Tag: educators

  • Immigration enforcement is driving away early childhood educators

    Immigration enforcement is driving away early childhood educators

    by Jackie Mader, The Hechinger Report
    December 10, 2025

    Close to 40,000 foreign-born child care workers have been driven out of the profession in the wake of the Trump administration’s aggressive deportation and detainment efforts, according to a new study by the Better Life Lab at the think tank New America. That represents about 12 percent of the foreign-born child care workforce.

    Child care workers with at least a two-year college degree are most likely to be leaving the workforce, as well as workers who are from Mexico, a demographic targeted by ICE, or those who work in center-based care, the left-leaning think tank found. The disruption has worsened an already deep shortage of child care staffers, threatening the stability of the industry and in turn is contributing to tens of thousands of U.S.-born mothers dropping out of the labor market because they don’t have reliable child care.

    In addition to workers facing detainment or deportation, many people are staying home to avoid situations where they may encounter Immigration and Customs Enforcement (ICE), the report found. Agents are detaining people who have not traditionally been the focus of ICE actions, including those following legal pathways like asylum seekers and green card applicants. Child care centers were once considered “sensitive locations” exempt from ICE enforcement, but the White House rescinded that in January. In at least one example, a child care worker was detained while arriving for work at a child care program. 

    “What’s different now is the ferocity of the enforcement,” said Chris Herbst, a professor at Arizona State University’s School of Public Affairs and one of the authors of the report, in an interview with The Hechinger Report. “ICE is arresting far more people, the number of deportations has risen dramatically,” he added. “People are scared out of their minds.”

    Related: Young children have unique needs and providing the right care can be a challenge. Our free early childhood education newsletter tracks the issues. 

    America has long relied on immigrants to fill hard-to-staff caregiving positions and enable parents to work. Across the country, around 1 in 5 child care workers is an immigrant. In Florida and New York, immigrants account for nearly 40 percent of the child care workforce. One study that compared native-born and immigrant child care workers found that nearly 64 percent of immigrants had a two- or four-year college degree, compared to 53 percent of native-born workers. The study also noted that immigrant workers are more likely than native-born workers to have child development associate credentials and to invest in professional development activities.

    Overall, the child care industry supports more than $152 billion in economic activity.

    In Wisconsin, Elaine, the director of a child care center, said her program has benefited greatly from a Ukrainian immigrant who has been teaching there for two years, ever since arriving in the United States as part of a humanitarian parole program. (The Hechinger Report is not using Elaine’s last name or the city where her child care center is located because she fears action by immigration enforcement.) Elaine’s center has experienced a teacher shortage for the past 13 years, and the immigrant, who has a college degree and past experience in social services, has been a steady presence for the children there.

    “She’s their consistent person. She spends more time than a lot of the parents do with the children during their waking hours,” Elaine said. “She’s there for them, she’s loving, she provides that support, that connection, that security that young children need.”

    In January, the Trump administration suspended the Uniting for Ukraine program, which allowed Ukrainians fleeing the Russian invasion to live and work in the United States for two years. While the program later opened up a process to apply for an extension, Elaine’s employee has encountered delays, like many others.

    The teacher’s parole expired this month. Under the law, she is now supposed to return to Ukraine, where her home city in southeast Ukraine is still under attack by Russian forces. 

    Elaine fears what will happen if the center loses her. “As a business, we need her. We need a teacher we can count on,” Elaine said. “For our teachers’ mental health, to have her leave and knowing where she would go would be really difficult.” 

    Elaine has decided to allow the employee to keep working, and is appealing to state lawmakers to help extend her stay. Several parents have also joined in the effort, writing letters to Democratic U.S. Sen. Tammy Baldwin telling her how much their children love the teacher — and how important she is to the local economy. One factor in granting an extension is that the person offers a “significant public benefit” to the country. 

    The authors of the new report found immigrants are not the only caregivers affected by ICE enforcement this year. There has also been a drop in U.S.-born child care workers in the industry, especially among Hispanic and less-educated caregivers. This could be the result of a “climate of fear and confusion” surrounding enforcement activity, according to the report, as well as a “perceived pattern of profiling or discriminatory enforcement practices.”

    “These deportations have been sold under the theory that they are going to be a boon for U.S.-born workers once we sort of unclog the labor market by removing large numbers of undocumented immigrants,” Herbst said. “We’re finding at least in the child care industry, and at least in the short run, that appears not to be the case.” Some foreign-born and U.S.-born workers have different skills and do not seem to be competing for the same caregiving jobs, he added. 

    Not all workers are leaving the caregiving industry altogether. Some immigrants are shifting to work as nannies or au pairs, Herbst said, “finding refuge” in private homes where they are less likely to come into contact with state child care regulators or be part of formal wage systems. (Already, an estimated 142,000 undocumented immigrants work as nannies and personal care or home health aides nationwide.) That contact with regulators and other authorities may be a reason why center-based early childhood educators are leaving the field in greater proportions now, Herbst said. 

    These findings come at the end of a difficult year for the child care workforce, which has long been in crisis due to dismally low pay and challenging work conditions. More than half of child care providers surveyed this year by the RAPID Survey Project at Stanford University reported experiencing difficulty affording food, the highest rate since the survey started collecting data on provider hunger in 2021. Other recent reports have found child care providers are at a higher risk for clinical depression, and in some cities an increasing number are taking on part-time jobs to make ends meet.

    Across the country this year, early childhood providers have seen drops in enrollment as families pull their children out of schools and programs to avoid ICE. Child care centers are losing money and finding that some staff members are too scared to come to work or have lost work authorization after the administration ended certain refugee programs. Many child care workers have taken on additional roles driving children to and from care, collecting emergency numbers and plans for children in their care in case parents are detained and dropping off food for families too scared to leave their homes.

    This story about immigration enforcement was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for the Hechinger newsletter.

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  • How AI can fix PD for teachers

    How AI can fix PD for teachers

    Key points:

    The PD problem we know too well: A flustered woman bursts into the room, late and disoriented. She’s carrying a shawl and a laptop she doesn’t know how to use. She refers to herself as a literacy expert named Linda, but within minutes she’s asking teachers to “dance for literacy,” assigning “elbow partners,” and insisting the district already has workbooks no one’s ever seen (awalmartparkinglott, 2025). It’s chaotic. It’s exaggerated. And it’s painfully familiar.

    This viral satire, originally posted on Instagram and TikTok, resonates with educators not because it’s absurd but because it mirrors the worst of professional development. Many teachers have experienced PD sessions that are disorganized, disconnected from practice, or delivered by outsiders who misunderstand the local context.

    The implementation gap

    Despite decades of research on what makes professional development effective–including a focus on content, active learning, and sustained support (Darling-Hammond et al., 2017; Joseph, 2024)–too many sessions remain generic, compliance-driven, or disconnected from day-to-day teaching realities. Instructional coaching is powerful but costly (Kraft et al., 2018), and while collaborative learning communities show promise, they are difficult to maintain over time.

    Often, the challenge is not the quality of the ideas but the systems needed to carry them forward. Leaders struggle to design relevant experiences that sustain momentum, and teachers return to classrooms without clear supports for application or follow-through. For all the time and money invested in PD, the implementation gap remains wide.

    The AI opportunity

    Artificial intelligence is not a replacement for thoughtful design or skilled facilitation, but it can strengthen how we plan, deliver, and sustain professional learning. From customizing agendas and differentiating materials to scaling coaching and mapping long-term growth, AI offers concrete ways to make PD more responsive and effective (Sahota, 2024; Adams & Middleton, 2024; Tan et al., 2025).

    The most promising applications do not attempt one-size-fits-all fixes, but instead address persistent challenges piece by piece, enabling educators to lead smarter and more strategically.

    Reducing clerical load of PD planning

    Before any PD session begins, there is a quiet mountain of invisible work: drafting the description, objectives, and agenda; building slide decks; designing handouts; creating flyers; aligning materials to standards; and managing time, space, and roles. For many school leaders, this clerical load consumes hours, leaving little room for designing rich learning experiences.

    AI-powered platforms can generate foundational materials in minutes. A simple prompt can produce a standards-aligned agenda, transform text into a slide deck, or create a branded flyer. Tools like Gamma and Canva streamline visual design, while bots such as the PD Workshop Planner or CK-12’s PD Session Designer tailor agendas to grade levels or instructional goals.

    By shifting these repetitive tasks to automation, leaders free more time for content design, strategic alignment, and participant engagement. AI does not just save time–it restores it, enabling leaders to focus on thoughtful, human-centered professional learning.

    Scaling coaching and sustained practice

    Instructional coaching is impactful but expensive and time-intensive, limiting access for many teachers. Too often, PD is delivered without meaningful follow-up, and sustained impact is rarely evident.

    AI can help extend the reach of coaching by aligning supports with district improvement plans, teacher and student data, or staff self-assessments. Subscription-based tools like Edthena’s AI Coach provide asynchronous, video-based feedback, allowing teachers to upload lesson recordings and receive targeted suggestions over time (Edthena, 2025). Project Café (Adams & Middleton, 2024) uses generative AI to analyze classroom videos and offer timely, data-driven feedback on instructional practices.

    AI-driven simulations, virtual classrooms, and annotated student work samples (Annenberg Institute, 2024) offer scalable opportunities for teachers to practice classroom management, refine feedback strategies, and calibrate rubrics. Custom AI-powered chatbots can facilitate virtual PLCs, connecting educators to co-plan and share ideas.

    A recent study introduced Novobo, an AI “mentee” that teachers train together using gestures and voice; by teaching the AI, teachers externalized and reflected on tacit skills, strengthening peer collaboration (Jiang et al., 2025). These innovations do not replace coaches but ensure continuous growth where traditional systems fall short.

    Supporting long-term professional growth

    Most professional development is episodic, lacking continuity, and failing to align with teachers’ evolving goals. Sahota (2024) likens AI to a GPS for professional growth, guiding educators to set long-term goals, identify skill gaps, and access learning opportunities aligned with aspirations.

    AI-powered PD systems can generate individualized learning maps and recommend courses tailored to specific roles or licensure pathways (O’Connell & Baule, 2025). Machine learning algorithms can analyze a teacher’s interests, prior coursework, and broader labor market trends to develop adaptive professional learning plans (Annenberg Institute, 2024).

    Yet goal setting is not enough; as Tan et al. (2025) note, many initiatives fail due to weak implementation. AI can close this gap by offering ongoing insights, personalized recommendations, and formative data that sustain growth well beyond the initial workshop.

    Making virtual PD more flexible and inclusive

    Virtual PD often mirrors traditional formats, forcing all participants into the same live sessions regardless of schedule, learning style, or language access.

    Generative AI tools allow leaders to convert live sessions into asynchronous modules that teachers can revisit anytime. Platforms like Otter.ai can transcribe meetings, generate summaries, and tag key takeaways, enabling absent participants to catch up and multilingual staff to access translated transcripts.

    AI can adapt materials for different reading levels, offer language translations, and customize pacing to fit individual schedules, ensuring PD is rigorous yet accessible.

    Improving feedback and evaluation

    Professional development is too often evaluated based on attendance or satisfaction surveys, with little attention to implementation or student outcomes. Many well-intentioned initiatives fail due to insufficient follow-through and weak support (Carney & Pizzuto, 2024).

    Guskey’s (2000) five levels of evaluation, from initial reaction to student impact, remain a powerful framework. AI enhances this approach by automating assessments, generating surveys, and analyzing responses to surface themes and gaps. In PLCs, AI can support educators with item analysis and student work review, offering insights that guide instructional adjustments and build evidence-informed PD systems.

    Getting started: Practical moves for school leaders

    School leaders can integrate AI by starting small: use PD Workshop Planner, Gamma, or Canva to streamline agenda design; make sessions more inclusive with Otter.ai; pilot AI coaching tools to extend feedback between sessions; and apply Guskey’s framework with AI analysis to strengthen implementation.

    These actions shift focus from clerical work to instructional impact.

    Ethical use, equity, and privacy considerations

    While AI offers promise, risks must be addressed. Financial and infrastructure disparities can widen the digital divide, leaving under-resourced schools unable to access these tools (Center on Reinventing Public Education, 2024).

    Issues of data privacy and ethical use are critical: who owns performance data, how it is stored, and how it is used for decision-making must be clear. Language translation and AI-generated feedback require caution, as cultural nuance and professional judgment cannot be replicated by algorithms.

    Over-reliance on automation risks diminishing teacher agency and relational aspects of growth. Responsible AI integration demands transparency, equitable access, and safeguards that protect educators and communities.

    Conclusion: Smarter PD is within reach

    Teachers deserve professional learning that respects their time, builds on their expertise, and leads to lasting instructional improvement. By addressing design and implementation challenges that have plagued PD for decades, AI provides a pathway to better, not just different, professional learning.

    Leaders need not overhaul systems overnight; piloting small, strategic AI applications can signal a shift toward valuing time, relevance, and real implementation. Smarter, more human-centered PD is within reach if we build it intentionally and ethically.

    References

    Adams, D., & Middleton, A. (2024, May 7). AI tool shows teachers what they do in the classroom—and how to do it better. The 74. https://www.the74million.org/article/opinion-ai-tool-shows-teachers-what-they-do-in-the-classroom-and-how-to-do-it-better

    Annenberg Institute. (2024). AI in professional learning: Navigating opportunities and challenges for educators. Brown University. https://annenberg.brown.edu/sites/default/files/AI%20in%20Professional%20Learning.pdf

    awalmartparkinglott. (2025, August 5). The PD presenter that makes 4x your salary [Video]. Instagram. https://www.instagram.com/reel/DMGrbUsPbnO/

    Carney, S., & Pizzuto, D. (2024). Implement with IMPACT: A framework for making your PD stick. Learning Forward Publishing.

    Center on Reinventing Public Education. (2024, June 12). AI is coming to U.S. classrooms, but who will benefit? https://crpe.org/ai-is-coming-to-u-s-classrooms-but-who-will-benefit/

    Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute. https://learningpolicyinstitute.org/sites/default/files/product-files/Effective_Teacher_Professional_Development_REPORT.pdf

    Edthena. (2025). AI Coach for teachers. https://www.edthena.com/ai-coach-for-teachers/

    Guskey, T. R. (2000). Evaluating professional development. Corwin Press.

    Jiang, J., Huang, K., Martinez-Maldonado, R., Zeng, H., Gong, D., & An, P. (2025, May 29). Novobo: Supporting teachers’ peer learning of instructional gestures by teaching a mentee AI-agent together [Preprint]. arXiv. https://arxiv.org/abs/2505.17557

    Joseph, B. (2024, October). It takes a village to design the best professional development. Education Week. https://www.edweek.org/leadership/opinion-it-takes-a-village-to-design-the-best-professional-development/2024/10

    Kraft, M. A., Blazar, D., & Hogan, D. (2018). The effect of teacher coaching on instruction and achievement: A meta-analysis of the causal evidence. Review of Educational Research, 88(4), 547–588. https://doi.org/10.3102/0034654318759268

    O’Connell, J., & Baule, S. (2025, January 17). Harnessing generative AI to revolutionize educator growth. eSchool News. https://www.eschoolnews.com/digital-learning/2025/01/17/generative-ai-teacher-professional-development/

    Sahota, N. (2024, July 25). AI energizes your career path & charts your professional growth plan. Forbes. https://www.forbes.com/sites/neilsahota/2024/07/25/ai-energizes-your-career-path–charts-your-professional-growth-plan/

    Tan, X., Cheng, G., & Ling, M. H. (2025). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education: Artificial Intelligence, 8, 100355. https://doi.org/10.1016/j.caeai.2024.100355



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  • Modernizing the special education workforce is a national imperative

    Modernizing the special education workforce is a national imperative

    Key points:

    America’s special education system is facing a slow-motion collapse. Nearly 8 million students now receive services under the Individuals with Disabilities Education Act (IDEA), but the number of qualified teachers and related service providers continues to shrink. Districts from California to Maine report the same story: unfilled positions, overworked staff, and students missing the services they’re legally entitled to receive.

    “The promise of IDEA means little if there’s no one left to deliver it.”

    The data tell a clear story. Since 2013, the number of children ages 3–21 served under IDEA has grown from 6.4 million to roughly 7.5 million. Yet the teacher pipeline has moved in the opposite direction. According to Title II reports, teacher-preparation enrollments dropped 6 percent over the last decade and program completions plunged 27 percent. At the same time, nearly half of special educators leave the field within their first five years.

    By 2023, 45 percent of public schools were operating without a full teaching staff. Vacancies were most acute in special education. Attrition, burnout, and early retirements outpace new entrants by a wide margin.

    Why the traditional model no longer works

    For decades, schools and staffing firms have fought over the same dwindling pool of licensed providers. Recruiting cycles stretch for months, while students wait for evaluations, therapies, or IEP services.

    Traditional staffing firms focus on long-term contracts lasting six months or more, which makes sense for stability, but ignores an enormous, untapped workforce: thousands of credentialed professionals who could contribute a few extra hours each week if the system made it easy.

    Meanwhile, the process of credentialing, vetting, and matching candidates remains slow and manual, reliant on spreadsheets, email, and recruiters juggling dozens of openings. The result is predictable: delayed assessments, compliance risk, and burned-out staff covering for unfilled roles.

    “Districts and recruiters compete for the same people, when they could be expanding the pool instead.”

    The hidden workforce hiding in plain sight

    Across the country, tens of thousands of licensed professionals–speech-language pathologists, occupational therapists, school psychologists, special educators–are under-employed. Many have stepped back from full-time work to care for families or pursue private practice. Others left the classroom but still want to contribute.

    Imagine if districts could tap those “extra hours” through a vetted, AI-powered marketplace. A system that matched real-time school requests with qualified providers in their state. A model like this wouldn’t replace full-time roles; it would expand capacity, reduce burnout, and bring talent back into the system.

    This isn’t theoretical. The same “on-demand” concept has already modernized industries from medicine to media. Education is long overdue for the same reinvention.

    What modernization looks like

    1. AI-driven matching: Districts post specific service needs (evaluations, IEP meetings, therapy hours). Licensed providers choose opportunities that fit their schedule.
    2. Verified credentials and provider profiles: Platforms integrate state licensure databases and background checks to ensure compliance and provide profiles with all candidate information including on-demand, video interviews so schools can make informed hiring decisions immediately.
    3. Smart staffing metrics: Schools track fill-rates, provider utilization, and service delays in real time.
    4. Integrated workflows: The system plugs into existing special education management tools. No new learning curve for administrators.

    A moment of urgency

    The shortage isn’t just inconvenient; it’s systemic. Each unfilled position represents students who lose therapy hours, districts risking due-process complaints, and educators pushed closer to burnout.

    With IDEA students now representing nearly 15 percent of all public school enrollment, the nation can’t afford to let a twentieth-century staffing model dictate twenty-first-century outcomes.

    We have the technology. We have the workforce. What we need is the will to connect them.

    “Modernizing special education staffing isn’t innovation for innovation’s sake, it’s survival.”

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  • A Guide to Accessibility (for Educators)

    A Guide to Accessibility (for Educators)

    With the DoJ’s April 24, 2026 deadline approaching mandating all digital tools be accessible, every educator across the US (and Canada) is rushing to make their course materials accessible.

    An Incomplete Guide to Accessibility (for Educators) is for instructors, professors, or TAs that need help approaching digital accessibility. In plain language, we’ll demonstrate how to update learning materials to meet compliance—without treading all over your painstakingly-planned pedagogy. It’s important to emphasize that accessibility is ultimately about breaking barriers for people with disabilities, and this guide will strive to keep that in mind.

    Accessibility isn’t easy

    It’s important not to downplay the work needed to ensure digital materials are well-designed for everyone, without discrimination. 

    But… accessibility really isn’t that hard, either. 

    While more complex solutions can be harder to implement, the basics of accessibility are fairly easy to understand and action on. Start there, and grow over time. 

    It’s a skill. It takes practice. But it’s not rocket science, or evaluating 100 student essays on the diction of Shakespeare, either. Every week, educators share ideas and concepts with students, which, with any luck, germinate into critical thinking skills. Teaching is a much harder thing; accessibility is simple by comparison.

    As a digital product designer with over 20 years experience, I know the effort it takes to push accessibility forward. In 2020, Top Hat’s product and engineering team worked to make our platform more accessible for any student.

    The goal of this guide is to help you navigate this work, too.

    This guide is evolving

    The “incomplete” title of this guide is intentional. Members of the Top Hat team will add to this guide over time, but accessibility standards change. In software, compliance drift can happen as companies make updates to their little corner of the web. The very browser you’re using to read these words has likely been updated dozens or hundreds of times since this guide was written. 

    Obligatory legal note (sorry): Please don’t mistake this guide as legal advice or counsel. Consider this work an incomplete and imperfect list of suggestions from our experience, nothing more.

    We appreciate feedback 

    Both good and constructive feedback (what my cat’s therapist calls “bad” feedback) are encouraged. If you spot any gaps or errors in the guide, please let us know and we’ll remediate. Just send us an email to [email protected].

    Chapter 1: Making Sense of Compliance

    Awareness of the law is important, but don’t get lost

    It’s easy to get overwhelmed by all the accessibility laws flying about. Federal, DOJ, State. How do they measure up against each other? What do you need to care about?

    TLDR: WCAG 2.1 Level AA 

    WCAG 2.1 Level AA is the standard to follow. If you know what that alphabet salad means, you can probably skip this chapter. 

    It’s the W3C standard this guide (and Top Hat) uses. 

    A wave of legislation

    Here is a list of accessibility policies from the US. I recommend glossing over it, unless you enjoy sifting through rats nests of legalese for reasons I won’t ask about:

    Americans with Disabilities Act (ADA), Section 508 of the Rehabilitation Act. Arizona (digital accessibility standards in statewide IT policy), Arkansas (Act 1227 of 1999), California (multiple government code sections), Colorado (House Bill 21-1110), Connecticut (Universal Website Accessibility Policy), Delaware (State Digital Accessibility Policy), Georgia (digital properties accessibility), Idaho (Web Publishing Guidelines), Illinois (Illinois Information Technology Accessibility Act), Indiana (Code 4-13.1-3), Iowa (Website Accessibility Standard), Kansas (Information Technology Executive Council Policy), Maine (Digital Accessibility and Usability Policy), Maryland (Information Technology Nonvisual Access Regulatory Standards), Massachusetts (Enterprise Information Technology Accessibility Policy), Michigan (Digital Accessibility Standard), Minnesota (Digital Accessibility Standard), Missouri (RSMo. 161.935), Montana (state code 18-5-605), Nebraska (Accessibility Policy), Nevada (ADA Technology Accessibility Guidelines), New Hampshire (Web and Mobile Application Accessibility Standards), New Jersey (NJ A4856), New York (NYS-P08-005 and Senate Bill S3114A), Ohio (Administrative Policy, Website Ability), Oklahoma (Electronic and Information Technology Accessibility Law), Pennsylvania (Information Technology Policy), Rhode Island (World Wide Web Consortium Priority 1 Checkpoints), Texas (Web Accessibility Standards and Administrative Code), Utah (accessibility standards for executive branch agencies), Virginia (Information Technology Access Act and Accessibility Standard), and Washington (USER-01 Accessibility Policy). 

    You might have noticed not all states are listed. Some states decided to spare us the headache of adding more to this list. Americans with Disabilities Act (ADA)—the big kahuna of federal legislation—still applies.

    Real risk

    If your legal department puckers up at the word accessibility, you should know it’s because the risk to your school is real. The ADA publishes “settlements” on its website, which is a public list where complainant(s) have filed discrimination suit(s) against a corporation and settled. A good chunk of them are against educational institutions (K-12, community colleges, and big institutions alike).

    State and federal policy is not written for you

    Its job is to provide the judicial system the right to pursue action against anyone caught discriminating, and to make you aware that they can (and might) do that. Less discrimination is good for everyone. We like that idea. 

    But knowing there are arcane words hanging above every slide deck and document you decide to share with your student body is scary. There’s pressure here to Do The Right Thing.™

    Good news: There’s a simple way to meet state and federal legislation: WCAG. Protip: It’s pronounced wug-ka-guh.

    WCAG: One Standard to Rule them All 

    Bad news: WCAG is written by engineers, but don’t hold that against it. 

    WCAG stands for Web Content Accessibility Guidelines. It’s managed by the World Wide Web Consortium, otherwise known as “W3C,” which is a wizardly-sounding name, if you ask me. Most policies across the US and Canada list it as a standard to meet for digital accessibility (the only reason I’m not saying ALL policies is because I haven’t read them all, but I’m fairly certain everyone is just copying each other’s homework here).

    Understanding the WCAG Alphabet Salad: Versions and Levels

    There are levels to the WCAG standard, but it’s very simple to unpack.

    Which WCAG version?

    Because almost all legislation focuses on WCAG 2.1 Level AA, we’ve focused this guideline on that. 

    Why not WCAG 2.2? 

    WCAG 2.2 adds more consideration to its framework for mobile devices and form factors. Top Hat follows 2.2, because our product supports mobile apps. 

    This isn’t as applicable for educators, so we’re focusing on 2.1 for this guide.

    What are WCAG levels?

    Within each version of WCAG there are “levels” of compliance denoted by A, AA, and AAA. Level AA is where most software vendors and digital services will hang out. 

    There’s no extra credit for meeting AAA. Generally speaking, AA will be a better choice for delivering great learning materials to students. The scuttlebutt on the street (the youth are all aflutter about this) is that AAA is for banks and government institutions.

    Note for Canadians

    Canadians will be expected to adhere to the Accessible Canada Act (ACA). Ontario, British Columbia, and Newfoundland and Labrador have their own laws, too.

    In most cases WCAG 2.1 Level AA will meet the letter of these laws, too.

    This guide follows: WCAG 2.1, Level AA

    This guide follows WCAG 2.1, Level AA standard, and so does Top Hat’s content and platform.

    If your institution uses another level, or something other than WCAG, this guideline may not be useful to you.

    It’s helpful to think of content and software together, but separate

    In addition to ensuring the form and fit of the software you use is up to standard, educators have an obligation to make sure the content and materials of a course are compliant, too.

    • If the software presenting your slides can’t be navigated by a user using assistive technology? That’s a violation. 
    • If the reading order of your slides isn’t correct? Violation. 
    • If you use an image to convey information that doesn’t have alt-text or a long description? Violation (every physics instructor will be hit especially hard by that last one).

    All of it needs to meet WCAG 2.1 AA compliance.

    For your own sanity, it will be helpful to keep both software and content in mind when navigating accessibility.

    Full disclosure: This article is published by Top Hat

    The goal of this article isn’t to woo you into using Top Hat. Top Hat is an ed tech platform that has features to help make educational content accessible, but it’s important to us that this guide will be useful for as many educators as possible.

    Throughout the chapters, where possible, we’ll provide accessible considerations for content both with and without use of the Top Hat platform. As you’ll see in this guide: where content is authored and shared with learners alters the choices you need to make to ensure your stuff works.

    Let’s go!

    Now that the standards are out of the way let’s get into the fun stuff: making your course and materials accessible. 

    Next Chapter: Text Alternatives for Educational Images and Visual Aids

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  • Solving the staffing crisis is key to the Science of Reading movement

    Solving the staffing crisis is key to the Science of Reading movement

    Key points:

    As someone who’s dedicated my career to advancing the Science of Reading movement, I’ve seen firsthand what it takes to help every child become a strong, fluent reader. We’ve made incredible strides in shifting the conversation toward evidence-based instruction, but I know we’re at a critical inflection point. While we–obviously–continue our work helping schools and districts adopt SOR, there’s an issue that stands in the way of real, sustained, progress: the staffing crisis and leadership churn that are leaving our educators overwhelmed and skeptical toward “change.” Without addressing these deeper structural issues, we risk stalling the momentum we’ve worked so hard to build.

    The hidden costs of constant turnover

    The data on teacher and leader turnover is bleak, and I’ve seen how it undermines the long-term commitment needed for any meaningful change. Consider this: Roughly 1 in 6 teachers won’t return to the same classroom next year, and nearly half of new teachers leave within their first five years. This constant churn is a massive financial burden on districts, costing an estimated $20,000 per teacher to recruit, hire, and onboard. But the real cost is the human one. Every time a new leader or teacher steps in, the hard-won progress on a literacy initiative can be jeopardized.

    I’ve watched districts spend years building momentum for the Science of Reading, providing extensive training and resources, only to see a new superintendent or principal arrive with a new set of priorities. This “leader wobble” can pull the rug out from under an initiative mid-stream. It’s especially frustrating when a new leader decides a program has had “plenty of professional learning” without taking the time to audit its impact. This lack of continuity completely disrupts the 3-5 years it takes for an initiative to truly take hold, especially because new teachers often arrive with a knowledge gap, as only about one-quarter of teacher preparation programs teach the Science of Reading. We can’t build on a foundation that’s constantly shifting.

    Overwhelmed by “initiative fatigue”

    I know what it feels like to have too much on your plate. Teachers, already juggling countless instructional materials, often see each new program not as a solution but as one more thing to learn, implement, and manage. Instead of excitement, there’s skepticism–this is initiative fatigue, and it can stall real progress. I’ve seen it firsthand; one large district I worked with rolled out new reading, math, and phonics resources all at once.

    To prevent this, we need to follow the principle of “pull weeds to plant flowers.” Being critical, informed consumers of resources means choosing flowers (materials) that are:

    • Supported by high-quality, third-party research
    • Aligned across all tiers of instruction
    • Versatile enough to meet varied student needs
    • Teacher-friendly, with clear guidance and instructional dialogue
    • Culturally relevant, reflecting the diverse backgrounds of students

    Now, even when a resource meets these standards, adoption shouldn’t be additive. Teachers can’t layer new tools on top of old ones. To see real change, old resources must be replaced with better ones. Educators need solutions that provide a unified, research-backed framework across all tiers, giving teachers clarity, support, and a path to sustainable student progress.

    Building a stable environment for sustained change

    So, how do we create the stable environment needed to support our educators? It starts with leadership that is in it for the long game. We need to mitigate turnover by using data to understand why teachers are leaving and then acting on that feedback. Strengthening mentorship, clarifying career pathways, and improving school culture are all crucial steps.

    Beyond just retaining staff, leaders must foster a culture of sustained commitment. It’s not enough to have a few “islands of excellence” where a handful of teachers are getting great results.

    We need system-wide adoption. This requires strong leaders to balance support and accountability. I’ve seen how collaborative teams, engaged in problem-solving and data-based decision-making, can transform a school. When teachers see students as “our students” and not just “my students,” shared ownership grows.

    A leader’s job is to protect and sustain this vision, making sure the essential supports–like collaborative planning time, ongoing professional development, and in-classroom coaching–are in place. But sustaining change goes beyond daily management; it requires building deep capacity so the work continues even if leadership shifts. This means hiring, training, and retaining strong educators, investing in future leaders, and ensuring committed advocates are part of the implementation team. It also requires creating a detailed, actionable roadmap, with budgets clearly allocated and accountability measures established, so that any initiative isn’t just a short-term priority but a long-term promise. By embedding these structures, leaders can secure continuity, maintain momentum, and ensure that every step forward in literacy translates into lasting gains for students.

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  • High quality learning means developing and upskilling educators on the pedagogy of AI

    High quality learning means developing and upskilling educators on the pedagogy of AI

    There’s been endless discussion about what students do with generative AI tools, and what constitutes legitimate use of AI in assessment, but as the technology continues to improve there’s a whole conversation to be had about what educators do with AI tools.

    We’re using the term “educators” to encompass both the academics leading modules and programmes and the professionals who support, enable and contribute to learning and teaching and student support.

    Realising the potential of the technologies that an institution invests in to support student success requires educators to be willing and able to deploy it in ways that are appropriate for their context. It requires them to be active and creative users of that technology, not simply following a process or showing compliance with a policy.

    So it was a bit worrying when in the course of exploring what effective preparation for digital learning futures could look like for our Capability for change report last year, it was noticeable how concerned digital and education leaders were about the variable digital capabilities of their staff.

    Where technology meets pedagogy

    Inevitably, when it comes to AI, some HE staff are enthusiastic early adopters and innovators; others are more cautious or less confident – and some are highly critical and/or just want it to go away. Some of this is about personal orientation towards particular technologies – there is a lively and important critical debate about how society comes into a relationship with AI technology and the implications for, well, the future of humanity.

    Some of it is about the realities of the pressures that educators are under, and the lack of available time and headspace to engage with developmental activity. As one education leader put it:

    Sometimes staff, they know that they need to change what they’re doing, but they get caught in the academic cycle. So every year it’s back to teaching again, really, really large groups of students; they haven’t had the time to go and think about how to do things differently.

    But there’s also an institutional strategic challenge here about situating AI within the pedagogic environment – recognising that students will not only be using it habitually in their work and learning, but that they will expect to graduate with a level of competence in it in anticipation of using AI in the workplace. There’s an efficiency question about how using AI can reprofile educator working patterns and workflows. Even if the prospect of “freeing up” lots of time might feel a bit remote right now, educators are clearly going to be using AI in interesting ways to make some of their work a bit more efficient, to surface insight from large datasets that might not otherwise be accessible, or as a co-creator to help enhance their thinking and practice.

    In the context of learning and teaching, educators need to be ready to go beyond asking “how do the tools work and what can I do with them?” and be prepared to ask and answer a larger question: “what does it mean for academic quality and pedagogy when I do?”

    As Tom Chatfield has persuasively argued in his recent white paper on AI and the future of pedagogy, AI needs to have a clear educative purpose when it is deployed in learning and teaching, and should be about actively enhancing pedagogy. Reaching this halcyon state requires educators who are not only competent in the technical use of the tools that are available but prepared to work creatively to embed those tools to achieve particular learning objectives within the wider framework and structures of their academic discipline. Expertise of this nature is not cheaply won – it takes time and resource to think, experiment, test, and refine.

    Educators have the power – and responsibility – to work out how best to harness AI in learning and teaching in their disciplines, but education leaders need to create the right environment for innovation to flourish. As one leader put it:

    How do we create an environment where we’re allowing people to feel like they are the arbiters of their own day to day, that they’ve got more time, that they’re able to do the things that they want to do?…So that’s really an excitement for me. I think there’s real opportunity in digital to enable those things.

    Introducing “Educating the AI generation”

    For our new project “Educating the AI generation” we want to explore how institutions are developing educator AI literacy and practice – what frameworks, interventions, and provisions are helpful and effective, and where the barriers and challenges lie. What sort of environment helps educators to develop not just the capability, but also the motivation and opportunity to become skilled and critical users of AI in learning and teaching? And what does that teach us about how the role of educators might change as the higher education learning environment evolves?

    At the discussion session Rachel co-hosted alongside Kortext advisor Janice Kay at the Festival of Higher Education earlier this month there was a strong sense among attendees that educating the AI generation requires universities to take action on multiple fronts simultaneously if they are to keep up with the pace of change in AI technology.

    Achieving this kind of agility means making space for risk-taking, and moving away from compliance-focused language to a more collaborative and exploratory approach, including with students, who are equally finding their feet with AI. For leaders, that could mean offering both reassurance that this approach is welcomed, and fostering spaces in which it can be deployed.

    In a time of such fast-paced change, staying grounded in concepts of what it means to be a professional educator can help manage the potential sense of threat from AI in learning and teaching. Discussions focused on the “how” of effective use of AI, and the ways it can support student learning and educator practice, are always grounded in core knowledge of pedagogy and education.

    On AI in assessment, it was instructive to hear student participants share a desire to be able to demonstrate learning and skills above and beyond what is captured in traditional assessment, and find different, authentic ways to engage with knowledge. Assessment is always a bit of a flashpoint in pedagogy, especially in constructing students’ understanding of their learning, and there is an open question on how AI technology can support educators in assessment design and execution. More prosaically, the risks to traditional assessment from large language models indicate that staff may need to spend proportionally more of their time on managing assessment going forward.

    Participants drew upon the experiences of the Covid pivot to emergency remote teaching and taking the best lessons from trialling new ways of learning and teaching as a useful reminder that the sector can pivot quickly – and well – when required. Yet the feeling that AI is often something of a “talking point” rather than an “action point” led some to suggest that there may not yet be a sufficiently pressing sense of urgency to kickstart change in practice.

    What is clear about the present moment is that the sector will make the most progress on these questions when there is sharing of thinking and practice and co-development of approaches. Over the next six months we’ll be building up our insight and we’d love to hear your views on what works to support educator development of AI in pedagogy. We’re not expecting any silver bullets, but if you have an example of practice to share, please get in touch.

    This article is published in association with Kortext. Join Debbie, Rachel and a host of other speakers at Kortext LIVE on Wednesday 11 February in London, where we’ll be discussing some of our findings – find out more and book your place here.

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  • Why empowering students sets the best course for future success

    Why empowering students sets the best course for future success

    Key points:

    When middle school students make the leap to high school, they are expected to have a career path in mind so their classes and goals align with their future plans. That’s a tremendous ask of a teenager who is unaware of the opportunities that await them–and emerging careers that have yet to exist.

    Mentors, parents, and educators spend so much time urging students to focus on their future that we do them a disservice by distracting them from their present–their passions, their interests, their hobbies. This self-discovery, combined with exposure to various career fields, fuels students’ motivation and serves as a guidebook for their professional journey.

    To meet their mission of directing every student toward an individualized post-secondary plan, schools need to prioritize recognizing each student’s lifestyle goals. That way, our kids can find their best-fit career and develop greater self-awareness of their own identity.

    Give students greater autonomy over their career exploration

    The most problematic aspect of traditional career-readiness programs is that they’re bound so tightly to the classes in which a student excels.

    For example, a high schooler on a technology track might be assigned an engineer as a mentor. However, that same student may also possess a love for writing, but because their core classes are science-based, they may never learn how to turn that passion into a career in the engineering field, whether as a UX writer, technical editor, or tech journalist. 

    Schools have the opportunity to help students identify their desired lifestyle, existing strengths, and possible career paths. In Aurora Public Schools in Nebraska, the district partnered with our company, Find Your Grind, an ESSA Tier 2 validated career exploration program, to guide students through a Lifestyle Assessment, enabling them to discover who they are now and who they want to become. Through this approach, teachers helped surface personalized careers, mentors, and pathway courses that aligned with students’ lifestyle goals.

    Meanwhile, in Ohio, school districts launched Lifestyle Fairs, immersive, future-ready events designed to introduce students to real-world career experiences, industry mentors, and interactive learning grounded in self-discovery. Hilliard City Schools, for example, welcomed more than seventh-grade students to a Lifestyle Fair this past May

    Rather than rely on a conventional booth-style setup, Hilliard offered interactive activations that centered on 16 lifestyle archetypes, including Competitor, Explorer, Connector, and Entrepreneur. The stations allowed students to engage with various industry leaders and participate in hands-on activities, including rocket launch simulations and creative design challenges, to ignite their curiosity. Following the Fair, educators reported increased student engagement and a renewed enthusiasm for learning about potential career paths.

    Create a fluidity path for future success

    According to the World Economic Forum, by 2030, 97 million jobs will be displaced by AI, significantly impacting lower-wage earners and workers of color. At the same time, 170 million new jobs are expected to be created, especially in emerging fields. By providing students more freedom in their career exploration, educators can help them adapt to this ever-changing 21st-century job market.

    Now is the time for school districts to ensure all students have access to equitable career planning programs and work to close societal disparities that hinder professional opportunities. Instead of setting students on a predetermined pathway toward a particular field–which may or may not exist a decade from now–educators must equip them with future-proof and transferable core skills, including flexibility, initiative, and productivity, in addition to job-specific skills. As the job market shifts, students will be prepared to change direction, switch jobs, and pivot between careers. 

    In Hawaii, students are taking advantage of career exploration curriculum that aligns with 21st-century career and technical education (CTE) frameworks. They are better prepared to complete their Personal Transition Plans, which are required for graduation by the state, and have access to micro-credentials that give them real-world experience in different industries rather than one particular field.

    For decades, career planning has placed students in boxes, based on what the adults in their lives expect of them. Ensuring every child reaches their full professional potential means breaking down the barriers that have been set up around them and allowing them to be at the center of their own career journey. When students are empowered to discover who they are and where they want to be, they are excited to explore all the incredible opportunities available to them. 

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  • Preparing for a new era of teaching and learning

    Preparing for a new era of teaching and learning

    Key points:

    When I first started experimenting with AI in my classroom, I saw the same thing repeatedly from students. They treated it like Google. Ask a question, get an answer, move on. It didn’t take long to realize that if my students only engage with AI this way, they miss the bigger opportunity to use AI as a partner in thinking. AI isn’t a magic answer machine. It’s a tool for creativity and problem-solving. The challenge for us as educators is to rethink how we prepare students for the world they’re entering and to use AI with curiosity and fidelity.

    Moving from curiosity to fluency

    In my district, I wear two hats: history teacher and instructional coach. That combination gives me the space to test ideas in the classroom and support colleagues as they try new tools. What I’ve learned is that AI fluency requires far more than knowing how to log into a platform. Students need to learn how to question outputs, verify information and use results as a springboard for deeper inquiry.

    I often remind them, “You never trust your source. You always verify and compare.” If students accept every AI response at face value, they’re not building the critical habits they’ll need in college or in the workforce.

    To make this concrete, I teach my students the RISEN framework: Role, Instructions, Steps, Examples, Narrowing. It helps them craft better prompts and think about the kind of response they want. Instead of typing “explain photosynthesis,” they might ask, “Act as a biologist explaining photosynthesis to a tenth grader. Use three steps with an analogy, then provide a short quiz at the end.” Suddenly, the interaction becomes purposeful, structured and reflective of real learning.

    AI as a catalyst for equity and personalization

    Growing up, I was lucky. My mom was college educated and sat with me to go over almost every paper I wrote. She gave me feedback that helped to sharpen my writing and build my confidence. Many of my students don’t have that luxury. For these learners, AI can be the academic coach they might not otherwise have.

    That doesn’t mean AI replaces human connection. Nothing can. But it can provide feedback, ask guiding questions, and provide examples that give students a sounding board and thought partner. It’s one more way to move closer to providing personalized support for learners based on need.

    Of course, equity cuts both ways. If only some students have access to AI or if we use it without considering its bias, we risk widening the very gaps we hope to close. That’s why it’s our job as educators to model ethical and critical use, not just the mechanics.

    Shifting how we assess learning

    One of the biggest shifts I’ve made is rethinking how I assess students. If I only grade the final product, I’m essentially inviting them to use AI as a shortcut. Instead, I focus on the process: How did they engage with the tool? How did they verify and cross-reference results? How did they revise their work based on what they learned? What framework guided their inquiry? In this way, AI becomes part of their learning journey rather than just an endpoint.

    I’ve asked students to run the same question through multiple AI platforms and then compare the outputs. What were the differences? Which response feels most accurate or useful? What assumptions might be at play? These conversations push students to defend their thinking and use AI critically, not passively.

    Navigating privacy and policy

    Another responsibility we carry as educators is protecting our students. Data privacy is a serious concern. In my school, we use a “walled garden” version of AI so that student data doesn’t get used for training. Even with those safeguards in place, I remind colleagues never to enter identifiable student information into a tool.

    Policies will continue to evolve, but for day-to-day activities and planning, teachers need to model caution and responsibility. Students are taking our lead.

    Professional growth for a changing profession

    The truth of the matter is most of us have not been professionally trained to do this. My teacher preparation program certainly did not include modules on prompt engineering or data ethics. That means professional development in this space is a must.

    I’ve grown the most in my AI fluency by working alongside other educators who are experimenting, sharing stories, and comparing notes. AI is moving fast. No one has all the answers. But we can build confidence together by trying, reflecting, and adjusting through shared experience and lessons learned. That’s exactly what we’re doing in the Lead for Learners network. It’s a space where educators from across the country connect, learn and support one another in navigating change.

    For educators who feel hesitant, I’d say this: You don’t need to be an expert to start. Pick one tool, test it in one lesson, and talk openly with your students about what you’re learning. They’ll respect your honesty and join you in the process.

    Preparing students for what’s next

    AI is not going away. Whether we’re ready or not, it’s going to shape how our students live and work. That gives us a responsibility not just to keep pace with technology but to prepare young people for what’s ahead. The latest futures forecast reminds us that imagining possibilities is just as important as responding to immediate shifts.

    We need to understand both how AI is already reshaping education delivery and how new waves of change will remain on the horizon as tools grow more sophisticated and widespread.

    I want my students to leave my classroom with the ability to question, create, and collaborate using AI. I want them to see it not as a shortcut but as a tool for thinking more deeply and expressing themselves more fully. And I want them to watch me modeling those same habits: curiosity, caution, creativity, and ethical decision-making. Because if we don’t show them what responsible use looks like, who will?

    The future of education won’t be defined by whether we allow AI into our classrooms. It will be defined by how we teach with it, how we teach about it, and how we prepare our students to thrive in a world where it’s everywhere.

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  • How tutors can support student thinking

    How tutors can support student thinking

    Key points:

    Consider the work of a personal trainer. They can explain and model a workout perfectly, but if the athlete isn’t the one doing the lifting, their muscles won’t grow. The same is true for student learning. If students only copy notes or nod along, their cognitive muscles won’t develop. Cognitive lift is the mental work students do to understand, apply, and explain academic content. It’s not about giving students harder problems or letting them struggle alone. It’s about creating space for them to reason and stretch their thinking.

    Research consistently shows that students learn more when they are actively engaged with the material, rather than passively observe. Learners often forget what they’ve “learned” if they only hear an explanation. That’s why great tutors don’t just explain material clearly–they get students to explain it clearly. 

    Tutoring, with its small group format, is the ideal space to encourage students’ cognitive lift. While direct instruction and clear explanations are essential at the right times in the learning process, tutorials offer a powerful opportunity for students to engage deeply and productively practice with support.

    The unique power of tutorials

    Small-group tutorials create conditions that are harder to foster in a full classroom. Having just a few students, tutors can track individual student thinking and adjust support quickly. Students gain more chances to voice reasoning, test ideas, and build confidence. Tutorials rely on strong relationships, and when students trust their tutor, they’re more willing to take risks, share half-formed thoughts, and learn from mistakes. 

    It’s easier to build space for every student to participate and shine in a tutorial than in a full class. Tutors can pivot when they notice students aren’t actively thinking. They may notice they’re overexplaining and can step back, shifting the cognitive responsibility back to the students. This environment gives each learner the opportunity to thrive through cognitive lift.

    What does cognitive lift look like?

    What does cognitive lift look like in practice? Picture two tutorials where students solve equations like they did in class. In the first, the tutor explains every step, pausing only to ask quick calculations like, “What’s 5 + 3?” The student might answer correctly, but solving isolated computations doesn’t mean they’re engaged with solving the equation.

    Now imagine a second tutorial. The tutor begins with, “Based on what you saw in class, where could we start?” The student tries a strategy, gets stuck, and the tutor follows up: “Why didn’t that work? What else could you try?” The student explains their reasoning, reflects on mistakes, and revises. Here, they do the mental heavy lifting–reaching a solution and building confidence in their ability to reason through challenges.

    The difference is the heart of cognitive lift. When tutors focus on students applying knowledge and explaining thinking, they foster longer-term learning. 

    Small shifts, big impact

    Building cognitive lift doesn’t require a complete overhaul. It comes from small shifts tutors can make in every session. The most powerful is moving from explaining to asking. Instead of “Let me show you,” tutors can try “How might we approach this?” or “What do you notice?” Tutoring using questions over explanations causes students to do more work and learn more.

    Scaffolds–temporary supports that help students access new learning–can support student thinking without taking over. Sentence stems and visuals guide thinking while keeping responsibility with the student. Simple moves like pausing for several seconds after questions (which tutors can count in their heads) and letting students discuss with a partner also create space for reasoning. 

    This can feel uncomfortable for tutors–resisting the urge to “rescue ” students too quickly can be emotionally challenging. But allowing students to wrestle with ideas while still feeling supported is where great learning happens and is the essence of cognitive lift.

    The goal of tutoring

    Tutors aren’t there to make learning easy–they’re there to create opportunities for students to think and build confidence in facing new challenges. Just like a personal trainer doesn’t lift the weights, tutors shouldn’t do the mental work for students. As athletes progress, they add weight and complete harder workouts. Their muscles strengthen as their trainer encourages them to persist through the effort. In the same way, as the academic work becomes more complex, students strengthen their abilities by wrestling with the challenge while tutors coach, encourage, and cheer.

    Success in a tutorial isn’t measured by quick answers, but by the thinking students practice. Cognitive lift builds independence, deepens understanding, and boosts persistence. It’s also a skill tutors develop, and with the right structures, even novices can foster it. Imagine tutorials where every learner has space to reason, take risks, and grow. When we let students do the thinking, we not only strengthen their skills, we show them we believe in their potential.

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  • How Educators Seek to Shape AI Use in Classrooms

    How Educators Seek to Shape AI Use in Classrooms

    For educators, using artificial intelligence in the classroom only makes sense if they have a real say in its development.

    Building on expert experience

    This summer, the American Federation of Teachers and its New York City affiliate, the United Federation of Teachers, announced a $23 million partnership with Microsoft, OpenAI, and Anthropic to establish a first-of-its-kind teacher institute for artificial intelligence: the National Academy for AI Instruction.

    “Technology is routinely weaponized against us,” said UFT President Michael Mulgrew. “We were not going to sit by and watch that happen again. This initiative allows us to take control of AI in the education sphere and develop it for and by educators.”

    While the physical plant will take 12–18 months to build, the academy has already started hosting its first series of AI workshops, introducing attendees to tools to help teachers plan, manage their workload, and meet student needs more effectively. Teachers received guidance on writing AI prompts and discussed ethics and the responsible use of AI. 

    “The academy is saying to teachers: You bring expertise to the classroom. You bring high-value pedagogy to the classroom,” said Rob Weil, Chief Executive Officer of the Academy. “We want you to use that pedagogy and expand that pedagogy, and there are resources you can use to make your expertise better. This is not about replacing your expertise; it’s about expanding your expertise.”

    AI use influenced by teachers

    Workshops this fall will engage educators in 200 New York City schools and then extend to educators in AFT union affiliates across the country. Organizers said the content will deepen as educators gain experience. And while supporting the exploration of AI, the AFT and the UFT were clear that neither organization endorsed specific AI tools or platforms.

    Iolani Grullon, a teacher at P.S. 4 in Manhattan who attended two sets of AI workshops this summer, said AI could be “a game changer” for educators. 

    “This is where things are going,” Grullon said. “If we resist, we’re only going to make our lives harder. We need to be part of the conversation, learn how to use these tools, and influence their next iteration. We are the voice of the classroom. We know what educators and students need. And if these tools can streamline planning and paperwork, it allows for more time to build relationships with students.”

    “It does not replace the human component,” Grullon said. “You need to see my face. You need to hear me say, ‘Great job!’ or ‘Let’s try this again’ or ‘Are you OK?’”

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