Collaborative Learning Activities That Enhance Critical Thinking

AI was trained on dominant narratives. That makes it the perfect tool for flipping them. Welcome to: 🧠 Day 6: Activist Engagement with Knowledge aka: the ability to use what you learn to challenge existing systems, surface inequity, and act on what needs to change. This isn’t “critical thinking as critique.” It’s knowledge as leverage —a willingness to wrestle with injustice, and the skill to revise the script that’s been handed down. Most classrooms stop at awareness. They ask for reflection, not redesign. They critique power, but don’t practice rewriting its rules. That’s where AI becomes subversive. Used well, AI can simulate the dominant narrative, expose its inherent assumptions, and build scaffolding for constructing alternatives. Here are 3 AI-powered activities that transform passive critique into activist redesign: › 🚨 Rewrite the Record Start with a known injustice (e.g. school discipline disparities, algorithmic bias in hiring). ⤷ Students prompt AI to generate how that issue is typically framed by those in power. ⤷ Then they ask AI to simulate the same issue from multiple marginalized perspectives—documenting shifts in framing, priority, and language. ⤷ Final phase: students use AI to help them compose a new policy, framework, or public narrative that could be implemented, challenged, and iterated. _____ › 📊 Data Doubt Engine Students choose a common data claim (e.g. “Crime is rising in urban areas”). ⤷ Ask AI: What data supports this? Who collects it? What’s missing? ⤷ Then students prompt AI to help generate counterfactual scenarios: What would the data look like if we measured community trust? If we disaggregated by neighborhood? ⤷ Students build a parallel dashboard or model—and then refine it across iterations to visualize what’s been erased. _____ › 🧬 System Swap Lab Students select a complex system (e.g. standardized testing, housing policy, scientific peer review). ⤷ They use AI to map its historical origins, intended function, and who benefits. ⤷ Then prompt AI to help them redesign the system with a different foundational logic (e.g. equity-first, anti-racist, community-controlled). ⤷ Students critique their own version using stakeholder simulations generated by AI—forcing them to defend, refine, or rebuild. _____ Activist thinking doesn’t end at critique. It lives in the messy, iterative work of building what’s better. When used wisely, AI doesn't need to be a reflection of the biases we've collected. It can be a thought and prototype partner for the futures that are waiting to be authored. Which of these would move your students from resistance to reimagining? 🛠️

"AI will isolate learners!" critics warn. Yesterday, I witnessed exactly the opposite - a moment that revealed how AI can catalyze rich collaborative thinking when thoughtfully orchestrated. My students were tackling Chapter 8 of "Machines Like Me" - McEwan's most ethically complex chapter. But here's the magic: AI wasn't the endgame - it was just act one. We strategically placed strong critical AI users across different groups, and what unfolded was fascinating. The AI helped stage the initial philosophical debate, identifying potential ethical frameworks for each character. But the real intellectual fireworks happened next. In their groups, students began challenging these AI-generated frameworks, with our stronger critical thinkers guiding their peers through increasingly sophisticated questions: "But if Charlie is really a utilitarian, how do we explain his decision about X?" "What happens when Miranda's supposed virtue ethics crashes into Adam's rigid deontology?" "Are we sure the AI's reading of their ethical positions holds up against these later scenes?" What I observed wasn't just AI analysis - it was students teaching students how to think more rigorously, using AI as a springboard for deeper collaborative inquiry. The technology wasn't replacing discussion; it was enriching it by giving students a common starting point to push against and refine. Here's what's becoming clear: When we thoughtfully orchestrate AI use, positioning it as the beginning rather than the end of analysis, and strategically leverage peer dynamics, something profound happens. Students don't just accept AI insights - they collectively build beyond them. The future of classroom discussion isn't about getting AI answers. It's about using AI to stage richer debates, then letting students collaboratively discover the limits and complexities those initial AI insights missed. Educators: How are you orchestrating AI use to spark, rather than replace, peer learning? #AIinEducation #CollaborativeLearning #EdTech #Teaching #GenerativeThinking Dr. Sabba Quidwai Mike Kentz Amanda Bickerstaff Ethan Mollick Rob Nelson Jason Gulya Doan Winkel Nick Burnett Dr. Martha Umana Ryan Findley Daniel Bashir Alan Hilsabeck Chrissy Macso, M.Ed Anna Mills

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