What is the learning while working conference The trials of running a conference live online Interesting points for facilitators and attendees https://learningconference.info https://www.linkedin.com/in/robin-petterd-b593b41/   Lightbulbmoment.online Lightbulbmoment.info Lightbulbmoment.community   @MomentLightbulb @LightbulbJo @MikeLightbulb

In this podcast Robin talks with Yishan Chan about the idea of personal talent stacks and how to develop your own talent stack. Often on the Learning While Working podcast we focus on designing learning and an organisational viewpoint on learning. This conversation with Yishan is a switch to focusing on how individuals learn. Yishan has a great podcast called Digital Learner where she talks with people about making career shifts and learning at work. Some of the topics we talk about include learning from peers, podcasting and side projects as a way of learning. **Useful links from the podcast ** Connect with Yishan Chan on LinkedIn Find out more building your talent stack Listen to Yishan’s Digital Learner podcast

Robin Petterd is the founder of Sprout Labs, and he’s on a mission to change how people learn at work. Robin’s belief is that learning at work needs to reflect the natural way we learn; it needs to restore our curiosity; and it needs to support our desire to learn with others. In this interview with Robin, we dive into his learning while working framework, and how to optimise the way you self-direct your learning to add new skills to your talent stack. I was also curious to find out Robin’s perspective on how to prioritise what you learn, and optimise how you learn in order to land your next career opportunity. You can find out more about the Learning While Working framework on Robin’s website below. I hope it inspires you to think differently about how you optimise your self-directed learning. Learning While Working Manifesto ☆ Build Your Talent Stack ☆

Paul Smith has taken on the role of Head of Training for Baker Construction Enterprises, the nation’s largest concrete construction company. Not surprisingly they have him working on developing Structured On-the-Job Training in keeping with his “Learning While Working” book. As leader of the training department Paul and his team have more than just SOJT […] The post Learning Insights Radio: Paul Smith with Baker Construction Enterprises appeared first on Business RadioX ®.

This podcast is the start of a series that was recorded at iDesignX 2019. They are shorter than most of the other Learning While Working podcasts. There is a bit of background noise from the conference venue. The focus of this series is on learning design. There are lots of great conversations coming up, with people you might not have heard about before. In this podcast, I’m talking to Nicole White from the ID Crowd and Rebecca Carter from CSIRO about a project in which they are using voice based digital storytelling to increase understanding of Aboriginal and Torres Strait Culture Awareness at CSIRO. The learning experience they are talking about is not a linear eLeaning, it’s an explorative interface. This podcast is a great summary of their journey to build a really innovative project. Towards the end of the podcast, Nicole talks about one of the most powerful questions they ask to trigger different approaches to eLearning ‘What would this project be like if it wasn't was eLearning’. **Useful links ** IDesignX The ID Crowd Find out more about Nicole White Find out more about Rebecca Carter

Emma Weber is an expert in learning transfer. This is actually the second great conversation with Emma on the Learning While Working podcast; the first conversation focused on the 70:20:10 learning model and learning transfer. This interview starts with Emma giving an overview of her approach to learning transfer. One of the key features of her approach is what she calls ‘learning breaks’, which are coaching conversations that focus on personal accountability for making changes and reflection. In the interview, Emma talks about how she struggled to find the right technology to support her approach to learning transfer. She is now using two platforms that work together: an action planning tool called Turning Learning into Action and a chatbot built with the Mobile Coach platform. The Turning Learning into Action platform is free. What she achieved is a great example of using digital technologies to automate the learning process. It might be not a perfect replacement for a personal learning transfer coach, but it is scaled and affordable. To go along with the podcast series we have released an eBook with all transcripts of the interviews. To go along with the podcast series on How artificial intelligence is changing the way L&D is working, we have released an eBook with all transcripts of the interviews. The eBook also gives a brief explanation of what AI is and an overview of how it is being used in L&D. Download the eBook Useful links Find out more about Emma Find out more about Lever – transfer of learning Find out more about Coach M – the learning transfer chatbot Start using the free Turn Learning into Action tool Find out more about learning transfer

Ben Betts from HT2 Labs is back on the podcast in this interview. Ben is passionate about using social learning to build high-impact learning experiences. HT2 Labs are also the people behind Learning Locker, which is an open source learning record store for xAPI data. At the Learning While Working conference, Ben talked about the work that HT2 Labs have been doing on how they are measuring social learning. The recording of that conference session goes into more depth on that work than this podcast does, so if you’re interested in what Ben is doing I encourage you to watch that recording. The work HT2 Labs is doing is built around a series of machine learning methods that are called ‘natural language processing’, which I think of as a series of methods that look for patterns in language. It’s maybe the most complex area of machine learning. The podcast starts by exploring data, AI, and automation in L&D, then moves into using natural language processing and measuring social learning data. To go along with the podcast series we have released an eBook with all transcripts of the interviews. To go along with the podcast series on How artificial intelligence is changing the way L&D is working, we have released an eBook with all transcripts of the interviews. The eBook also gives a brief explanation of what AI is and an overview of how it is being used in L&D. Download the eBook Useful links Find out more about Ben Betts Find out more about Learning Locker and Curatr Learning Experience Platform

You learn a lot in a room by yourself. We welcome your reviews and comments email: chimein@theconversationtheory.com Don't forget to SUBSCRIBE!!! Rate!!! And Review!!! You can follow the Podcast and Mia on Twitter or Instagram at: https://twitter.com/TheConvoTheory https://twitter.com/TheTheoryofMia https://www.instagram.com/theconversationtheory/ https://www.instagram.com/thetheoryofmia/ Don't forget the blog "After Thoughts" on our website at http://theconversationtheory.com/afterthoughts/

Patti Shank is a leader in evidence-based learning. We're excited about the release of her book Practice and feedback for deeper learning, and Patti is our guest on this episode of the Learning While Working podcast where she and Robin discuss the need for more research in L&D.

Learning transfer professional Emma Weber is our guest on this episode of the Learning While Working podcast. Emma talks about the need to focus on the whole of the 70:20:10 model, and why the '10' is too often overlooked.

Dr Melissa Bordogna returns to the Learning While Working podcast to discuss social learning and collaboration in the workplace. It's also worth listening to our previous discussion with Melissa on The Future of Work.

What is social learning, and what new opportunities can be opened up when social learning is introduced to the workplace? On the Learning While Working podcast, Ben Betts from HT2 Labs dives into social learning and how it can be used with data analysis for more valuable learning outcomes.

Hamish Dewe from Orion Health joins the Learning While Working podcast to outline some of the practical applications of xAPI and Totara in a company with a global reach.

Ben McEwing from Carben returns to the Learning While Working podcast and talks with host Robin Petterd about the emerging role of VR as a storytelling and learning tool.

A brief introduction of the Learning While Working podcast.