How Education can Address AI's Impact

Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education (published in International Journal of Educational Technology in Higher Education by Springer Nature Group) The present discussion examines the transformative impact of Artificial Intelligence (AI) in educational settings, focusing on the necessity for AI literacy, prompt engineering proficiency, and enhanced critical thinking skills. AI literacy is identified as crucial, encompassing an understanding of AI technologies and their broader societal impacts. Prompt engineering is highlighted as a key skill for eliciting specific responses from AI systems, thereby enriching educational experiences and promoting critical thinking. This is discussed through a case-study based on a Swiss university and a narrative literature review, followed by practical suggestions of how to implement AI in the classroom. 💡 Key Ideas: 1. #AILiteracy is crucial for students and teachers to understand AI capabilities, limitations, and societal impacts. This knowledge enables responsible and effective use of AI in education. 2. #Prompt engineering skills allow educators to strategically design prompts that elicit desired behaviors and critical thinking from AI systems. This transforms AI into an interactive pedagogical tool. 3. #Fostering #CriticalThinking skills through AI use is vital, enabling analysis of information, evaluation of perspectives, and reasoned arguments within AI environments. This prepares students for an AI-driven world. 4. #Continuous AI #training and support for teachers is essential as rapid advancements can otherwise outpace educator knowledge, causing classroom management issues. Keeping teachers updated enables successful AI integration. 5. Addressing #AI #bias through diverse and inclusive training data is important to prevent inequities. Educator training in recognizing biases is also necessary to avoid perpetuating prejudices. 🔧 Recommendations: 1. Develop comprehensive AI literacy courses and integrate AI ethics discussions across subjects to promote responsible use. 2. Provide regular AI training workshops for teachers on prompt engineering, bias recognition, and pedagogical integration to close knowledge gaps. 3. Fund programs that increase equitable access to AI education tools, targeting underprivileged schools and diverse learners. 4. Encourage critical analysis of real-world AI case studies to highlight societal impacts and ethical considerations. 5. Foster an institutional culture of open AI communication through forums and collaborations. This enables continuous learning and innovation. https://lnkd.in/e4xhDdg2

If students don’t learn how to think with AI, they’ll let AI think for them. Last Thursday at Shanghai American School, I got to "beam in" to give a keynote presentation on one of the most urgent conversations in education today: How do we integrate AI without losing what makes learning human? Here are the key takeaways from our time together: • Generative AI can amplify learning—or weaken it. Studies show that when students engage critically with AI, they learn more. But when they rely on it to do the work for them, learning declines. The key? Teach students to think with AI, not just use it. • Confidence in AI can lower critical thinking. Research suggests that when people trust AI too much, they question it less. The best educators will teach students how to balance trust and skepticism when using AI tools. • Ethical AI use starts with values. We discussed how every school needs guiding principles for AI integration—beyond just policies. What should we protect? What should we enhance? These questions shape AI’s role in education. We concluded with "Three Ts" for responsible AI use: 1. Talk – Normalize generative AI discussions with students and teachers. I shared my "Generative AI Guidelines Canvas" to support conversations. https://lnkd.in/gyjTkK7d 2. Teach – Build generative AI literacy into the curriculum. I shared Cora Yang and Dalton Flanagan's C.R.E.A.T.E. framework for teaching students to prompt. https://lnkd.in/g-KYt4Uy 3. Try – Teachers should experiment with generative AI tools in meaningful, ethical ways. I shared Darren Coxon's Hattie Bot to let teachers experiment with building lessons that have high effect size. https://lnkd.in/g44gZzA3 This conversation isn’t over—it’s just beginning. Critical thinking isn't optional if machines do the easy thinking for us. Much gratitude to Alan Preis & Scott Williams for crafting such a great experience. Photo Credit Alex McMillan 🙏 P.S. I asked everyone at Shanghai American School: What values should guide our approach to AI in education? What's your answer? #generativeAI #guidelines #teachers #ethics

Each year it takes me several days and multiple times listening to the brilliant Amy Webb's Annual Tech Trend Report to analyze the major takeaways for k12 education. Her report is mind blowing! These trends underscore the rapid pace of technological innovation and its profound impact on society. 👉 To ensure that students are prepared for a future shaped by Artificial Intelligence, Quantum Computing, Biotechnology, Sustainable Energy, and Extended Reality, education must proactively integrate these emerging technologies into curriculum, pedagogy, and learning environments. Here’s what #educators and #edleaders can do now to prepare: 1️⃣ Invest in Education and Public Awareness: Educate the public (teachers, students, parents, & community) about upcoming technologies to promote informed decision-making, ethical considerations and public engagement. 2️⃣ Artificial Intelligence: Integrate #AILiteracy into K-12 by teaching students how #AI works, its ethical implications, and career impact; leveraging AI-powered tools and adaptive learning platforms to personalize learning and enhance engagement; and fostering classroom discussions on AI ethics, bias, misinformation, and responsible usage. 3️⃣ Quantum Computing: Incorporate computational thinking and quantum basics in #STEM courses to introduce new problem-solving approaches, and foster interdisciplinary learning by connecting quantum applications to fields such as #cybersecurity, #medicine, and #finance. 4️⃣ Biotechnology: Expand access to hands-on biotech experiences through lab-based learning, bioengineering projects, teaching biomimicry, engaging in ethical debates; collaborate with biotech companies for #internships and real-world applications and integrate bioethics into the curriculum to explore the moral and societal implications of genetic engineering, CRISPR, and personalized medicine. 5️⃣ Sustainable Energy: Promote green #STEM education by integrating renewable energy, environmental science, and sustainability into coursework; engage students in hands-on energy initiatives like solar panel installations, wind energy experiments, and sustainability challenges; and teach energy policy and its global impact to prepare students for careers in climate solutions #CTE. 6️⃣ Extended Reality (XR): Incorporate immersive #VR/#AR learning experiences for science simulations, historical reenactments, and skill-based training; leverage XR for career readiness #CTE through virtual job shadowing, simulations, and hands-on technical training; and train educators on XR integration to enhance lesson engagement & connect abstract concepts to real-world. 💡 After we have met the basic needs of all students, K12 Leaders, where do we begin preparing them for the future? Full Report: https://lnkd.in/esP6mxe2 Watch: https://lnkd.in/eA2j8EEm Future of Education Technology Conference, District Administration

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.

NEW policy released around AI in education. Here's what you can't miss of what's to come: U.S. Department of Education's AI guidelines are here! #1 theme: Balance between AI efficiency and human oversight. AI streamlines processes, but still be aware of risks & biases. Educators in control, using AI to amplify their capabilities. Example: AI-assisted custom curriculum creation Input standards & requirements, get structured output. But human expertise crucial for proofreading & refinement. Tool spotlight: Anthropic's Claude Projects for educators Compile sources: standards, lesson plans, and samples. Create comprehensive, tailored educational materials. Innovative use case: AI-powered grading assistance Upload rubrics, top examples, and your student's work. Get comparative feedback and improvement suggestions. The future of education = Human-guided, AI-enhanced learning Saving time, improving quality, and benefiting students. P.S. Thanks for the insights, Katie Wrathall! (follow her for more on modern education) P.P.S. How do you see AI shaping the future of education?

The conversation around AI in education often focuses on teacher efficiency (creating lesson plans faster, responding to emails quicker) but we aren’t spending nearly enough time talking about the importance of modeling the use of AI for our students. Using AI to improve efficiency is just the beginning, not the goal. The real opportunity? Empowering students for an AI-driven future. 🔹 How can we model using AI as a brainstorming partner? 🔹 How can we use AI to provide feedback to enhance learning? 🔹 How do we teach students to use AI to synthesize complex information? Yes, AI can save time. But more importantly, it can shape the next generation of thinkers, creators, and leaders. Let's shift the conversation! How are you helping students engage with AI meaningfully? ISTE ASCD #FutureOfLearning

How Should Education Evolve in the AI Era? Last night at Northwestern University’s SF campus, we had a fantastic opportunity to reconnect with MSL alumni and discuss the evolving challenges of education in the AI age. Huge thanks to Evan Goldberg and Leslie Oster for organizing, and to Professors Daniel B. Rodriguez and Emerson Tiller for their insightful discussion. 🔍 Key Challenges in Education: 📌 The Expertise Gap – If AI takes over routine tasks traditionally handled by juniors, how will juniors gain the foundational experience needed to grow into senior roles and become experts? 📌 Faculty Adaptation – Many professors were trained before AI, making faculty upskilling and curriculum updates essential. 📌 Industry Feedback – Prompt engineering courses are being introduced, but structured industry feedback mechanisms remain underdeveloped. 🌟 These shifts in education extend far beyond law—they impact medicine, business, engineering, and more. 🚀 Where Education Must Evolve: ✅ Mastering Prompting Skills – Becoming an expert in asking the right questions to guide and instruct AI effectively. ✅ Critical Thinking & Verification – Developing the ability to evaluate AI-generated content for accuracy, bias, and real-world application – essentially becoming a ‘judge’ of AI outputs. ✅ Redefining Expert – Seniority does not equal expertise. True expertise lies in specialized knowledge and ensuring AI outputs are accurate and verifiable. A junior with niche skills and knowledge can be an expert—and highly employable. ✅ Getting Industry Feedback Involved – Every prompt needs real-world testing, and industry collaboration is essential to ensure these skills translate into practical impact. 💡 The Good News? 1️⃣ Pioneering programs like Northwestern Master of Science in Law are already addressing this need. At the intersection of law, business, and technology, it offers courses in 🌟 prompt engineering 🌟. 📖 Learn more here: https://lnkd.in/eD4VFRtG 2️⃣ We’re also building solutions to help students / professionals create, refine, and test expert-level prompts, ensuring they can actively contribute in an AI-driven world and receive real-world feedback. This discussion highlighted both challenges and opportunities. If you’d like to keep the conversation going and contribute your insights to help education and talent development evolve, I’d love to hear your thoughts: 🎓 If you’re a higher education professional, how is your institution preparing students for an AI-driven future? 🚀 If you’re a student or job seeker, how are you preparing yourself to manage AI tools and models—key skills for the workforce of the future? 🎯 Let’s exchange ideas and rethink education and talent development together. #AIinEducation #FutureOfLearning #EdTech #AIandWork #HRTech

Sal Khan's Vision of Education in the Age of AI In the early days after the #ChatGPT launch, one of the most topical discussions centered on how it would impact the world of education. As time has passed, schools have been forced to recognize that #AI is here to stay, and a vision for coexistence is necessary. I recently listened to an interview between Adam Grant and Sal Khan, founder of Khan Academy. They delved into the evolving landscape of education, highlighting the transformative role of AI in reshaping learning processes and outcomes. Khan emphasizes the significance of mastery learning in education, a paradigm shift from traditional methods that often leave students with gaps in understanding. He advocates for a system where students are not just pushed forward after achieving a minimum grade but are encouraged to attain full comprehension of a topic. Leveraging AI will help achieve this goal. He envisions AI playing a pivotal role in personalizing education. He foresees AI as a tool to address the long-standing challenge of differentiation in teaching, where students' unique interests and learning paces are accommodated. AI, according to Khan, could act as a one-on-one tutor, providing tailored support to each student. This individualized approach could help bridge learning gaps, thereby promoting mastery. He discusses the potential of AI in enhancing writing skills. He proposes a scenario where AI acts as a writing coach, helping students outline and draft essays while providing feedback aligned with the assigned rubric. This concept not only aids in developing writing skills but also makes it difficult to cheat, as the process focuses on individual thought development rather than just the final outcome. Khan suggests using AI to rejuvenate students' interest in classic literature. By enabling interactions with literary characters or immersive experiences in the story's world, AI could make literature more engaging and relevant to students. This approach could potentially transform the perception of classics from tedious assignments to enjoyable, insightful experiences. Khan expresses concern that current education levels, even at the college graduate stage, are not adequate in the face of advanced AI capabilities. He stresses the need for education systems to elevate critical thinking, writing, and comprehension skills to a level where individuals can not only use AI effectively but also surpass its capabilities in creativity and refinement. Sal Khan's vision for education in the AI era revolves around leveraging AI to create personalized, mastery-focused learning experiences while preparing students to coexist with and excel beyond AI's capabilities. This vision requires a fundamental rethinking of educational approaches, focusing on developing a deeper understanding and critical skills that remain essential in an AI-augmented world. #JordiPlusJarvis #SalKhan Note: This is an AI generated image.

AI is revolutionizing education, offering tools that personalize learning and break down barriers. But with great power comes great responsibility. Let’s unpack the ethical challenges facing AI-EdTech: → Algorithmic Transparency How does AI decide which student gets which resources? Companies must ensure transparency, enabling educators and learners to understand and trust the system. → Combating Algorithmic Bias AI learns from data, but data isn’t always neutral. To prevent discrimination, algorithms need regular audits and updates. Equity isn’t optional—it’s essential. → Data Privacy & Security Student data is sensitive. From complying with regulations to protecting against breaches, EdTech companies must make privacy a top priority. Clear communication about data usage builds trust. → Balancing Profit with Purpose Profitability drives innovation, but it should never overshadow the mission to educate. Purpose-driven innovation focuses on solving real challenges, not just riding the AI wave. → Engaging Stakeholders Teachers and students know the classroom best. Collaborating with them ensures AI tools meet genuine needs while maintaining ethical integrity. → Navigating Regulatory Challenges The laws governing AI in education are still catching up. Companies should advocate for clear, ethical guidelines while proactively ensuring compliance. The bottom line? Corporate responsibility in AI-EdTech isn’t just good PR—it’s a necessity. By aligning profit with purpose, we can create tools that truly serve learners, uphold ethical standards, and build a future where education and innovation thrive together. The Bertrand Education Group (B.E.G) What are your thoughts on balancing ethics and business in AI-EdTech? Let’s discuss!

The U.S. Department of Education proposes a new discretionary grant priority on AI in education. 30 day public comment period. Background & Rationale - AI is reshaping education and the workforce, making AI literacy crucial for students. - AI tools can support personalized instruction, engagement, and learning outcomes. - Computer science education is foundational to understanding and using AI responsibly. - Educator training and early exposure to AI concepts are key to workforce readiness and innovation. Proposed Priority Areas (a) Expand AI Understanding - Integrate AI literacy and misinformation detection into teaching. - Expand K-12 and higher education offerings in AI and computer science. - Embed AI into teacher preparation and professional development. - Support dual-enrollment and certification pathways in AI. - Build and share evidence for effective AI integration in education. (b) Expand AI Use in Education Use AI to support: - Gifted students or those needing advanced learning. - Students below grade level or needing additional support. - Students with disabilities and their families. - Deploy AI-powered personalized learning tools ("This integration may include, but is not limited to, adaptive learning technologies, virtual teaching assistants, tutoring, and data analytics tools to support student progress") - Promote AI in teacher training and operational efficiency. - Use AI technology to provide high-quality instructional resources, high-impact tutoring, and college and career pathway exploration, advising, and navigation to improve educational outcomes. Submit comments by August 20, 2025. The full Federal Register notice is here: https://lnkd.in/eC5jf-Dk FYI: Kim Smith, Alex Kotran, Pat Yongpradit, Claire Zau, Jean-Claude Brizard, Amy Chen Kulesa, Mary Wells, Cheryl Oldham, Caitlin Codella Low, Kyle Butler, Julia Freeland Fisher, Alex Swartsel, Rebecca Finlay, Daniel Correa, Reeve Bull, Cassandra Madison, Jennifer Anastasoff, Richard Culatta, Gabriela Lopez, Robin Lake, Bree Dusseault, Brent Orrell, Hayley S., Meg Evans, Angie Cooper, Krista Cupp, Elizabeth Pishny