Collaborative Learning Enhancements

🤔 How might you infuse more experiential elements into even the most standard Q&A session? This was my question to myself when wrapping up a facilitation course for a client that included a Q&A session. I wanted to be sure it complemented the other experiential sessions and was aligned with the positive adjectives of how participants had already described the course. First and foremost - here is my issue with Q&As: 👎 They are only focused on knowledge transfer, but not not memory retention (the brain does not absorb like a sponge, it catches what it experiences!) 👎 They tend to favor extroverts willing to ask their questions out loud 👎 Only a small handful of people get their questions answered and they may not be relevant for everyone who attends So, here is how I used elements from my typical #experiencedesign process to make even a one-directional Q&A more interactive and engaging: 1️⃣ ENGAGE FROM THE GET-GO How we start a meeting sets the tone, so I always want to engage everyone on arrival. I opted for music and a connecting question in the chat connected to why we were there - facilitation! 2️⃣ CONNECTION BEFORE CONTENT Yes, people were there to have their questions answered, but I wanted to bring in their own life experience having applied their new found facilitation skills into practice. We kicked off with breakout rooms in small groups to share their own experiences- what had worked well and what was still challenging. This helped drive the questions afterwards. 3️⃣ MAKE THE ENGAGEMENT EXPLICIT Even if it was a Q&A, I wanted to be clear about how THIS one would be run. I set up some guidelines and also gave everyone time to individually think and reflect what questions they wanted to ask. We took time with music playing for the chat to fill up. 4️⃣ COLLABORATIVE LEARNING IS MOST IMPACTFUL Yes, they were hoping to get my insights and answers, however I never want to discredit the wisdom and lived experience in the room. As we walked through the questions, I invited others to also share their top tips and answers. Peer to peer learning is so rich in this way! 5️⃣ CLOSING WITH ACTIONS AND NEVER QUESTIONS The worst way to end any meeting? "Are there any more questions?" Yes, even in a Q & A! Once all questions were answered, I wanted to land the journey by asking everyone to reflect on what new insights or ideas emerged for them from the session and especially what they will act upon and apply forward in their work. Ending with actions helps to close one learning cycle and drive forward future experiences when they put it to the test! The session received great reviews and it got me thinking - we could really apply these principles to most informational sessions that tend to put content before connection (and miss the mark). 🤔 What do you think? Would you take this approach to a Q&A? Let me know in the comments below👇 #ExperienceLearningwithRomy

COIL (collaborative online international learning) is often promoted as a scalable, inclusive way to internationalise higher education. However, this study shows it’s not that simple: #interculturallearning in #COIL is not automatic. It depends on how COIL is designed, facilitated, assessed, and supported. In short: good intentions don’t create intercultural learning - design does. Research papers can be hard to interpret or apply. This post breaks down the study’s findings and explains why they matter for different audiences 👇 MANAGEMENT & LEADERSHIP: COIL success is shaped by institutional choices, not just enthusiastic educators. Misalignment in assessment, timetabling, and accountability can undermine collaboration, engagement, and learning. This research: ◾ Makes the case for strategic coordination across partner institutions ◾ Clarifies where investment (support, training, alignment) is needed to reduce risk and boost impact ◾ Strengthens the link between COIL, student experience, and graduate attributes POLICY ADVISORS: COIL can advance internationalisation-at-home and equity goals - but only when quality and learning design are prioritised. It offers policymakers a basis for: ◾ Moving beyond counting COIL initiatives toward measurable outcomes - stop asking “How many COIL projects?” and start asking “Are they designed to support intercultural learning?” ◾ Embedding design, assessment, and facilitation criteria into evaluation frameworks ◾ Supporting COIL as a credible, high-impact educational method not just a replacement for physical mobility EDUCATORS, INSTRUCTORS & DESIGNERS: Intercultural outcomes are linked to how groups are formed, collaboration is assessed, and learning is facilitated. It offers practical insights for: ◾ Designing intentional group composition rather than random allocation ◾ Aligning assessment with collaborative learning activities and intercultural goals ◾ Creating environments that support engagement, accountability, and cultural intelligence RESEARCHERS: This paper contributes methodologically and conceptually. The study: ◾ Using a multi-level mixed-methods approach, examines individual, group, and within-group dynamics - still underused in COIL research. ◾Moves beyond descriptive accounts to examine how and when intercultural learning unfolds ◾ Integrates personality, attitudes, group composition, and course design in one framework ◾ Shows outcomes depend on design and context, not participation alone Hackett, S., Janssen, J., & van Tartwijk, J. (2025). The significance of personality traits, collaborative attitudes, and group composition during collaborative online international learning (COIL): a mixed methods study. Journal of Computing in Higher Education https://lnkd.in/eSbsMsgW De Haagse Hogeschool / The Hague University of Applied Sciences Centre of Expertise Global & Inclusive Learning #HigherEducationPolicy #EducationalLeadership #LearningDesign #VirtualExchange #HigherEd

In our rush to regulate AI use in schools, we're missing something profound: AI is fundamentally changing how students learn together. This shift isn't about technology – it's about what happens when students collectively make sense of AI-generated information. What I'm seeing in classrooms everywhere is fascinating: students aren't just sharing answers anymore; they're engaging in what I call "collective sense-making." Here's a game-changing insight: when students work together with AI, they naturally engage in five powerful learning behaviors: 1. Challenge collective assumptions - they question not just the AI, but each other's interpretations 2. Build on diverse experiences - each student brings unique insights to AI-generated content 3. Create shared understanding - they construct meaning together, not just individually 4. Develop collaborative critique - they learn to evaluate AI outputs as a team 5. Generate group insights - they produce knowledge that surpasses individual understanding The transformation is striking. Instead of "divide and conquer" group work, students are engaging in true collaborative knowledge building. Here's what effective collective sense-making looks like: Question Together Start with AI responses Generate shared questions Build collective understanding Connect and Expand Link to diverse experiences Find unexpected patterns Create new frameworks Transform and Create Generate new perspectives Produce original content Build shared knowledge This approach has completely changed how students interact with both AI and each other. Instead of competing, they're collaborating. Instead of dividing work, they're multiplying insights. Important note: These patterns emerge across grade levels, subjects, and student populations! The key is shifting from individual AI use to collective meaning-making. How are you seeing student collaboration change with AI? What unexpected forms of group learning are emerging in your classroom? Let's explore this transformation together. #PragmaticAISolutions #AIinEducation #CollaborativeLearning #EdTech #FutureofEducation #StudentEngagement

Collaborative AI Agents: A New Frontier in Human Learning and Information Discovery Exciting new research from Stanford and Yale introduces an innovative approach to AI-assisted learning that could transform how we tackle complex information-seeking tasks. Stanford: Introducing Co-STORM: Collaborative AI for Exploring the Unknown ... A team of researchers led by Yucheng Jiang and Yijia Shao at Stanford University have developed Co-STORM, a system that enables humans to participate in and learn from conversations between multiple AI agents. Their paper, "Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations," presents a novel way to help people discover information they didn't even know they were missing. 👉 What is Collaborative Storm Imagine you're trying to learn about a complex topic, but you don't even know what questions to ask. It's like being in a dark room, not knowing where the light switch is. Co-STORM is like having a group of friendly experts come into that room with you. They start talking about the topic, asking each other questions, and shining flashlights around. As they talk, you start to see more of the room and understand what's in it. 👉 Here's how it works: 1. Multiple AI Experts: Co-STORM creates several AI "experts" with different perspectives on your topic. It's like having a biologist, a chemist, and a physicist all discussing a scientific question. 2. Conversation Simulation: These AI experts have a conversation about your topic. They ask each other questions, provide answers, and explore different aspects of the subject. It's like listening to a roundtable discussion among knowledgeable people. 3. User Participation: You're not just watching - you can jump in anytime with your own questions or thoughts. It's like being part of the discussion, not just an observer. 4. Dynamic Mind Map: As the conversation progresses, Co-STORM creates a visual map of the ideas being discussed. Imagine a tree growing new branches as new topics come up. This helps you keep track of what's been covered. 5. Moderator AI: There's also an AI "moderator" that helps steer the conversation in interesting directions. It's like having a skilled teacher who knows how to ask thought-provoking questions. 6. Internet-Grounded Information: The AI experts don't just make things up - they use information from internet searches to back up what they're saying. It's like having a library at their fingertips. 7. Final Report: After the conversation, Co-STORM can generate a detailed report summarizing everything that was discussed, with references. It's like getting a well-organized set of notes after a great class. The big idea is that by listening to (and participating in) this simulated expert conversation, you learn about aspects of the topic you might never have thought to ask about. It helps you discover your "unknown unknowns" - the things you didn't even know you didn't know!

How many edtech pitches have we seen say exactly the same thing. "Your personal AI tutor, available 24/7." Personalized learning paths. Individual mastery. One student, one screen, optimizing alone. But for many cultures, meaning-making happens through the group, not alone. Zaretta Hammond's Culturally Responsive Teaching and the Brain (https://lnkd.in/evrmkM8J) was a game changer for me in understanding this tension in our current systems. African American, Latino, Pacific Islander, Native American, and Asian communities often lean toward communalism where understanding emerges through collective dialogue and cooperative learning. Here's the problem: An 8th grader debugging code alone with AI learns differently than four students reasoning through it together, negotiating what's broken, building shared understanding through talk. Hammond calls this productive struggle in community. The social interaction IS the cognitive scaffold. But our AI tools aren't built for this. They're designed for individual users who happen to sit near each other. Even when a group shares one device, they're taking turns being solo learners. What would AI for communal learning actually look like? I don't fully know. But it would: - Respond to a group's collective reasoning, not individual gaps - Make the group's emerging consensus visible - Strengthen interdependence, not independence - Honor that knowledge is constructed together The risk: We invest billions making learning more and more isolated. The question: Can we build AI that serves collaboration and learning in community?

Two models to foster collaborative learning in your organization. 👇 I'm reflecting on the session I chaired at LT24, and going back to my notes. Shout-out to Lynn Rodgers and Kinga Petrovai, PhD for bringing two concrete, and practical formats we can steal and implement right away. 1️⃣ Lynn shared their "Team rhythm of weekly 20-minute conversations" 🧠 Principle: Small drops of learning within each team. How does it work? 👉 Weekly 20-minutes, team-based and peer-led conversations 👉 Each team has a designated host, pre-selected based on a set of criteria 👉 People Leaders are not included in these conversations 👉 L&D curates a list of topics centrally, and supports these conversations with nudges and resournces which the teams can explore together 👉 Constant cycles of exploration + experiments + reflection: —Week 1 starts with the exploration of a topic. —Teams are encouraged to "get curious", identify small improvement opportunities and commit to one concrete action (or experiemnt) they will apply in the coming week. —The aim of these actions is to improve how they work, or the world they operate in. —Week 2 invites to reflect on those experiements, what worked and what didn't, what stood in the way of the change, how can they keep it alive. —The cycle repeats: explore + experiment + reflect 🧚♂️ Key ingredient: The hosts are supported by central L&D and through their own community in MS Teams Channel, as well as specific events for hosts. They are testing new conversations, suggest topics, and protect the principles these conversations are based on. 2️⃣ Kinga shared her new "Learning Hives" Model 🧠 Principle: The Hive is the thread to collect and amplify the many existing resources within an organisation. How does it work? 👉 A group of ~10 individuals with same learning goals come together to learn from each other 👉 The sessions are integrated into the workflow, online or offline 👉 Each Hive has clear learning objectives 👉 Sessions are designed and run by a "Knowledgeble Host" The Hives function based on 6 key elements: - Leadership protects the time and space for the Hives to meet regularly - Hives have clear learning objectives aligned with organisational needs - The Hosts uses strategic questions designed to anchor the conversation and move the group towards the objectives - The Host synthesises learning and takeaways to be incorporated in the flow of work - The Host provides nudges between the sessions to reinforce learning and incorporate in the work - Deeper focus as each session builds on the previous one, and move the Hives closer to their learning objectives 🧚♂️ Key ingredient: The Knowledgeable Host gets to know the Hive members, weaves all voices into conversation, encourages the flow of learning. They are a trained facilitator, not a peer or a team member. 🎤 Over to you: What other collaborative learning formats have you experimented with? #learninganddevelopment #collaborativelearning

📖 Reading doesn’t have to be a silent, individual task. What if your students could teach each other while reading? Discover the Jigsaw Reading Method and other powerful strategies to make reading interactive and meaningful. Unlock Reading Skills with the Jigsaw Method, Students become “experts” on text parts, then share to build the full story. 2. Step 1 Break the text into smaller, manageable sections. 3. Step 2 Form expert groups—each group dives deep into one section. 4. Step 3 Reassign into mixed groups where students teach one another. 5. Step 4 Reconstruct the narrative together—everyone sees the bigger picture. 6. Helpful Supports ✔ Annotated passages ✔ Graphic organizers ✔ Guided prompts 7. Other Effective Reading Strategies ✨ Reciprocal Teaching – students take roles (summarizer, questioner, clarifier, predictor). ✨ Think–Pair–Share – quick reflection, peer discussion, then class sharing. ✨ Close Reading – multiple focused readings for deeper meaning. ✨ SQ3R Method – Survey, Question, Read, Recite, Review for structured comprehension. ✨ Reader’s Theater – dramatizing texts to build fluency and engagement. 8. Enhance the Experience 🔹 Use digital breakout rooms 🔹 Add visuals & timelines 🔹 Encourage peer questioning 🔹 End with a reflection or short writing task. Students don’t just read. They analyze, collaborate, and own the learning process. How do you make reading more interactive and collaborative in your classroom? #TeachingStrategies #ActiveLearning #ReadingComprehension #EnglishTeaching #EdTech #CollaborativeLearning #TeachingTips #StudentEngagement #LearningStrategies #OnlineTeaching

Collaborative learning in immersive virtual reality (IVR) is gaining traction, but how much does it really impact learning? A recent Stanford-led study explored this by comparing different levels of interaction in a virtual ocean education experience. The results offer clear insights into when and how collaboration in IVR truly enhances learning—and when it might actually get in the way. Major Takeaways 1. Active Collaboration Boosts Learning -Learners who built virtual reef models together outperformed those who only watched or discussed the content. 2. Watching Alone Isn’t Enough - Passive or discussion-only formats didn’t match the learning gains of hands-on collaboration. 3. Emotions and Social Bonds Can Hinder Learning -Feeling overly active, ashamed, or strongly bonded to the group negatively impacted learning. 4. No Boost in Self-Efficacy or Presence -Increased interactivity didn’t lead to higher self-belief or immersion. 5. Social Interaction May Distract from Content -Group dynamics can shift focus away from learning objectives. Instructional Design Implications 1. Use Authentic, Collaborative Tasks - Prioritize group projects that require joint problem-solving. 2. Manage Cognitive Load -Avoid overwhelming learners—train and scaffold VR use. 3. Limit Emphasis on Group Bonding -Focus on collaboration quality, not just team cohesion. 4. Support Emotional Readiness -Prep learners for IVR to reduce shame or overwhelm. 5. Leverage IVR for Unique Experiences -Use it to simulate otherwise impossible or expensive tasks.

Over time, my approach to teaching graduate classes has shifted towards creating an environment where students act more like a group of consultants tackling real-world, data-driven problems. Instead of simply following theoretical frameworks, students now dive into real-life datasets, analyze trends, and craft creative solutions. This hands-on method encourages them to think critically and out of the box—steering away from the temptation of copy-pasting from AI tools like ChatGPT. The focus isn’t just on solving problems; it’s about viewing challenges from different perspectives. By engaging with diverse datasets, students learn to approach problems with fresh eyes, ensuring a deeper retention of knowledge. It also makes the learning process more interactive and fun! This week, we focused on conducting data-driven SWOT analyses. Students worked in teams, using multiple datasets to identify strengths, weaknesses, opportunities, and threats. Along the way, they developed their soft skills, learned the value of collaboration, and strengthened their ability to work effectively in groups. This approach not only prepares students for real-world consulting roles but also equips them with the skills to think critically, collaborate, and adapt to a rapidly evolving business landscape. #DataDrivenLearning #ConsultingSkills #RealWorldProblems #GraduateEducation #CriticalThinking #OutOfTheBox #SWOTAnalysis #SoftSkillsDevelopment #CollaborativeLearning #FunInTheClassroom #BusinessEducation #InnovationInTeaching #HigherEd

During Learning Labs with educators and scholars in @natomasusd we focused on critical “inquiry moves” that deepen understanding and learning and allow us all to lead, learn and have an inquiry mindset. Collaboration is a huge part of what makes inquiry different, what allows for deeper learning and builds positive relationships and nurtures healthy cultures of learning. 3️⃣ things to remember about collaboration… 1. Get your learners collaborating and sharing thinking at the start of the lesson. A great practice to tune into ideas being shared aloud and to create space that immediately centers your learners 2. Layer collaborative structures. Try a Turn & Talk, a GOGO (Give One, Get One) or opportunity for movement in sharing and a whole group share out that allows for synthesize & reflection 3. Consider your role in collaboration. Partnering up with less confident learners, moving about the space to hear discourse and notice what big ideas and misconceptions emerge and document what’s unfolding (photos, video, notes, etc.) Huge shoutout to Trevor MacKenzie, Mary Rimby and Kristen Martin for making these days so impactful for all learners 💕