How to Improve Teaching With AI

A look at how CS50 has incorporated artificial intelligence (AI), including its new-and-improved rubber duck debugger, and how it has impacted the course already. 🦆 https://lnkd.in/eb-8SAiw In Summer 2023, we developed and integrated a suite of AI-based software tools into CS50 at Harvard University. These tools were initially available to approximately 70 summer students, then to thousands of students online, and finally to several hundred on campus during Fall 2023. Per the course's own policy, we encouraged students to use these course-specific tools and limited the use of commercial AI software such as ChatGPT, GitHub Copilot, and the new Bing. Our goal was to approximate a 1:1 teacher-to-student ratio through software, thereby equipping students with a pedagogically-minded subject-matter expert by their side at all times, designed to guide students toward solutions rather than offer them outright. The tools were received positively by students, who noted that they felt like they had "a personal tutor." Our findings suggest that integrating AI thoughtfully into educational settings enhances the learning experience by providing continuous, customized support and enabling human educators to address more complex pedagogical issues. In this paper, we detail how AI tools have augmented teaching and learning in CS50, specifically in explaining code snippets, improving code style, and accurately responding to curricular and administrative queries on the course's discussion forum. Additionally, we present our methodological approach, implementation details, and guidance for those considering using these tools or AI generally in education. Paper at https://lnkd.in/eZF4JeiG. Slides at https://lnkd.in/eDunMSyx. #education #community #ai #duck

Is AI helping students think better—or replacing their thinking altogether? As a professor of International Marketing at Berkeley, I’ve embraced AI in my classes with clear rules around its use. Students need to identify when they use AI in assignments. As a marketer, I believe embracing new apps and platforms is part of the job description, but it’s equally important to use them judiciously. The most important goal is for students to learn the benefits and limitations of AI. If my job is to teach them how to think, they need to understand the thinking they must do on their own and how to supplement, not replace, it. So, in the first assignments, I ask them to answer one question three ways: first on their own, then with the help of AI, and finally by integrating both. I also ask them to reflect on what they learn. It's fascinating to see how the students’ AI-generated responses differ, highlighting the importance of effectively framing their prompts. But the most revealing part is their reflections. They quickly see how AI can support their inquiry and where it falls short; they learn to value their unique perspective and voice. My Berkeley colleagues have also found my approach helpful, and together, we’re all learning how to embrace and manage the tools at our disposal. By integrating AI into the classroom in a deliberate way, I’ve discovered a process that fosters experimentation, critical thinking, and self-awareness—skills that will serve students well in their academic lives, future careers, and beyond. What are your thoughts on integrating AI into education? Have you seen any examples that stood out to you? Let me know in the comments.

“AI is killing critical thinking." That’s the debate, right? That if students use AI, they’ll stop thinking for themselves? But there’s the flaw in that narrative—critical thinking isn’t about avoidance. If we keep positioning AI as a threat to thinking, we miss the bigger opportunity: to design learning experiences where students wrestle with ideas, troubleshoot problems, and refine their reasoning. The narrative is in your hands. Students disengaged? AI might be the perfect addition to your toolbox. Not by handing them answers—but by making them earn them. Here’s how flipping the script on AI can re-engage students across subjects: ✅ Math– Instead of solving problems, AI generates incorrect solutions. Students become the detectives, diagnosing errors and justifying corrections. ✅ English/History– AI debates students with an opposing viewpoint on a book or historical event. Instead of summarizing, students sharpen arguments, analyze bias, and refine persuasion. ✅ Science– AI describes a fictional planet’s gravity and atmosphere. Students determine if humans could survive there, using real-world physics and biology to back up their claims. ✅ Art– Instead of generating art, AI critiques student work from the perspective of Van Gogh, a minimalist, or an AI itself. The result? Students engage in deeper reflection and artistic intent. ✅ Coding– AI presents buggy, inefficient code, and students have to debug it. Less memorization, more hands-on problem-solving. The best part? Privacy stays intact; AI isn't collecting student data, just giving them a challenge to wrestle with. We don’t need AI to think for students. We need to use it in ways that push them to think harder. AI isn’t the problem. It’s how we use it that matters. Let’s build the future of learning with that in mind. Who else is designing AI-powered learning experiences that keep students in the driver’s seat? Let’s swap ideas. #AIinEducation #EdTech #StudentEngagement

Here's a fascinating bit of history: the United States Military Academy at West Point has been using "AI" since the 1800s (although not the kind you may be thinking of).  "Additional Instruction" (AI) has been a cornerstone of cadet education, offering personalized 1:1 mentoring to those students struggling with complex subjects. Now, a forward-thinking West Point accounting professor has created "AI4AI" - ingeniously merging traditional Additional Instruction with modern artificial intelligence. 🔄Here's how AI4AI works: 1. Cadets must first consult an AI Tutor to explore their questions 2. They submit their AI conversation logs when requesting Additional Instruction from a professor 3. The professor analyzes the submitted AI dialogue before meeting the student 🌟 Why This Approach Is Innovative: This approach aligns perfectly with BoodleBox's three pillars of AI readiness: 1. Domain Expertise: - Students must actively wrestle with concepts using AI before getting Additional Instruction - This "productive struggle" builds deeper understanding 2. AI Enablement: - Students get hands-on experience learning when and how to use AI effectively - This develops critical AI enablement skills for future leaders 3. Human Excellence: - Student-professor interactions become laser-focused on advanced concepts, with AI handling foundational questions beforehand. - By reviewing the student’s AI interactions first, professors can focus their valuable time on what matters most: providing targeted mentorship, sharing deep insights, and building meaningful connections with students. 💡 Why AI4AI Resonates with Modern Education: - It keeps the “Professor in the Loop” ... AI is used as part of a collaboration not as a replacement - It maximizes instructor impact: the Professor can focus on deep engagement and transformative teaching moments - It creates a scalable model for personalized learning support: a professor can reach more students without sacrificing individual attention - It empowers student autonomy while reinforcing that they can and should reach out for guidance when needed 🚀 For Fellow AI in Education Innovators: This aligns well with the innovative approaches to responsible AI in education that we're seeing from over 10,000 faculty and students using BoodleBox: - It's a great example of teaching with AI (to create domain expertise) and teaching about AI (to develop AI enablement), while crucially maintaining the irreplaceable role of human educators - this isn't about AI replacing professors (teaching by AI), but rather empowering faculty to be even more effective and impactful while also being efficient. This innovative approach maintains West Point's tradition of educational excellence while readying cadets for an AI-powered future. It shows how historical teaching methods can be thoughtfully adapted with technology for the modern era. Totally Not Genuine AI Generated Photo Credit: Flux

Some thoughts on how we integrate AI into education: We first need to start by recognizing which skills are becoming more valuable and designing new ways to teach them. We all remember the effort it takes to write a paper—revising, structuring arguments, and refining our points. With AI, everyone will have a writing co-pilot to handle the mechanics, making the process more efficient. So, what if we redirected that effort into helping students develop higher-order skills like critical thinking, prompt design, and iterative analysis? A thought experiment: Imagine an assignment where students submit not just their essays but also the prompts they used to get AI-generated critiques. Their task wouldn’t be just to write and submit—it would be to argue, analyze, refine, and iterate. In less time than it takes to write a traditional paper, students could engage in deeper intellectual exercises—interrogating their own arguments, considering counterpoints, and strengthening their reasoning. For teachers, AI can streamline grading while amplifying feedback—providing broad insights that help shape targeted, meaningful commentary. This means students receive richer, more personalized guidance, making learning more interactive and impactful.

Today, I witnessed something extraordinary in my classroom that challenged everything we think we know about AI in education. Instead of handing students a rigid playbook of dos and don'ts with AI, I decided to flip the script entirely. Since summer, I've watched the endless parade of methodological frameworks and usage guidelines sweep through education. Each promising to be the "right way" to integrate AI into learning. But today, we tried something radically different. I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing. Students began mapping out research directions I'd never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns. Most importantly, they documented their journey, creating a meta-learning archive of their process. What struck me most was this: When we stopped fixating on the tangible "products" of AI interaction and instead centered on the mental maps being developed, something magical happened. Some might say this approach is too unstructured, too risky. But consider what we're gaining: 1. Metacognitive development: Students are thinking deeply about their own learning process 2. Agency and ownership: They're designing their own educational pathways 3. Critical navigation skills: Learning to chart courses through AI-enhanced knowledge spaces 4. Creative confidence: Freedom to experiment without fear of "wrong" approaches 5. Future-ready adaptability: Building skills to work with evolving AI systems We're not just teaching students to use AI – we're empowering them to design their own learning ecosystems. The focus isn't on what appears on the screen, but on the neural pathways being forged, the cognitive frameworks being built. Watching these students navigate this space, I'm reminded that the future of education isn't about controlling AI use – it's about nurturing the wisdom to use it well. We need to trust our students' capacity to be architects of their own learning journeys. The real breakthrough happens when we stop seeing AI as space to be contained and start seeing it as a landscape to be explored. Our role as educators isn't to build fences, but to help students develop their own compasses. #AIEducation #FutureOfLearning #EducationalInnovation #StudentAgency #EdTech #CognitiveDesign #GenerativeThinking Amanda Bickerstaff Stefan Bauschard Dr. Sabba Quidwai Mike Kentz David Gregg David H. Doan Winkel Jason Gulya Dr. Lance Cummings. Alfonso Mendoza Jr., M.Ed.

We need to rethink how we're talking about AI and education. I'm seeing a lot of this: "I use AI to generate feedback." "I use AI to generate lesson plans." "I use AI to generate Power Points." Or I'm seeing this: "I'd never outsource feedback to AI." "I'd never generate lesson plans with AI." "I'd never generate Power Points with AI." It's either/or. But there is another way. ⬇️⬇️ ------------------------ The problem: we tend to think of products as one-and-done tasks. So, we say things like "I created a lesson plan." But that's not how it works. To create a lesson plan, I go through a whole list of tasks! Instead of asking myself "Can I use AI to make a lesson plan?" I can ask "Can I use AI to improve some of the tasks I go through when creating a lesson plan, to do a better job overall?" (I know...I know...it's not as catchy) This way, the process looks something like this. ------------------------- TO CREATE A LESSON PLAN, I DO THIS: 1️⃣ Reflect on the last lesson. ➝ How did the last lesson go? ➝ How did my students respond? ➝ Do I need to fill the gap between lessons? "This is all me. No AI required." Balance: 100% 🙂 0% 🤖 2️⃣ Think about the current topic. ➝ What are some misconceptions about it? ➝ What are the main skills we're tapping into? ➝ How can I make it relevant for my students? "I can use AI to help me creatively brainstorm." Balance: 80% 🙂 20% 🤖 3️⃣ Figure out how to encourage everyone to be mentally present. ➝ How can I get attention productively? ➝ How can I help us be mentally present? ➝ Will an ice breaker or similar activity help? "I'm happy too offload more of this, because I suck at it. I am horrendous at planning the first 5 minutes, in a way that isn't hokey. So, I'll ask AI for suggestions and poke and prod until I get what I like." Balance: 20% 🙂 80% 🤖 4️⃣ Design a hands-on activity. ➝ Would a game help? ➝ Would group work help? ➝ How can I personalize this? ➝ Would student-led discussion help? ➝ How can we move from theory to practice? ➝ What kind of practice might help here? "Let me start planning, and I'll try to figure out if AI can help. I'll start, and then use AI if I get stuck and need something to bounce ideas off of. I'll do this, especially if my planning starts to feel stale." Balance: It's different every time!! Usually, it ends up being: 75% 🙂 25% 🤖 5️⃣ Wrap things up. ➝ What do I want people to leave with? "It's better if I do this myself, unless I'm really stumped." Balance: 90% 🙂 10% 🤖 Basically, it's complicated. But using AI isn't an either/or decision ---------- Images: From John Warner's recent article, "Calling B.S. on the AI Education Future." It makes great points, though. I disagree with a lot of it. The full article: https://lnkd.in/ehQ-wqci