How Schools can Address Future Literacy Needs

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

A New Era of AI-Generated Humans: OmniHuman-1 Imagine scrolling through a social media feed, watching a video of a person giving a passionate speech, singing a song, or doing any number of things, and not even realizing that the person isn’t real! That’s the reality we are entering with ByteDance’s newly unveiled OmniHuman-1 model, an AI system capable of ultra-realistic human animation (link in comments). This model is not yet available to consumers, but imagine a future in which this capability is built into a platform such as TikTok, and every user has this capability? This advancement underscores a growing challenge in AI literacy: if we can no longer distinguish between real and AI-generated humans, how can we ensure our students and educators are prepared to navigate this world responsibly? I talk a lot about preparing students for the future job market, but AI literacy is also about preparing them to be critical and ethical creators and consumers. Education leaders have long emphasized digital literacy, but the rise of generative AI demands AI fluency, not just to detect AI-generated content but to ethically collaborate with AI, critically evaluate AI-generated media, and understand its implications on democracy, privacy, and the job market. If your school is still operating as if AI is not completely changing the world around us, your students will not be ready for what is coming. If OmniHuman-1 can create lifelike human animations today, what will AI be capable of in five years? The ability to differentiate reality from AI-generated content will become as fundamental as reading and writing. Education leaders must prioritize AI literacy now, ensuring that students graduate with the skills, ethics, and critical thinking needed to thrive in an AI-driven world. AI literacy isn’t a future need—it’s an urgent necessity. Education leaders must take immediate steps to: 1. Create AI Literacy Guidelines – Establish clear guidelines for AI use in schools to foster responsible engagement rather than banning tools outright. 2. Incorporate AI Literacy into the Curriculum – Teach students not just about how AI works, but how to critically analyze AI-generated content, question its biases, and assess its credibility. 3. Empower educators with ongoing, job-embedded AI training – so teachers understand how to use AI responsibly in the classroom and how to guide student use. 4. Re-think traditional pedagogy– Focus on the durable skills that will serve them in an uncertain future (such as those in the NC Portrait fo a Graduate), emphasize learning process over product, increased student agency, frequent formative assessment, authentic assessment such as PBL & learning portfolios. The future is NOT waiting and education can not afford to either. Are your schools ready? North Carolina Department of Public Instruction

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

Exciting developments in AI education are reshaping the landscape from K-12 to universities. 🚀 The recent spotlight on AI majors at renowned institutions like Penn, Rice, and Carnegie Mellon signals a significant shift—AI is no longer on the periphery but at the core of academic disciplines. However, the key to unlocking the full potential of AI doesn't start in college—it begins much earlier. Building a foundation in digital fluency during K-12 lays the groundwork for essential thinking skills and curiosity that are vital in the AI realm. Why is early exposure crucial? - The AI job market extends beyond traditional engineering roles, encompassing positions such as prompt engineers, AI product managers, data curators, and ethicists, all stemming from early exposure to AI, not just algorithms. - Employers are increasingly prioritizing demonstrable AI skills over formal degrees, emphasizing the importance of practical expertise in the field. - Commencing AI education in elementary or middle school allows students to learn, experiment, and grow without fear of failure, preparing them to innovate in college and beyond. Ensuring equity in AI education is paramount. Not all students have access to elite AI programs, but early-access initiatives, such as those offered by platforms like Tynker, can democratize opportunities and bridge the gap, enabling all students to pursue a future in the AI workforce. What steps can we take? - Advocate for AI-centric curricula in K-12 education, transitioning from experimental projects to sustainable initiatives. - Invest in educators' AI literacy to equip them with the essential knowledge needed to guide students effectively. - Promote platforms like Tynker that provide engaging pathways for younger learners to explore AI creatively and build confidence. While university AI degrees validate the importance of AI, the true groundwork for success begins long before college. Let's champion early AI literacy, empowering K-12 students with the critical and creative skills needed for future innovation, not just jobs. #AILiteracy #K12Education #EdTech #AI #Startups #Students #Teachers #Jobs #College https://lnkd.in/gmKuNYqS

As a leader in the academic innovation space, like many of you, I've been exploring how we reimagine the ways we assess learning, and how we define what it means to learn something. Looking forward, not just for what believe students need to know today but for the skills and competencies they’ll need in the workforce of tomorrow. Futures Literacy, developed by UNESCO, has been an invaluable framework for this work, as a process to help envision unimaginable, innovative approaches to assessment that align with the jobs of the future. Futures Literacy invites us to confront our anticipatory assumptions. Those often unexamined beliefs that shape our expectations about how we can do things. It challenges us to explore not only what is possible but also what is preferred. This mindset is crucial as we consider how GenAI is transforming teaching and learning. The big challenges I'm interested in exploring: How do we design assessments that prepare individuals for roles that don’t yet exist? How do we measure those things that are hard to measure such as care, empathy, creativity, critical thinking, adaptability, and collaboration. In my work, I use the Futures Literacy framework to help reimagine assessments that: Equip learners to navigate a world of constant technological evolution. Prioritize transferable skills like problem-solving, ethical reasoning, and AI fluency. Foster equity and inclusion, ensuring pathways to opportunity for all learners, especially those historically underrepresented in tech and AI-driven fields. I’d love to hear from you: How are you rethinking assessment to align with future workforce needs? Not just reimagining how to do what we currently do differently with GenAI, but entirely reimagining our approach? What assumptions are driving your current strategies for preparing learners for the jobs of tomorrow? What does your preferred future for assessing learning look like in the age of AI? Let’s co-create a vision where assessment doesn’t just measure learning but inspires it. Preparing the next generation to thrive in an AI-driven world. Share your thoughts below or DM me to start the conversation! #FuturesLiteracy #EducationInnovation #AIinEducation #GenerativeAI #FutureOfAssessment #FutureOfWork

By the time today’s freshmen graduate, much of what they learned will be obsolete. The fix isn’t just better curriculum — it’s better thinking. My computer science degree taught me languages and algorithms. But what prepared me for my career? Two years of hands-on coding at Motorola while still in school. That real-world work taught me to solve ambiguous problems, adapt fast, and deliver under pressure — skills no classroom can teach. What school did give me was the ability to think critically, analyze complex systems, and learn continuously. These meta-skills matter far more than memorizing code. Today, this is more urgent than ever. AI and tech evolve so fast that freshman year knowledge can be outdated by senior year. Universities must shift focus: teach students how to think critically and learn continuously — so they can adapt and lead no matter how fast technology changes. And they must make AI literacy foundational across all disciplines — not just coding, but understanding how AI shapes decisions, automates work, and disrupts industries. This empowers graduates to use AI strategically, evaluate its impact, and collaborate with it — not compete against it. The future of education is clear: 🔹 AI literacy in every field 🔹 Critical thinking and continuous learning 🔹 Tech fluency balanced with human creativity Today is World Youth Skills Day. On #WorldYouthSkillsDay, let’s commit to building lifelong learners who don’t just survive change — they drive it. #AI #FutureOfWork #Leadership #artificialIntelligence

The current AI literacy movement has a blind spot: it operates in a vacuum. Most AI literacy frameworks focus on skills like prompt engineering, bias detection, and ethical reasoning. These are important. But they miss a crucial reality: the infrastructure decisions that districts make today will determine which AI literacy skills actually matter tomorrow. I need to share something critical I'm seeing: what I've started calling 'infrastructure literacy' - a pattern emerging among successful AI adopters that goes far beyond basic tool competency or prompt engineering. This isn't about mastering AI capabilities or understanding model limitations. Instead, it manifests as a particular kind of strategic awareness: the ability to see and critically evaluate how platform decisions shape learning possibilities, all while navigating vendor ecosystems with nuanced judgment. Here's what I'm observing: successful districts aren't just comparing AI tool features - they're analyzing how different choices constrain or enable their pedagogical vision. They're mapping out how Google's Gemini integration affects existing workflows, then examining the long-term implications for vendor dependency. What's striking is how this capability develops. It's not through traditional training or AI literacy curricula. Instead, it emerges through repeated cycles of three distinct types of engagement: Infrastructure assessment - evaluating how platform choices align with educational goals Integration analysis - examining workflow implications and adoption barriers Ecosystem navigation - balancing convenience against pedagogical control Each cycle builds not just technical knowledge but strategic judgment. Leaders develop an almost intuitive sense of when platform integration serves learning, when it creates dependency, and when to prioritize specialized solutions over convenient ones. This observation suggests we might need to fundamentally rethink how we approach AI literacy in educational settings. Instead of focusing on universal skills or abstract concepts, perhaps we should be developing capacity to navigate the specific infrastructure realities that will determine which AI literacies actually matter. The future of AI in education won't be determined by the best AI literacy curriculum. It will be determined by the infrastructure decisions we make today and whether our literacy efforts account for those realities. Alfonso Mendoza Jr., M.Ed. Aman Kumar Amanda Bickerstaff Dr. Sabba Quidwai Vriti Saraf Mike Kentz David H. Owen Matson, Ph.D. Polina Sapunova

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