Category: IT

  • The 3 learning advantages of 3D printing

    The 3 learning advantages of 3D printing

    Key points:

    It’s truly incredible how much new technology has made its way into the classroom. Where once teaching consisted primarily of whiteboards and textbooks, you can now find tablets, smart screens, AI assistants, and a trove of learning apps designed to foster inquiry and maximize student growth.

    While these new tools are certainly helpful, the flood of options means that educators can struggle to discern truly useful resources from one-time gimmicks. As a result, some of the best tools for sparking curiosity, creativity, and critical thinking often go overlooked.

    Personally, I believe 3D printing is one such tool that doesn’t get nearly enough consideration for the way it transforms a classroom.

    3D printing is the process of making a physical object from a three-dimensional digital model, typically by laying down many thin layers of material using a specialized printer. Using 3D printing, a teacher could make a model of a fossil to share with students, trophies for inter-class competitions, or even supplies for construction activities.

    At first glance, this might not seem all that revolutionary. However, 3D printing offers three distinct educational advantages that have the potential to transform K–12 learning:

    1. It develops success skills: 3D printing encourages students to build a variety of success skills that prepare them for challenges outside the classroom. For starters, its inclusion creates opportunities for students to practice communication, collaboration, and other social-emotional skills. The process of moving from an idea to a physical, printed prototype fosters perseverance and creativity. Meanwhile, every print–regardless of its success–builds perseverance and problem-solving confidence. This is the type of hands-on, inquiry-based learning that students remember.
    2. It creates cross-curricular connections: 3D printing is intrinsically cross-curricular. Professional scientists, engineers, and technicians often use 3D printing to create product models or build prototypes for testing their hypotheses. This process involves documentation, symbolism, color theory, understanding of narrative, and countless other disciplines. It doesn’t take much imagination to see how these could also be beneficial to classroom learning. Students can observe for themselves how subjects connect, while teachers transform abstract concepts into tangible points of understanding.     
    3. It’s aligned with engineering and NGSS: 3D printing aligns perfectly with Next Gen Science Standards. By focusing on the engineering design process (define, imagine, plan, create, improve) students learn to think and act like real scientists to overcome obstacles. This approach also emphasizes iteration and evidence-based conclusions. What better way to facilitate student engagement, hands-on inquiry, and creative expression?

    3D printing might not be the flashiest educational tool, but its potential is undeniable. This flexible resource can give students something tangible to work with while sparking wonder and pushing them to explore new horizons.

    So, take a moment to familiarize yourself with the technology. Maybe try running a few experiments of your own. When used with purpose, 3D printing transforms from a common classroom tool into a launchpad for student discovery.

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  • Why K-12 educators need data literacy, not just data

    Why K-12 educators need data literacy, not just data

    Key points:

    Walk into any data meeting at a K-12 school today, and you’ll likely see a familiar scene: educators huddled around printed reports, highlighters in hand, trying to make sense of student data spread across multiple dashboards. If you’ve ever left one of these meetings feeling mentally exhausted without clear next steps, you’re not alone. The problem isn’t that we lack data in education, but rather that most dashboards show us the past–not the path ahead. It’s like trying to drive while only looking in the rearview mirror.

    The education sector sits on massive amounts of student data, yet most schools lack data maturity. They’ve committed to using data and may even have systems that centralize records. But they haven’t embraced what’s possible when we move from having data to using it well; from describing what happened to predicting what’s likely to happen if nothing changes.

    We have dashboards–now what?

    Every district has dashboards. We can see attendance rates, assessment scores, and demographic breakdowns. These tools tell us what happened, which is useful–but increasingly insufficient for the challenges facing K-12 schools. By the time we’re reacting to chronic absenteeism or declining grades, we’re already behind. And, when does an educator have time to sit down, pull up multiple dashboards, and interpret what they say about each student?

    The power of any data dashboard isn’t in the dashboard itself. It’s in the conversations that happen around it. This is where data literacy becomes essential, and it goes far beyond simply reading a chart or calculating an average.

    Data literacy means asking better questions and approaching data with curiosity. It requires recognizing that the answers we get are entirely driven by the questions we ask. A teacher who asks, “Which students failed the last assessment?” will get very different insights than one who asks, “Which students showed growth but still haven’t reached proficiency, and what patterns exist among them?”

    We must also acknowledge the emotional dimension of data in schools. Some educators have been burned when data was used punitively instead of for improvement. That resistance is understandable, but not sustainable. The solution isn’t to check professional expertise at the door. It’s to approach data with both curiosity and courage, questioning it in healthy ways while embracing it as a tool for problem-solving.

    From descriptive to predictive: What’s possible

    Let’s distinguish between types of analytics. Descriptive analytics tell us what happened: Jorge was absent 15 days last semester. Diagnostic analytics tell us why: Jorge lives in a household without reliable transportation, and his absences cluster on Mondays and Fridays.

    Now we get to the game-changers: predictive and prescriptive analytics. Predictive analytics use historical patterns to forecast what’s likely to happen: Based on current trends, Jorge is at 80 percent risk of chronic absenteeism by year’s end. Prescriptive analytics go further by helping the educator understand what they should do to intervene. If we connect Jorge’s family with transportation support and assign a mentor for weekly check-ins, we can likely reduce his absence risk by 60 percent.

    The technology to do this already exists. Machine learning can identify patterns across thousands of student records that would take humans months to discern. AI can surface early warning signs before problems become crises. These tools amplify teacher judgment, serving up insights and allowing educators to focus their expertise where it matters most.

    The cultural shift required

    Before any school rushes to adopt the next analytics tool, it’s worth pausing to ask: What actually happens when someone uses data in their daily work?

    Data use is deeply human. It’s about noticing patterns, interpreting meaning, and deciding what to do next. That process looks different for every educator, and it’s shaped by the environment in which they work: how much time they have to meet with colleagues, how easily they can access the right data, and whether the culture encourages curiosity or compliance.

    Technology can surface patterns, but culture determines whether those patterns lead to action. The same dashboard can spark collaboration in one school and defensiveness in another. That’s why new tools require attention to governance, trust, and professional learning–not just software configuration.

    At the end of the day, the goal isn’t simply to use data more often, but to use it more effectively.

    Moving toward this future requires a fundamental shift in how we think about data: from a compliance exercise to a strategic asset. The most resilient schools in the coming years will have cultures where data is pervasive, shared transparently, and accessible in near real-time to the people who need it. Think of it as an instructional co-pilot rather than a monkey on the back.

    This means moving away from data locked in the central office, requiring a 10-step approval process to access. Instead, imagine a decentralized approach where a fifth-grade team can instantly generate insights about their students’ reading growth, or where a high school counselor can identify seniors at risk of not graduating with enough time to intervene.

    This kind of data democratization requires significant change management. It demands training, clear protocols, and trust. But the payoff is educators empowered to make daily decisions grounded in timely, relevant information.

    Turning data into wisdom

    Data has been part of education from the very beginning. Attendance records, report cards, and gradebooks have always informed teaching. What’s different now is the volume of data available and the sophistication of tools to analyze it. K-12 educators don’t need to become data scientists, but they do need to become data literate: curious, critical consumers of information who can ask powerful questions and interpret results within the rich context of their professional expertise.

    The schools that harness their data effectively will be able to identify struggling students earlier, personalize interventions more effectively, and use educator time more strategically. But this future requires us to move beyond the dashboard and invest in the human capacity to transform data into wisdom. That transformation starts with data literacy, and it starts now.

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  • We built evaluation for accountability–now it’s time to build it for growth

    We built evaluation for accountability–now it’s time to build it for growth

    Key points:

    Teacher evaluations have been the subject of debate for decades. Breakthroughs have been attempted, but rarely sustained. Researchers have learned that context, transparency, and autonomy matter. What’s been missing is technology that enhances these at scale inside the evaluation process–not around it. 

    As an edtech executive in the AI era, I see exciting possibilities to bring new technology to bear on these factors in the longstanding dilemma of observing and rating teacher effectiveness.

    At the most fundamental level, the goals are simple, just as they are in other professions: provide accountability, celebrate areas of strong performance, and identify where improvement is needed. However, K-12 education is a uniquely visible and important industry. Between 2000 and 2015, quality control in K-12 education became more complex, with states, foundations, and federal policy all shaping the definition and measurement of a “proficient” teacher. 

    For instance, today’s observation cycle might include pre- and post-observation conferences plus scheduled and unscheduled classroom visits. Due to the potential for bias in personal observation, more weight has been given to student achievement, but after critics highlighted problems with measuring teacher performance via standardized test scores, additional metrics and artifacts were included as well.

    All of these changes have resulted in administrators spending more time on observation and evaluation, followed by copying notes between systems and drafting comments–rather than on timely, specific feedback that actually changes practice. “Even when I use Gemini or ChatGPT, I still spend 45 minutes rewriting to fit the district rubric,” one administrator noted.

    “When I think about the evaluation landscape, two challenges rise to the surface,” said Dr. Quintin Shepherd, superintendent at Pflugerville Independent School District in Texas. “The first is the overwhelming volume of information evaluators must gather, interpret, and synthesize. The second is the persistent perception among teachers that evaluation is something being done to them rather than something being done for them. Both challenges point in the same direction: the need for a resource that gives evaluators more capacity and teachers more clarity, immediacy, and ownership. This is where AI becomes essential.”

    What’s at stake

    School leaders are under tremendous pressure. Time and resources are tight. Achieving benchmarks is non-negotiable. There’s plenty of data available to identify patterns and understand what’s working–but analyzing it is not easy when the data is housed in multiple platforms that may not interface with one another. Generic AI tools haven’t solved this.  

    For teachers, professional development opportunities abound, and student data is readily available. But often they don’t receive adequate instructional mentoring to ideate and try out new strategies. 

    Districts that have experimented with AI to provide automated feedback of transcribed recordings of instruction have found limited impact on teaching practices. Teachers report skepticism that the evolving tech tools are able to accurately assess what is happening in their classrooms. Recent randomized controlled trials show that automated feedback can move specific practices when teachers engage with it. But that’s exactly the challenge: Engagement is optional. Evaluations are not. 

    Teachers whose observations and evaluations are compromised or whose growth is stymied by lost opportunities for mentoring may lose out financially. For example, in Texas, the 2025-26 school year is the data capture period for the Teacher Incentive Allotment. This means fair and objective reviews are more important than ever for educators’ future earning potential.

    For all of these reasons, the next wave of innovation has to live inside the required evaluation cycle, not off to the side as another “nice-to-have” tool.

    Streamlining the process

    My background at edtech companies has shown me how eager school leaders are to make data-informed decisions. But I know from countless conversations with administrators that they did not enter the education field to crunch numbers. They are motivated by seeing students thrive. 

    The breakthrough we need now is an AI-powered workspace that sits inside the evaluation system. Shepherd would like to see “AI that quietly assists with continuous evidence collection not through surveillance, but pattern recognition. It might analyze lesson materials for cognitive rigor, scan student work products to detect growth, or help teachers tag artifacts connected to standards.”

    We have the technology to create a collaborative workspace that can be mapped to the district’s framework and used by administrators, coaches, support teams, and educators to capture notes from observations, link them to goals, provide guidance, share lesson artifacts, engage in feedback discussions, and track growth across cycles. After participating in a pilot of one such collaborative workspace, an evaluator said that “for the first time, I wasn’t rewriting my notes to make them fit the rubric. The system kept the feedback clear and instructional instead of just compliance-based.”

    As a superintendent, Shepherd looks forward to AI support for helping make sense of complexity. “Evaluators juggle enormous qualitative loads: classroom culture, student engagement, instructional clarity, differentiation, formative assessment, and more. AI can act as a thinking partner, organizing trends, highlighting possible connections, identifying where to probe deeper, or offering research-based framing for feedback.”

    The evaluation process will always be scrutinized, but what must change is whether it continues to drain time and trust or becomes a catalyst for better teaching. Shepherd expects the pace of adoption to pick up speed as the benefits for educators become clear: “Teachers will have access to immediate feedback loops and tools that help them analyze student work, reconsider lesson structures, or reflect on pacing and questioning. This strengthens professional agency and shifts evaluation from a compliance ritual to a growth process.”

    Real leadership means moving beyond outdated processes and redesigning evaluation to center evidence, clarity, and authentic feedback. When evaluation stops being something to get through and becomes something that improves practice, we will finally see technology drive better teaching and learning.

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  • 25 predictions about AI and edtech

    25 predictions about AI and edtech

    eSchool News is counting down the 10 most-read stories of 2025. Story #2 focuses on predictions educators made for AI in 2025.

    When it comes to education trends, AI certainly has staying power. As generative AI technologies evolve, educators are moving away from fears about AI-enabled cheating and are embracing the idea that AI can open new doors for teaching and learning.

    AI tools can reduce the administrative burden so many educators carry, can personalize learning for students, and can help students become more engaged in their learning when they use the tools to brainstorm and expand on ideas for assignments and projects. Having AI skills is also essential for today’s students, who will enter a workforce where AI know-how is becoming more necessary for success.

    So: What’s next for AI in education? We asked educators, edtech industry leaders, stakeholders, and experts to share some predictions about where they think AI is headed in 2025. (Here’s our list of 50 predictions for edtech in 2025.)

    Here’s what they had to say:

    In 2025, online program leaders will begin to unlock the vast potential of generative AI, integrating it more deeply into the instructional design process in ways that can amplify and expedite the work of faculty and instructional designers. This technology, already making waves in instruction and assessment, stands poised to transform the creation of online courses. By streamlining time-intensive tasks, generative AI offers the promise of automation, replication, and scalability, enabling institutions to expand their online offerings at an unprecedented pace. The key is that we maintain rigorous standards of quality–and create clear guardrails around the ethical use of AI at a time when increasingly sophisticated models are blurring the lines between human design–and artificial intelligence. Generative AI holds extraordinary promise, but its adoption must be grounded in practices that prioritize equitable and inclusive access, transparency, and educational excellence.
    –Deb Adair, CEO, Quality Matters

    In 2025, education in the United States will reflect both the challenges and opportunities of a system in transition. Uncertainty and change at the federal level will continue to shift decision-making power to states, leaving them with greater autonomy but also greater responsibility. While this decentralization may spark localized innovation, it is just as likely to create uneven standards. In some states, we’ve already seen benchmarks lowered to normalize declines, a trend that could spread as states grapple with resource and performance issues. This dynamic will place an even greater burden on schools, teachers, and academic leaders. As those closest to learners, they will bear the responsibility of bridging the gap between systemic challenges and individual student success. To do so effectively, schools will require tools that reduce administrative complexity, enabling educators to focus on fostering personal connections with students–the foundation of meaningful academic growth. AI will play a transformative role in this landscape, offering solutions to these pressures. However, fragmented adoption driven by decentralized decision-making will lead to inequities, with some districts leveraging AI effectively and others struggling to integrate it. In this complex environment, enterprise platforms that offer flexibility, integration, and choice will become essential. 2025 will demand resilience and creativity, but it also offers all of us an opportunity to refocus on what truly matters: supporting educators and the students they inspire.
    —Scott Anderberg, CEO, Moodle

    As chatbots become more sophisticated, they’re rapidly becoming a favorite among students for their interactive and personalized support, and we can expect to see them increasingly integrated into classrooms, tutoring platforms, and educational apps as educators embrace this engaging tool for learning. Additionally, AI is poised to play an even larger role in education, particularly in test preparation and course planning. By leveraging data and predictive analytics, AI-driven tools will help students and educators create more tailored and effective learning pathways, enhancing the overall educational experience.
    —Brad Barton, CTO, YouScience 

    As we move into 2025,  we’ll move past the AI hype cycle and pivot toward solving tangible classroom challenges. Effective AI solutions will integrate seamlessly into the learning environment, enhancing rather than disrupting the teaching experience. The focus will shift to practical tools that help teachers sustain student attention and engagement–the foundation of effective learning. These innovations will prioritize giving educators greater flexibility and control, allowing them to move freely around the classroom while effortlessly managing and switching between digital resources. An approach that ensures technology supports and amplifies the irreplaceable human connections at the heart of learning, rather than replacing them.
    –Levi Belnap, CEO, Merlyn Mind

    The year 2025 is set to transform science education by implementing AI-driven learning platforms. These platforms will dynamically adjust to the student’s interests and learning paces, enhancing accessibility and inclusivity in education. Additionally, virtual labs and simulations will rise, enabling students to experiment with concepts without geographical constraints. This evolution will make high-quality STEM education more universally accessible.
    –Tiago Costa, Cloud & AI Architect, Microsoft; Pearson Video Lesson Instructor 

    In the two years since GenAI was unleashed, K-12 leaders have ridden the wave of experimentation and uncertainty about the role this transformative technology should have in classrooms and districts. 2025 will see a shift toward GenAI strategy development, clear policy and governance creation, instructional integration, and guardrail setting for educators and students. K-12 districts recognize the need to upskill their teachers, not only to take advantage of GenAI to personalize learning, but also so they can teach students how to use this tech responsibly. On the back end, IT leaders will grapple with increased infrastructure demands and ever-increasing cybersecurity threats.
    —Delia DeCourcy, Senior Strategist, Lenovo Worldwide Education Team

    AI-driven tools will transform the role of teachers and support staff in 2025: The advent of AI will allow teachers to offload mundane administrative tasks to students and provide them more energy to be at the “heart and soul” of the classroom. Moreover, more than two-thirds (64 percent) of parents agreed or strongly agreed that AI should help free teachers from administrative tasks and help them build connections with the classroom. Impact of technological advancements on hybrid and remote learning models in 2025: AI is revolutionizing the online learning experience with personalized pathways, tailored skills development and support, and enhanced content creation. For example, some HBS Online courses, like Launching Tech Ventures, feature an AI course assistant bot to help address learners’ questions and facilitate successful course completion. While the long-term impact remains uncertain, AI is narrowing the gap between online and in-person education. By analyzing user behavior and learning preferences, AI can create adaptive learning environments that dynamically adjust to individual needs, making education more engaging and effective. 
    –David Everson, Senior Director of Marketing Solutions, Laserfiche

    In education and digital publishing, artificial intelligence (AI) will continue transitioning from novelty applications to solutions that address real-world challenges facing educators and students. Successful companies will focus on data security and user trust, and will create learner-centered AI tools to deliver personalized experiences that adapt to individual needs and enhance efficiency for educators, enabling them to dedicate more time to fostering meaningful connections with students. The ethical integration of AI technologies such as retrieval-augmented generation (RAG) is key to this evolution. Unlike traditional large language models that ingest information from the Internet at large, RAG delivers AI outputs that are grounded in authoritative, peer-reviewed content, reducing the risk of misinformation while safeguarding the integrity of intellectual property. Thoughtfully developed AI tools such as this will become partners in the learning journey, encouraging analysis, problem-solving, and creativity rather than fostering dependence on automated responses. By taking a deliberate approach that focuses on ethical practices, user-centered design, and supporting the cultivation of essential skills, successful education companies will use AI less as innovation for its own sake and more as a means to provide rich and memorable teaching and learning experiences.
    —Paul Gazzolo, Senior Vice President & Global General Manager, Gale, a Part of Cengage Group

    Adaptive learning technologies will continue to personalize curriculum and assessment, creating a more responsive and engaging educational journey that reflects each student’s strengths and growth areas. Generative AI and other cutting-edge advancements will be instrumental in building solutions that optimize classroom support, particularly in integrating assessment and instruction. We will see more technology that can help educators understand the past to edit materials in the present, to accelerate teachers planning for the future.
    —Andrew Goldman, EVP, HMH Labs

    We’ll witness a fundamental shift in how we approach student assessment, moving away from conventional testing models toward more authentic experiences that are seamless with instruction. The thoughtful integration of AI, particularly voice AI technology, will transform assessment from an intermittent event into a natural part of the learning process. The most promising applications will be those that combine advanced technology with research-validated methodologies. Voice-enabled assessments will open new possibilities for measuring student knowledge in ways that are more natural and accessible, especially for our youngest learners, leveraging AI’s capabilities to streamline assessment while ensuring that technology serves as a tool to augment, rather than replace, the critical role of teachers.
    –Kristen Huff, Head of Measurement, Curriculum Associates

    AI is already being used by many educators, not just to gain efficiencies, but to make a real difference in how their students are learning. I suspect in 2025 we’ll see even more educators experimenting and leveraging AI tools as they evolve–especially as more of the Gen Z population enters the teaching workforce. In 2024, surveyed K-12 educators reported already using AI to create personalized learning experiences, provide real-time performance feedback, and foster critical thinking skills. Not only will AI usage continue to trend up throughout 2025, I do believe it will reach new heights as more teachers begin to explore GenAI as a hyper-personalized asset to support their work in the classroom. This includes the use of AI as an official teacher’s assistant (TA), helping to score free response homework and tests and providing real-time, individualized feedback to students on their education journey.
    –John Jorgenson, CMO, Cambium Learning Group

    The new year will continue to see the topic of AI dominate the conversation as institutions emphasize the need for students to understand AI fundamentals, ethical considerations, and real-world applications outside of the classroom. However, a widening skills gap between students and educators in AI and digital literacy presents a challenge. Many educators have not prioritized keeping up with rapid technological advancements, while students–often exposed to digital tools early on–adapt quickly. This gap can lead to uneven integration of AI in classrooms, where students sometimes outpace their instructors in understanding. To bridge this divide, comprehensive professional development for teachers is essential, focusing on both technical skills and effective teaching strategies for AI-related topics. Underscoring the evolving tech in classrooms will be the need for evidence of outcomes, not just with AI but all tools. In the post-ESSER era, evidence-based decision-making is crucial for K-12 schools striving to sustain effective programs without federal emergency funds. With the need to further justify expenditures, schools must rely on data to evaluate the impact of educational initiatives on student outcomes, from academic achievement to mental health support. Evidence helps educators and administrators identify which programs truly benefit students, enabling them to allocate resources wisely and prioritize what works. By focusing on measurable results, schools can enhance accountability, build stakeholder trust, and ensure that investments directly contribute to meaningful, lasting improvements in learning and well-being.
    —Melissa Loble, Chief Academic Officer, Instructure

    With AI literacy in the spotlight, lifelong learning will become the new normal. Immediate skills need: The role of “individual contributors” will evolve, and we will all be managers of AI agents, making AI skills a must-have. Skills of the future: Quantum skills will start to be in demand in the job market as quantum development continues to push forward over the next year. Always in-demand skills: The overall increase in cyberattacks and emerging risks, such as harvest now and decrypt later (HNDL) attacks, will further underscore the continued importance of cybersecurity skills. Upskilling won’t end with AI. Each new wave of technology will demand new skills, so lifelong learners will thrive. AI will not be siloed to use among technology professionals. The democratization of AI technology and the proliferation of AI agents have already made AI skills today’s priority. Looking ahead, quantum skills will begin to grow in demand with the steady advance of the technology. Meanwhile cybersecurity skills are an evergreen need.
    —Lydia Logan, VP of Global Education & Workforce Development, IBM

    This coming year, we’ll see real progress in using technology, particularly GenAI, to free up teachers’ time. This will enable them to focus on what they do best: working directly with students and fostering the deep connections crucial for student growth and achievement. GenAI-powered assistants will streamline lesson planning after digesting information from a sea of assessments to provide personalized recommendations for instruction to an entire class, small groups, and individual students. The bottom line is technology that never aims to replace a teacher’s expertise–nothing ever should–but gives them back time to deepen relationships with students.
    —Jack Lynch, CEO, HMH

    Looking to 2025, I anticipate several key trends that will further enhance the fusion of educators, AI and multimodal learning. AI-powered personalization enhanced by multimedia: AI will deliver personalized learning paths enriched with various content formats. By adapting to individual learning styles–whether visual, auditory, or kinesthetic–we can make education more engaging and effective. Expansion of multimodal learning experiences: Students will increasingly expect learning materials that engage multiple senses. Integrating short-form videos created and vetted by actual educators, interactive simulations, and audio content will cater to different learning preferences, making education more inclusive and effective. Deepening collaboration with educators: Teachers will play an even more critical role in developing and curating multimodal content. Their expertise ensures that the integration of technology enhances rather than detracts from the learning experience.
    –Nhon Ma, CEO & Co-founder, Numerade

    AI and automation become a competitive advantage for education platforms and systems. 2025 will be the year for AI to be more infused in education initiatives and platforms. AI-powered solutions have reached a tipping point from being a nice-to-have to a must-have in order to deliver compelling and competitive education experiences. When we look at the education sector, the use cases are clear. From creating content like quizzes, to matching students with education courses that meet their needs, to grading huge volumes of work, enhancing coaching and guidance for students, and even collecting, analyzing and acting on feedback from learners, there is so much value to reap from AI. Looking ahead, there could be additional applications in education for multimodal AI models, which are capable of processing and analyzing complex documents including images, tables, charts, and audio.
    —Rachael Mohammed, Corporate Social Responsibility Digital Offerings Leader, IBM

    Agentic and Shadow AI are here. Now, building guardrails for safe and powerful use will be key for education providers and will require new skillsets. In education, we expect the start of a shift from traditional AI tools to agents. In addition, the mainstream use of AI technology with ChatGPT and OpenAI has increased the potential risk of Shadow AI (the use of non-approved public AI applications, potentially causing concerns about compromising sensitive information). These two phenomena highlight the importance of accountability, data and IT policies, as well as control of autonomous systems. This is key mostly for education providers, where we think there will be greater attention paid to the AI guardrails and process. To be prepared, educators, students, and decision makers at all levels need to be upskilled in AI, with a focus on AI ethics and data management. If we invest in training the workforce now, they will be ready to responsibly develop and use AI and AI agents in a way that is trustworthy.
    —Justina Nixon-Saintil, Vice President & Chief Impact Officer, IBM

    Rather than replacing human expertise, AI can be used as a resource to allow someone to focus more of their time on what’s truly important and impactful. As an educator, AI has become an indispensable tool for creating lesson plans. It helps generate examples, activity ideas, and anticipate future students’ questions, freeing me to focus on the broader framework and the deeper meaning of what I’m teaching.
    –Sinan Ozdemir, Founder & Chief Technology Officer, Shiba Technologies; Author, Quick Start Guide to Large Language Models 

    Data analytics and AI will be essential towards tackling the chronic absenteeism crisis. In 2025, the conversation around belonging will shift from abstract concepts to concrete actions in schools. Teachers who build strong relationships with both students and families will see better attendance and engagement, leading more schools to prioritize meaningful connection-building over quick-fix solutions. We’ll see more districts move toward personalized, two-way school communications that create trust with parents and the larger school community. In order to keep up with the growing need for this type of individualized outreach, schools will use data analytics and AI to identify attendance and academic patterns that indicate students are at risk of becoming chronically absent. It won’t be dramatic, but we’ll see steady progress throughout the year as schools recognize that student success depends on creating environments where both students and families feel valued and heard.
    —Dr. Kara Stern, Director of Education and Engagement, SchoolStatus

    As access to AI resources gains ground in classrooms, educators will face a dire responsibility to not only master these tools but to establish guidelines and provide best practices to ensure effective and responsible use. The increasing demand for AI requires educators to stay informed about emerging applications and prioritize ethical practices, ensuring AI enhances rather than impedes educational outcomes.. This is particularly critical in STEM fields, where AI has already transformed industries and is shaping career paths, providing new learning opportunities for students. To prevent the exacerbation of the existing STEM gap, educators must prioritize equitable access to AI resources and tools, ensuring that all students, regardless of background, have the opportunity to engage with and fully understand these technologies. This focus on equity is essential in leveling the playing field, helping bridge disparities that could otherwise limit students’ future success. Achieving these goals will require educators to engage in professional development programs designed to equip them with necessary skills and content knowledge to implement new technology in their classrooms. Learning how to foster inclusive environments is vital to cultivating a positive school climate where students feel motivated to succeed. Meanwhile, professionally-trained educators can support the integration of new technologies to ensure that every student has the opportunity to thrive in this new educational landscape.
    —Michelle Stie, Vice President, Program Design & Innovation, NMSI

    Artificial intelligence (AI) is poised to increase in use in K-12 classrooms, with literacy instruction emerging as a key area for transformative impact. While educators may associate AI with concerns like cheating, its potential to enhance human-centered teaching is gaining recognition. By streamlining administrative tasks, AI empowers teachers to focus on connecting with students and delivering personalized instruction. One trend to watch is AI’s role in automating reading assessments. These tools reduce the time educators spend administering and analyzing tests, offering real-time insights that guide individualized instruction. AI is also excelling at pinpointing skill gaps, allowing teachers to intervene early, particularly in foundational reading areas.  Another emerging trend is AI-driven reading practice. Tools can adapt to each student’s needs, delivering engaging, personalized reading tutoring with immediate corrective feedback. This ensures consistent, intentional practice–a critical factor in literacy growth. Rather than replacing teachers, AI frees up educator time for what matters most: fostering relationships with students and delivering high-quality instruction. As schools look to optimize resources in the coming year, AI’s ability to augment literacy instruction can be an important tool that maximizes students’ growth, while minimizing teachers’ work.
    —Janine Walker-Caffrey, Ed.D., Chief Academic Officer, EPS Learning

    We expect a renewed focus on human writing with a broader purpose–clear communication that demonstrates knowledge and understanding, enhanced, not replaced by available technology. With AI making basic elements of writing more accessible to all, this renaissance of writing will emphasize the ability to combine topical knowledge, critical thinking, mastery of language and AI applications to develop written work. Instead of being warned against using generative AI, students will be asked to move from demand–asking AI writing tools to produce work on their behalf, to command–owning the content creation process from start to finish and leveraging technology where it can be used to edit, enhance or expand original thinking. This shift will resurface the idea of co-authorship, including transparency around how written work comes together and disclosure of when and how AI tools were used to support the process. 
    —Eric Wang, VP of AI, Turnitin

    GenAI and AI writing detection tools will evolve, adding advanced capabilities to match each other’s detectability flex. End users are reaching higher levels of familiarity and maturity with AI functionality, resulting in a shift in how they are leveraged. Savvy users will take a bookend approach, focusing on early stage ideation, organization and expansion of original ideas as well as late stage refinement of ideas and writing. Coupling the use of GenAI with agentic AI applications will help to overcome current limitations, introducing multi-source analysis and adaptation capabilities to the writing process. Use of detection tools will improve as well, with a focus on preserving the teaching and learning process. In early stages, detection tools and indicator reports will create opportunities to focus teaching on addressing knowledge gaps and areas lacking original thought or foundation. Later stage detection will offer opportunities to strengthen the dialogue between educators and students, providing transparency that will reduce student risk and increase engagement.
    —Eric Wang, VP of AI, Turnitin

    Advanced AI tools will provide more equitable access for all students, inclusive of reaching students in their home language, deaf and hard of hearing support through AI-enabled ASL videos, blind and visually impaired with real time audio descriptions, tactiles, and assistive technology.
    –Trent Workman, SVP for U.S. School Assessments, Pearson 

    Generative AI everywhere: Generative AI, like ChatGPT, is getting smarter and more influential every day, with the market expected to grow a whopping 46 percent every year from now until 2030. By 2025, we’ll likely see AI churning out even more impressive text, images, and videos–completely transforming industries like marketing, design, and content creation. Under a Trump administration that might take a more “hands-off” approach, we could see faster growth with fewer restrictions holding things back. That could mean more innovative tools hitting the market sooner, but it will also require companies to be careful about privacy and job impacts on their own. The threat of AI-powered cyberattacks: Experts think 2025 might be the year cybercriminals go full throttle with AI. Think about it: with the advancement of the technology, cyberattacks powered by AI models could start using deepfakes, enhanced social engineering, and ultra-sophisticated malware. If the Trump administration focuses on cybersecurity mainly for critical infrastructure, private companies could face gaps in support, leaving sectors like healthcare and finance on their own to keep up with new threats. Without stronger regulations, businesses will have to get creative–and fast–when it comes to fighting off these attacks.
    –Alon Yamin, Co-Founder & CEO, Copyleaks

    Laura Ascione
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  • Being a principal just got harder–and here’s why

    Being a principal just got harder–and here’s why

    eSchool News is counting down the 10 most-read stories of 2025. Story #3 focuses on challenges in school leadership.

    This story was originally published by Chalkbeat. Sign up for their newsletters at ckbe.at/newsletters.

    There is a squeaky old merry-go-round in my neighborhood that my own children play on from time to time. Years of kids riding on it have loosened its joints so it spins more freely and quickly. The last time they played on the merry-go-round, my children learned the important lesson that the closer to the center they sit the more stable and in control they feel.

    While being a school leader has always felt like being on a spinning piece of playground equipment, leading since the inauguration of President Donald Trump has made me feel as if I moved from the center to the edges in this merry-go-round metaphor. Immigration raids and attacks on civil liberties have made the work feel blindingly fast.

    The school I serve has a large population of immigrant students. Teens who just weeks ago felt like our school was a safe and secure place now carry a new level of concern into our classrooms and hallways. My school has seen a significant drop in attendance since January with parents and guardians citing the desire to keep their children home instead of sending them to school and putting them in harm’s way as ICE raids happen across the city.

    Our staff feels the impact of the rhetoric and policy shifts out of Washington as well. They fear for the physical and emotional safety of our students when they leave the school.

    For my part, I wonder if my decisions that prioritize equity and inclusion will make me the target of criticism–or worse, an investigation. This year, we have had ongoing professional development opportunities to teach staff how they can better support our queer students and employees. Each time we engage in these discussions, I find myself worrying about the repercussions.

    But I am determined that the programs and people in place to support and protect our most vulnerable students will not go away. Rather, they will be reinforced. My role as a school leader is to create an environment so safe and accepting that students and staff never feel like they must look over their shoulder while they are at school. We want them to breathe easily knowing that, at least during the school day, they can be seen, safe, and successful.

    To be sure, this job has always been a juggle, which includes instructional leadership, behavioral support, budgeting, staffing, and–in my case–fighting the stigma of historically being identified as a low-performing school by the Colorado Department of Education. But the changes out of Washington have taken things to the next level. As I navigate it all, I do my best to be energetic, optimistic, and reliable. Each day is an exercise in finding joy in my interactions with students and staff.

    I find joy in seeing students cheer on their peers at basketball games. I find joy in watching a teacher sit with a student until they grasp a challenging concept. I find joy when I see staff members step in to teach a class for a colleague who is sick or just needs a break. I find joy and hope in my daily interactions with students and staff; they are the core of my work and are the bravest people I have worked with in my career.

    When I push my children on the merry-go-round, I tell them to get to the center because the spinning seems to slow down and the noise decreases. This is the same advice I would give to school leaders right now. Get right to the center of your work by being with students and staff as much as possible. Even at the center, the spinning does not stop. The raids, political attacks, and fear tactics do not decrease, but the challenge of facing them becomes a little more manageable. While every force out there may be pushing leaders away from the center of their work, prioritizing that values-based work reminds us exactly why we do what we do.

    Chalkbeat is a nonprofit news site covering educational change in public schools.

    For more news on school leadership, visit eSN’s Educational Leadership hub.

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  • 3 threats putting student safety at risk

    3 threats putting student safety at risk

    Key points:

    In today’s schools, whether K-12 or higher education, AI is powering smarter classrooms. There’s more personalized learning and faster administrative tasks. And students themselves are engaging with AI more than ever before, as 70 percent say they’ve used an AI tool to alter or create completely new images. But while educators and students are embracing the promise of AI, cybercriminals are exploiting it.

    In 2025, the U.S. Department of Education reported that nearly 150,000 suspect identities were flagged in recent federal student-aid forms, contributing to $90 million in financial aid losses tied to ineligible applicants. From deepfakes in admissions to synthetic students infiltrating online portals and threatening high-value research information, AI-powered identity fraud is rising fast, and our educational institutions are alarmingly underprepared.

    As identity fraud tactics become more scalable and convincing, districts are now racing to deploy modern tools to catch fake students before they slip through the cracks. Three fraud trends keep IT and security leaders in education up at night–and AI is supercharging their impact.

    1. Fraud rings targeting education

    Here’s the hard truth: Fraudsters operate in networks, but most schools fight fraud alone.

    Coordinated rings can deploy hundreds of synthetic identities across schools or districts. These groups recycle biometric data, reuse fake documents, and share attack methods on dark web forums.

    To stand a fair chance in the fight, educational institutions must work with identity verification experts that enable a holistic view of the threat landscape through cross-transactional risk assessments. These assessments spot risk patterns across devices, IP addresses, and user behavior, helping institutions uncover fraud clusters that would be invisible in isolation.

    2. Deepfakes and injected selfies in remote enrollment

    Facial recognition was once a trusted line of defense for remote learning and test proctoring. But fraudsters can now use emulators and virtual cameras to bypass those checks, inserting AI-generated faces into the stream to impersonate students. In education, where student data is a goldmine and systems are increasingly remote, the risk is even more pronounced.

    In virtual work environments, for example, enterprises are already seeing an uptick in the use of deepfakes during job interviews. By 2028, Gartner predicts 1 in 4 job candidates worldwide will be fake. The same applies to the education sector. We’re now seeing fake students, complete with forged government IDs and a convincing selfie, slide past systems and into financial aid pipelines.

    So, what’s the fix? Biometric identity intelligence, trusted by a growing number of students, can verify micro-movements, lighting, and facial depth, and confirm whether a real human is behind the screen. Multimodal checks (combining visual, motion, and even audio data) are critical for stopping AI-powered identity fraud.

    3. Synthetic students in your systems

    Unlike stolen identities, synthetic identities are crafted from real–and fake–fragments, such as a legit SSN combined with a fake name. These “students” can pass enrollment checks, get campus credentials, and even apply for financial aid.

    Traditional document checks aren’t enough to catch them. Today’s identity verification tools must use AI to detect missing elements, like holograms or watermarks, and flag patterns including identical document backgrounds, which is a key sign of industrial-scale fraud.

     AI-powered identity intelligence for education

    As digital learning becomes the norm and AI accelerates, identity fraud will only get more sophisticated. However, AI also offers educators a solution.

    By layering biometrics, behavioral analytics, and cross-platform data, schools can verify student identities at scale and in real time, keeping pace with advancing threats, and even staying one step ahead.

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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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  • 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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  • Scaling structured literacy with implementation science

    Scaling structured literacy with implementation science

    When districts adopt evidence-based practices like Structured Literacy, it’s often with a surge of excitement and momentum. Yet the real challenge lies not in the initial adoption, but in sustaining and scaling these practices to create lasting instructional change. That’s the point at which implementation science enters the picture. It offers a practical, research-backed framework to help district leaders move from one-time initiatives to systemwide transformation.

    Defining the “how” of implementation

    Implementation science is the study of methods and strategies that support the systematic uptake of evidence-based practices. In the context of literacy, it provides a roadmap for translating the science of reading, based on decades of cognitive research, into day-to-day instructional routines.

    Without this roadmap, even the most well-intentioned literacy reforms struggle to take root. Strong ideas alone are not enough; educators need clear structures, ongoing support, and the ability to adapt while maintaining fidelity to the research. Implementation science brings order to change management and helps schools move from isolated professional learning sessions to sustainable, embedded practices.

    Common missteps and how to avoid them

    One of the most common misconceptions among school systems is that simply purchasing high-quality instructional materials or delivering gold-standard professional learning, like Lexia LETRS, is enough. While these are essential components, they’re only part of the equation. What’s often missing is a focus on aligned leadership, strategic coaching, data-informed decisions, and systemwide coordination.

    Another frequent misstep is viewing Structured Literacy as a rigid, one-size-fits-all approach. In reality, it is a set of adaptable practices rooted in the foundational elements of reading: Phonemic awareness, phonics, fluency, vocabulary, and comprehension. Effective implementation requires both structure and flexibility, guided by tools like the Active Implementation Formula or NIRN’s Hexagon Tool.

    District leaders must also rethink their approach to leadership. Instructional change doesn’t happen in a vacuum or stay confined to the classroom. Leaders at every level–from building principals to regional directors–need to be equipped not just as managers, but as implementation champions.

    Overcoming initiative fatigue

    Initiative fatigue is real. Educators are weary of the pendulum swings that often characterize educational reform. What’s new today may feel like a rebranded version of yesterday’s trend. Implementation science helps mitigate this fatigue by building clear, supportive structures that promote consistency over time.

    Fragmented professional learning is another barrier. Educators need more than one-off workshops–they need coherent, job-embedded coaching and opportunities to reflect, revise, and grow. Coaching plays a pivotal role here. It serves as the bridge between theory and practice, offering modeling, feedback, and emotional support that help educators build confidence and capacity.

    Building sustainable systems

    Sustainability starts with readiness. Before launching a Structured Literacy initiative, district leaders should assess their systems. Do they have the right people, processes, and tools in place? Have they clearly defined roles and responsibilities for everyone involved, from classroom teachers to district office staff?

    Implementation teams are essential. These cross-functional groups help drive the work forward, break down silos, and ensure alignment across departments. Successful districts also make implementation part of their onboarding process, so new staff are immersed in the district’s instructional vision from day one.

    Flexibility is important, too. No two schools or communities are the same. A rural elementary school might need different pacing or grouping strategies than a large urban middle school. Implementation science supports this kind of contextual adaptation without compromising core instructional principles.

    Measuring progress beyond test scores

    While student outcomes are the ultimate goal, they’re not the only metric that matters. Districts should also track implementation fidelity, educator engagement, and coaching effectiveness. Are teachers confident in delivering instruction? Are they seeing shifts in their students’ engagement and performance? Are systems in place to sustain these changes even when staff turnover occurs?

    Dashboards, coaching logs, survey tools, and walkthroughs can all help paint a clearer picture. These tools also help identify bottlenecks and areas in need of adjustment, fostering a culture of continuous improvement.

    Equity at the center

    Implementation science also ensures that Structured Literacy practices are delivered equitably. This means all students, regardless of language, ability, or zip code, receive high-quality, evidence-based instruction.

    For multilingual learners, this includes embedding explicit vocabulary instruction, oral language development, and culturally responsive scaffolding. For students with disabilities, Structured Literacy provides a clear and accessible pathway that often improves outcomes significantly. The key is to start with universal design principles and build from there, customizing without compromising.

    The role of leadership

    Finally, none of this is possible without strong leadership. Implementation must be treated as a leadership competency, not a technical task to be delegated. Leaders must shield initiatives from political noise, articulate a long-term vision, and foster psychological safety so that staff can try, fail, learn, and grow.

    As we’ve seen in states like Mississippi and South Carolina, real gains come from enduring efforts, not quick fixes. Implementation science helps district leaders make that shift–from momentum to endurance, from isolated success to systemic change.

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