The Future is Now: AI in Education

The Future is Now: AI in Education

SEE HOW AI IS SETTING A NEW COURSE FOR EDUCATION – PERSONALIZING INSTRUCTION, IMPROVING SUPPORT FOR STUDENTS WITH DISABILITIES, OFFERING SMARTER TEACHING TOOLS AND MORE.

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A Time of Sea Change

Generative AI has brought sea change to education, causing us to rethink practices and consider new opportunities. How can it support teachers and administrators in their work? How can it give us richer insight into students’ progress? What are the risks and limitations? How do we leverage its possibilities without compromising human connections?

This issue of “The Future is Now: AI in Education “ takes a deep dive into these questions. It’s packed with tips and insights from educators, researchers, and leading voices in the field. They outline strategies for reevaluating measures of success, improving learning experiences, choosing tools for the classroom, teaching responsible use, and ensuring data privacy.

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5 ways districts can center human connection in their AI strategy

8 Redefining student success — what it means to be future-ready

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5 questions to ask when evaluating AI edtech tools 14 Four strategies for building AI literacy in the classroom 16 AI could revolutionize dyslexia intervention in schools

18 Kickstart your school year with AI tools

20 AI: On both sides of the cybersecurity fence

5 ways districts can center human connection in their AI strategy

Generative AI can be a gamechanger in education, but schools still need to safeguard human connection, writes Julia Freeland Fisher.

By Julia Freeland Fisher

As more Generative AI tools hit the market this year, schools will be working to craft policies that keep up with the technology. But in that rush, there’s a chance that we may be missing the forest for the trees. How schools use this new technology is critical — but equally critical is the impact that new technologies could have on students’ offline lives.

As AI becomes increasingly capable of things like empathy, attunement, personalized support, and on-demand advice, many of the attributes we historically held as inherently human are no longer so. For example, researchers have already found that well-

trained bots can alleviate loneliness on par with a human connection and outperform some doctors in their bedside manner

The same may be starting in education. In a report released in January, Anna Arsenault and I analyzed navigation and guidance tools emerging in the age of AI. Among our findings? Some providers are building bots that take on more emotional, motivational, and esteem support roles. At the same time, we heard that districts and colleges aren’t demanding tools focused on scaling human connection. These technological capabilities and market incentives are a perfect storm: as the tech gets better and better at performing human-like tasks, the risk that students’ social needs are

met by bots rather than humans gets worse. With that in mind, districts’ AI policies and strategies, particularly when it comes to the use of chatbots, need to take human connection into account. Here are five considerations for leaders:

1. Reinvest saved resources back into relationships.

In many cases, AI promises tempting efficiencies where human-driven processes and interventions have been time and money-intensive. While efficiencies typically replace human costs, some institutions are pouring those resources back into human connec-

tion. For example, at Georgia State University, using Mainstay chatbots to increase student persistence, revenue gained through enrollment increases was put toward hiring more staff for student support. “Some people think we’re trading technology and getting rid of staff members,” said Tim Renick, head of the university’s National Center for Student Success. “Our advisor ratio 10 years ago when we didn’t have the technology was, in some cases, a thousand students to every academic advisor. Now we’re down to 350 to one. …The technology has allowed us to hold on to students, which means holding on to tuition dollars which allows us to plow more resources into hiring more people.”

2. Invest in tech that connects. Not all schools, especially K-12 schools, have the luxury of recouping dollars to put back into staff. But even with those constraints, schools can still take a human-first approach to adopting new technologies. In fact, some tools are expanding schools’ pools of support by recruiting and training mentors, coaches,

There’s a yellow flag emerging in the space that schools would be wise to pay more attention to: students preferring to interact with bots rather than humans...

and experts to supplement schools’ scarce human resources. For example, Backrs, Career Village, College Advising Corps and Let’s Get Ready are all using AI to make connections to additional human supports.

3. Ensure access to #human support. Some providers have taken pains to ensure that anytime a student is chatting with a bot, a human is just one click away. A number of tools include the option for students interacting with a chatbot to type “#human” to get automatically directed to a human advisor or coach. Advisors can also reinforce that choice. “At the end of my meeting I always say, ‘You can always chat [with] Blu, but if Blu makes a mistake or you want to talk to a real person, [we’re] behind the chat and we’ll be able to answer you,” said Maria Francisco an advisor with the nonprofit Bottom Line. This offers not only agency for students to choose what modality of support they most prefer but also requires systems to properly staff and support those human connections.

4. Escalate based on avoidant and over-reliant behaviors, not just acute emergencies.

Districts using chatbots and companies building them often take pains to ensure that trigger words suggesting a student may be intending to harm themselves or someone else immediately raise a red flag to an adult. But there’s a yellow flag emerging in the space that schools would be wise to pay more attention to: students preferring to interact with bots rather than humans and using chatbots to avoid human interaction outright. That’s a trickier line to draw, but schools could implement escalation protocols in circumstances where students appear to be forming emotional bonds with bots or limit the duration that chats can occur.

5. Renew district-wide commitments to connection.

As AI technology rapidly advances, what we used to deem uniquely human is quickly becoming obsolete. Based on this clear trajectory, the question the field will face in the coming years is not whether bots should lend students various vital forms of support, but whether our schools stand for the value that everyone deserves human help and connection as well. In the past, that may have been implicit, as schools are social hubs in their community. But as bots in both consumer and edtech applications take on more and more social support roles, schools and their stakeholders can no longer take human connection as a given. “I think if everybody is on board with AI doing the mundane things in life, we’ll actually have time to build relationships,” said Tiffany Green, Founder and CEO of the nonprofit Uprooted Academy. “It will only work if everybody from a systems level is on board and saying we are all willing to step away from the control of the mundane of the knowledge piece and work on doing the relational.” In other words, a strong vision–and metrics–that schools will safeguard, deepen, and diversify students’ relationships provides a critical counterpoint to AI.

As schools strive to reach each and every student, AI could be a game-changer. But as GenAI begins to emulate human connection in impressive and startling ways, schools must be aware of the social implications. By safeguarding connection in these ways, students can have the best of both worlds: a technology that extends human potential and a connected community to live into that potential together.

Julia Freeland Fisher is the director of education research at the Clayton Christensen Institute. Her work aims to educate policymakers and community leaders on the power of disruptive innovation in the K-12 and higher education spheres. l

and potentially indicate where we should lean in because of an early indicator we missed. There’s also huge potential in meeting students where they’re at. We’re talking about using AI in language arts classes to adjust an anchor text’s Lexile level so students all access the same text, but it’s accessible to everyone.

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None of us have 20/20 vision about what students will need in the future, but they are going to need structured, safe environments and opportunities to explore technology with people who know them; people they trust.

privacy? Are there certain security mistakes that you see often in schools?

Dawson: Here in Illinois, schools require a contract with any vendor or third party they share student data with. They agree not to share student data, and we get insight into their security protocols. Data will follow our young students for a good period of their lives, so that’s a big responsibility. What gives me some anxiety are tools that have added AI since we signed on with them. Do we need to reevaluate each one and make sure we still approve of them having student data?

Plans fail without the right culture. How do schools build a culture that supports the use of data and AI tools?

Dawson: We need to engage parents and community members as we develop our plan, let them provide feedback and encourage them to come in and learn. None of us have 20/20 vision about what students will need in the future, but they are going to need structured, safe environments and opportunities to explore technology with people who know them; people they trust. The world we live in will be very different in five to 10 years, and we have a responsibility to help our students be ready for that, even if we’re not. l

PatrickDawson is the director of Innovation, Teaching, and Learning forWinnetka Public Schools, an Otus partner school. Otus combines assessment, data, and insights in one solution, helping educators track progress, close learning gaps and personalize instruction. Learn more at Otus.com

SB: Data security remains a top concern for school leaders, especially as the use of AI tools increases. What security practices should educators adopt to better safeguard student data

Redefining student success — what it means to be future-ready

Looking at the skills necessary for future adult success will help education leaders determine what student success should look like now.

By Isabelle Hau

The age of AI is reshaping how we work, live and connect, creating a seismic shift in the skills required to thrive in the future. Yet our education system remains entrenched in outdated models, churning out students ill-prepared for a world where algorithms excel at routine tasks but fail at creativity, ethics and relational intelligence. The gap between traditional measures of student success and the skills demanded by the future is widening — and it’s a gap we cannot afford to ignore. This is more than an urgent challenge; it’s a profound opportunity. As AI transforms industries, we must reimagine what success in education truly means. It’s no longer enough to focus on grades, test scores or rote mastery of knowledge. Instead, student success must be redefined to align with the capabilities that empower individuals to thrive in a rapidly evolving world.

Redefining success in education means moving beyond traditional metrics to prioritize a broader, more holistic set of competen-

cies. These include thinking critically, solving complex problems, innovating, collaborating, and navigating ethical and societal challenges. To achieve this, education must embrace transformative shifts:

Redefining student success

Success as relational intelligence

In an AI-driven world and our future “relational economy,” technical skills are not enough. Students must develop relational intelligence by connecting, empathizing and collaborating with others. This is particularly vital as workplaces increasingly demand teamwork, emotional intelligence and technical expertise. Success must be measured by how well students can engage authentically and work effectively in diverse and interconnected environments. For example, Tools of the Mind fosters relational intelligence by engaging preschool children in collaborative activities like Buddy Reading and Make-Believe Play, teaching empathy, perspective-taking and social connection from an early age.

Success as lifelong adaptability

The future is dynamic, and success will hinge on adaptability. Students need a continuous learning mindset, embracing curiosity and resilience as they navigate ever-changing careers and industries. Education must instill a love of lifelong learning, where students are equipped to acquire new skills and knowledge throughout their lives. For example, Pathways in Technology Early College High Schools (P-TECH) integrate high school, college, and workplace skills. Students graduate with both a diploma and an associate degree and the ability to adapt to rapidly changing industries through hands-on experience with industry mentors.

Success as creativity and problem-solving

In a world where AI handles routine tasks, human creativity becomes the ultimate differentiator. Success should be defined by students’ ability to think critically, generate innovative ideas and solve complex problems. This requires shifting from standardized

The future is dynamic, and success will hinge on adaptability.

assessments to project-based learning and other experiential methods that foster original thinking. For instance, at Big Picture Learning, students pursue personalized learning plans based on their passions, often working with mentors and completing hands-on projects.

Success as ethical and responsible citizenship

AI raises profound ethical questions about privacy, bias and societal impact. Students must be prepared to engage with these challenges, developing a strong moral compass and the ability to evaluate the broader implications of their decisions. Success should be measured by their capacity to contribute to society responsibly and equitably. For example, Montgomery County Public Schools, Maryland, has implemented a curriculum teaching digital ethics, data privacy and media literacy. Students learn to evaluate the societal impact of technology, including ethical dilemmas surrounding AI and social media.

Success as joyful learning Education too often equates success with stress and compliance. Instead, success should be about cultivating joy, passion and a sense of purpose in learning. When students are motivated by curiosity and intrinsic interest, they achieve better outcomes and sustain their drive to learn long into adulthood. Programs like Briya PCS in Washington, DC, or Tiny Trees in Seattle, Wash., immerse children in nature-based, hands-on exploration, fostering curiosity, resilience and joy.

Leading the way: 3 success stories

Take Gwinnett County Public Schools in Georgia, the fifth-largest district in the country, for example. This forward-thinking district has embraced AI as a cornerstone of its educational strategy, focusing on future-ready skills that empower students for an evolving workforce. Gwinnett integrates AI and emerging technologies into its curriculum to enhance career and technical education, personalize learning, and teach critical competencies such as data literacy and computational thinking. By preparing students to work alongside intelligent machines, Gwinnett sets a benchmark for how districts can harness technology to bridge the gap between current education models and future skill demands.

On a state level, Massachusetts is leading a transformational shift in measuring student success. Moving away from traditional standardized tests, the state has adopted competency-based assessments to evaluate students’ ability to apply knowledge and skills to real-world challenges. These assessments prioritize critical thinking, problem-solving, and interdisciplinary learning, focusing on what students can do rather than what they can memorize. This approach ensures that graduates are academically prepared and equipped to navigate complex, global challenges — a vital shift in a rapidly changing economy.

New Hampshire has also stepped forward with innovative legislation on play-based learning. The state mandates play-based approaches for young learners. This initiative is grounded in research showing that play fosters creativity, problem-solving, and social-emotional skills — key attributes for future success. By embedding play into the fabric of early education, New Hampshire addresses foundational learning needs and lays the groundwork for a lifelong love of exploration and innovation.

A blueprint for change

As Gwinnett, Massachusetts and New Hampshire show, we must fundamentally rethink how and what students learn to redefine student success. This requires embracing innovative approaches to education:

■ Collaborative learning: Success is measured not by individual competition but by the ability to work effectively in teams and leverage collective intelligence.

■ Interdisciplinary learning: The future requires connecting knowledge across fields. Success involves navigating complexity and synthesizing diverse perspectives to solve real-world challenges.

■ Experiential learning: Success is not abstract but grounded in real-world application. Internships, simulations and community-based projects allow students to practice and refine their skills.

■ Personalized learning pathways: Success looks different for every student. Education must adapt to individual strengths, interests and goals, fostering unique trajectories of achievement.

Closing the gap

The widening gap between student success as traditionally defined and the future’s skill demands is unsustainable. If we continue to equate success with test scores and compliance, we risk leaving students unprepared for a world where adaptability, creativity, and relational intelligence are paramount.

AI gives us the tools to bridge this gap, enabling personalized learning, scalable innovations and deeper engagement with students’ needs. But technology alone cannot redefine success. It takes a shift in mindset — a collective commitment to prioritizing the skills that make us uniquely human.

Imagine a future where students leave school with knowledge and the confidence, empathy and creativity to shape their own paths. A future where education measures success not by what students achieve in the classroom but by how they thrive.

The time to act is now. Let’s redefine success and create an education system that empowers every student to meet the future with purpose, resilience and joy.

Isabelle C. Hau is the executive director of the StanfordAcceleratorforLearning and the authorof “Love to Learn:TheTransformative Power ofCare and Connection in EarlyEducation.” l

5 questions to ask when evaluating AI edtech tools

How teachers can magnify AI edtech tools’ power by focusing on their needs and possibilities when selecting them.

By Tracy A. Huebner and Rachel Burstein

Many have hailed 2023 as generative AI’s breakout year. Doomsday scenarios that were previously the province of researchers, ethicists and technologists went mainstream The boardroom dramas of AI companies were above-the-fold news. Commentators wondered how the acceleration of AI technologies would impact work, environment, education and a host of other areas. Meanwhile, some of us played around with new AI edtech tools and prompts — by turns delighted, frustrated, excited and scared by what we discovered.

That was particularly true in education, where teachers, students, staff and administrators alike experimented with AI-powered tools for a range of tasks, including organization, writing, research and form completion. Some of these approaches were productive, while others produced concerning results. Meanwhile, it seems that every edtech

product now positions itself as “AI-powered,” seeking to capitalize on AI’s big moment.

At the same time, many hyped predictions for AI in education never came to fruition: School districts’ initial prohibitions on the use of ChatGPT on school-owned devices gradually gave way to guidance for using AI tools. Regular usage of AI tools by educators and students was more limited than many commentators expected. There was no sizable increase in cheating behaviors among students, even with the wide availability of AI tools.

It’s time to think less about what AI could mean for education and more about how educators can harness AI technologies for education right now. There are a host of possibilities. Some involve direct interaction between educators and students, and others assist with back-end functions such as record-keeping and lesson planning. But whatever the case, we need to focus less on the technology itself and more on how

the technology can help empower quality instruction — either by helping teachers in core instructional areas, or in freeing up time for them to concentrate on providing impactful instruction.

AI edtech tools can provide power boosts to instruction

With AI seemingly everywhere, and educators exhausted, overworked and often unclear how to evaluate the usefulness of new tools, it’s helpful to think about AI trends through the lens of “technology-enabled instruction,” an emerging term that we’ve explored. Tech-enabled instruction looks beyond technology integration (whether technology is used in the classroom) to when and how teachers use technology in their instructional practices in ways that research shows improve learning outcomes.

How can educators and administrators understand the potential value of an AI tool

It’s time to think less about what AI could mean for education and more about how educators can harness AI technologies for education right now.

for promoting tech-enabled instruction? Researchers have identified five power boosts that technology in instruction can provide:

■ Personalization, differentiation and customization to address learner needs.

■ Curation, availability, accommodation and accessibility of vetted educational materials and learning environments.

■ Student engagement, interest and motivation.

■ Communication, collaboration and relationship-building.

■ Learning analytics.

Some AI tools are well-designed to harness these areas of instructional impact, while others are not. Most useful tools will not align to all areas; indeed, some might provide value in a single area or may free up teacher time to concentrate on these areas. Such alignment must be a key consideration when educators and administrators make decisions about when and how to use AI-powered tools.

What questions should educators ask when evaluating alignment between an AI-powered edtech tool and power boost areas for impactful technology-enabled instructional practice? We break down five critical questions.

1. Does the tool allow teachers to differentiate?

Personalization to improve outcomes in learning predates modern edtech and does not need to involve technology. However, researchers have identified several ways that teachers’ use of technology for differentiation is uniquely well-positioned to advance student learning: scaffolding, multiple ways of assessing learners, opportunities for immediate feedback, opportunities to free up teacher time and more.

AI tools can make differentiation and customization easier for improved learning, even if significant questions about their

effectiveness remain. For example, Khan Academy’s chatbot, Khanmigo, allows students to receive responses that correspond directly to their questions rather than having to sift through reams of material that may or may not be appropriate for them. AI tools may also potentially realize the contextual factors impacting all learners in ways that traditional adaptive systems cannot.

2. Does the tool offer access to vetted educational materials?

The availability of vetted educational materials through edtech platforms frees teachers from the burden of having to compile materials from disparate — and often unvetted — sources. Researchers have shown that this compilation plays an important role in advancing student learning in two critical ways: supporting learner variability and making learning relevant

While curation is possible through nontechnological means, technology is a clear accelerant; it can help learners access materials that might be difficult to locate in print form, and it can allow multiple ways for learners to interact with materials. AI tools have the potential to build upon the power of open educational resource collections by customizing collections for different teaching use cases. For example, ISTE + ASCD’s walled garden chatbot draws only on materials developed by the learning organization. In evaluating any such tools, it will be important for educators to understand how the technology curates, vets and authenticates customized collections.

3. Does the tool help teachers promote student interest?

Research shows that when students are interested in a topic, they are more likely to perform well academically in that area. Teachers can employ a variety of nontechnological approaches to promoting student interest, but technology often makes that task much easier. For example, when guided by skilled educators, students can use particular databases or the internet to conduct research on topics of their own interest, using sources that would not be available to them without technology.

So-called intelligent tutoring systems may have the potential to make this process easier, offering guidance to students about how

to evaluate sources of interest to them and freeing teachers to foster deeper student interest. Of course, accuracy, bias and ease of use will be important considerations as educators evaluate such tools.

4. Does the tool offer opportunities for relationship-building?

Strong teacher-student relationships lead to better learning outcomes in the long term, according to a report from Search Institute. Similarly, when educators form strong relationships with families, students are more likely to make positive gains in the long term. At first, it may seem counterintuitive that technology could help strengthen relationships between people. But imagine a video platform that provides automatic translation services in a meeting between a teacher and a parent about a student’s progress. Or imagine a technological tool that allows students to share how they are feeling, flagging opportunities for follow-up with teachers.

AI tools can extend the value of such tools even further. For example, AI-pow-

ered text messages from tools such as AllHere and Family Engagement Lab can allow educators to more effectively reach and develop relationships with historically underserved families.

5. Does the tool offer impactful learning analytics?

The possibility of data generation and data analysis for learning underlies many benefits of using technology for instructional purposes. Of course, technology’s ability to deliver on its promise requires that the data generated by a program are both useful and provided in a timely manner that positions educators to take action. For example, a teacher may analyze data generated by an adaptive learning system to pinpoint areas of student struggle and identify appropriate interventions. But the simple data point of how many minutes a student spent on the program would be much less useful.

AI technologies promise to transform learning analytics — not just what is taught and to whom, but how instruction itself takes

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place. For example, AI-powered tools such as TeachFX provide teacher feedback at scale, offering opportunities for improved instructional practice.

What’s next?

Decisions about which edtech tools to adopt and in what ways are notoriously difficult. AI has expanded the edtech field, making adoption decisions more challenging. Using the lens of technology-enabled instruction and technology’s power boost potential in teaching is not a panacea for this challenge. But asking the five questions above is an important first step in separating the chaff from the wheat in harnessing AI-powered tools’ full potential.

Tracy Huebner, Ph.D., is director of advancement teaching and learning at WestEd. Rachel Burstein, Ph.D., is an independent education researcher and writer. They are the co-authors of “Strategies for Encouraging EffectiveTechnology-Enabled Instructional Practices in K-12 Education: AThought Piece Drawing on Research and Practice.” l

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Four strategies for building AI literacy in the classroom

The stakes are high to educate elementary and secondary students in AI literacy and the responsible use of AI technologies.

By Julianne Robar

With recent widespread access to AI-based tools, educators nationwide are only beginning to understand the scope and impact AI will have on future learning and their students’ lives. The excitement is understandable, and the potential to shape education

— and society — is immeasurable. Today, it’s even more pressing that we equip our teachers and students with the knowledge they need to navigate this new frontier.

This is a subject I am especially passionate about. I have been working with AI in some shape or form since 2000, beginning with algorithms to generate math items. In

2023, I had the honor of joining the inaugural cohort of the EDSAFE AI Alliance’s Women in AI Fellowship, which provided a venue to explore AI in educational technology further. It was perfect timing; ChatGPT was released to the public two months earlier, and I became immersed in the importance of policy and the necessity of a framework for creating a safe

environment to explore and leverage AI.

We know that today’s students will be using AI-based tools as the workforce of the future, just like many of us are already. And we can expect AI to continue to become more sophisticated. Just as teaching media literacy and responsible use of social media have become critical, the next generation will also need AI literacy. The bottom line is this: Educators need more support to understand AI, and students need to be equipped with knowledge to assess the promise and limitations of this technology and how they can use it responsibly.

Thankfully, educators don’t need to be AI experts to teach AI literacy. Common themes have emerged in the conversations surrounding AI-focused curricula for elementary

and secondary students — in addition to curricula supporting educators in learning about AI themselves! One of these resources is the International Society for Technology in Education (ISTE), which has published helpful guides for educators of all kinds.

With that in mind, here are four strategies to help build AI literacy in the classroom. But first, check your school’s policy on AI usage and see if your state has published guidelines.

Understanding AI and AI literacy

You and your students can establish a foundational understanding of AI using materials like the Artificial Intelligence (AI) for K-12 initiative (AI4K12). It offers guidance with its “Five Big Ideas in Artificial Intelligence” framework, which provides a baseline for building knowledge about AI. Core elements include perception, representation and reasoning, learning, natural interaction and societal impact. Code.org also offers a video lesson series called “How AI Works.”

From there, you can gauge students’ familiarity with specific AI tools and discuss AI’s potential and how it might impact their lives. Emphasize AI’s potential in amplifying human capabilities and broadening our horizons. It can allow any student to explore coding or deepen their creativity by interacting with image and video design. Using AI, students might learn new skills and ultimately change the course of their education, careers and lives.

Be open about the risks and limitations

Students need to understand the risks and consequences involved with AI, including responses that may present incorrect information or infringe on copyrights. Large Language Models have many ethical concerns and considerations, including answer bias and privacy concerns.

Additionally, it is essential to ensure students understand the concept of hallucinations — how inaccurate data can be generated by popular AI tools and how that information might undermine their learning.

Create a safe environment to experiment with AI

Once students understand the potential and risks, and you know your school’s AI usage policy and data privacy measures, encourage students to interact with AI in a low-stakes

environment.

Some wonderful activities designed for elementary and secondary students provide them with hands-on experience and real-time insights into AI applications. For example, Code.org offers interactive lessons with fun activities for grades 3–5 and grades 6–12—there is even a Dance Party Edition! Students can see the effects of applying human decisions to an AI bot.

Sharpen critical thinking skills to question AI

We can all agree that critical thinking skills are vital in a world of AI-generated information. Human involvement in questioning, refining and fact-checking AI-generated content is also vital.

Educators can offer several activities that will help build students’ ability to recognize inconsistencies and errors and where to turn to find factual information. One example is generating a series of AI responses to the same prompt. Then, ask students to compare and contrast the responses to identify similarities and discrepancies and facilitate a discussion about what could influence the different answers. Another exercise could ask students to identify and discuss bias in AI-generated content about controversial topics.

The quality of AI-created content should also be explored. AI responses often use specific phrasing and, by their very nature, do not include personal examples or anecdotes. A lesson might consist of two written passages, one created by a human and one AI-generated. Can the students tell the difference? Or if a student revises AI-generated content, can another student read it and recognize that AI is still involved? How does this impact our society if the same generic content is shared everywhere?

AI holds incredible promise for the future by streamlining processes, opening up new opportunities and enhancing our way of working. With these steps, educators can help prepare the next generation to leverage AI tools to their best advantage while deepening students’ critical thinking abilities.

Julianne Robar is the senior director of metadata and product interoperabilityat Renaissance. Her background as a high-school math educator informs herspecialization in assessment content development. l

AI could revolutionize dyslexia intervention in schools

AI can help teachers deliver effective dyslexia interventions for students by smoothing friction points in the process of diagnosing dyslexia.

By Coral Hoh

Will 2024 be a pivotal year for education? On the one hand, students still face post-pandemic learning loss and the end of emergency funding. On the other hand, AI promises a new kind of relief that may be more widespread and permanent. This is especially true of the perennial problem of reading difficulty or dyslexia. AI can offer individually customized evaluations for dyslexia that feed directly into individually customized interventions for all each student all at once. To learn more about the beneficial effects of this technology, let’s first look at dyslexia itself.

The economic and other problems of dyslexia

Dyslexia is not just an educational problem but an economic one. Affecting 1 in 5 people, dyslexia is the largest category in special education. Other special education categories, such as attention-deficit/hyperactivity disorder and autism, often come with reading and learning difficulties as well. Schools across the US spend over $120 billion a year on special ed

A big part of the problem with dyslexia is that even authorities in the field cannot agree on what it is. Indeed, a comprehensive meta-analytic review highlights the inconclusive nature of dyslexia studies, including the efficacy of commonly used interventions Similarly, in the last decade, rigorously designed dyslexia studies show no significant positive effect of intervention on broad reading achievement for at-risk readers after third grade. The one exception was an intervention that was not scalable due to the intensity of training needed for both teachers and students.

Due to economic and staffing limitations, interventions currently only serve about half of students with a reading difficulty. Can schools do more for this group? The answer is “no” if they keep to the current system, but it’s “yes” if they revamp the system.

Special education hampered by friction points

The current system has many friction points. Let me illustrate by putting a fictional student through the system with Alex, a third-grader with dyslexia. Dyslexia is often called an invisible disability because its symptoms are not often obvious. Alex’s school screens all students for dyslexia, as required in 40 states Immediately, we run into several friction points. The school has to train teachers to administer the screener, pay for this training, and find time in Alex’s schedule to screen him. Alex’s teacher then has to interpret the results and differentiate instruction accordingly. Multiply these efforts 5,000 times for a city school district like Columbus, Ohio Next, let us take another fictional example with Chris, a fifth-grader who has dyslexia, ADHD and autism. These conditions often co-exist. Chris’s school intends to use a more elaborate evaluation to classify her disabilities to provide appropriate services. Now, we see even more friction points. The school has to decide on which test batteries to administer among an alphabet soup of literacy, language and cognitive assessments, and by whom. Since most schools have only a few certified personnel who can administer such assessments, schools have to decide on which students to evaluate and which ones to put on a waiting list. Again, Chris’s team has to interpret the evaluation results one

student at a time. But the task is considerably harder because of 20 pages of results to translate into actionable plans. Now multiply these efforts for however many students involved. A special education teacher I met recently said she quit her job because of this Herculean task.

How AI can help ease friction points

AI can, and has, erased some of these friction points. One AI program for evaluating and correcting dyslexia, Dysolve AI, does so by making decisions autonomously without human intervention and customizes automatically for each student on demand. The power of AI in this case comes from the technology’s ability to overcome three traditional obstacles:

■ Complexity of the human brain. Dyslexia and other language-based disorders involve processing deficits in the linguistic

The cost of using AI for dyslexia intervention can be less than 10% of current spending on special services per pupil.

system that are impossible for humans to locate precisely.

■ Speed of language processing. Human evaluators cannot measure brain processes that occur in hundreds of milliseconds in parallel.

■ Capacity to serve one and all students. Teachers cannot track all errors made by one student throughout their program to locate their sources and correct them. But a computer system can — not just for one but for all students.

AI also offers the benefit of simplicity. An AI system that can overcome all three obstacles has to be massively complex in its architecture and operation. However, the student only needs to log into a webbased program and play the AI-generated evaluative-corrective games. Meanwhile, their teacher can attend to other students or monitor all users from the teacher dashboard. The AI then alerts the teacher as

to which deficits have been corrected for which student. That student is now receptive to the teacher’s instruction, such as spelling rules.

The benefits of using AI for dyslexia intervention

The cost of using AI for dyslexia intervention can be less than 10% of current spending on special services per pupil. The AI benefit goes beyond cost savings. For the first time, we can read individual brains to understand neurodivergence at a level of specificity that enables correction. AI uses a game interface to map the functional, not the physical, brain. The AI controls and corrects a user’s linguistic-cognitive outputs such as game responses through its generated games.

AI has already delivered a considerable benefit for dyslexia. The AI-generated data shows that key language processes oper-

ating below 90% to 100% efficiency hinder reading acquisition, according to Dysolve research. Different dyslexic brains have different processes operating below this level of efficiency. But a game-based program has succeeded in bringing individuals to full efficiency. At that point, students can acquire spelling, reading and written vocabulary effectively.

Before AI was connected with dyslexia assessments and interventions, specialists thought that dyslexia could not be corrected. Now, AI users who were once struggling readers are outscoring many of their peers. The same method is now being used to understand other neurodivergences. We expect even more pleasant

Coral Hoh, Ph.D., is the CEO of AI firm EduNational and the architect of Dysolve AI As a clinical linguist, she writes and referees for academic journals and is a regular guest of regional and national media l

Kickstart your school year with AI tools

Are you stumped on how to use AI tools effectively in your classroom? Michael Gaskell offers tips to get started with AI tools for teachers.

By Michael Gaskell

As the new school year begins, I think of “Friday Night Lights” and the excitement of the band playing while the home football team rushes out to rousing applause. School openings are exhilarating, but they can also feel overwhelming. Any solutions I can use to economize my time and free up for more direct contact with students and staff in classrooms are too important to overlook.

My endless list of mundane tasks and needs to open my school feels daunting. New tech solutions like AI are not the cure-all. Yet I can’t pass up having more time to improve learning and teaching by offloading trivial administrative tasks, or “administrivia,” and enlisting AI. There are reasons to be cautious about the remarkably imperfect productivity of AI, so understanding the benefits while using AI is a practical approach.

The following resources include a tool, an example of their use and cautions to consider. This is far from an exhaustive list, but you will come away with a few new methods to help offload tedious and labor-intensive tasks to an AI tool and improve the real work of improving learning and teaching.

Prompt ideas for AI chatbots

Make use of an AI chatbot to engage students in engaging ways. Leverage the power of a chatbot’s understanding of known figures to capture students’ attention. For example, if you are teaching a science lesson on the parts of a cell, why not enlist the services of none other than … Yoda?

Within the chatbot, write “I am a sixthgrade student who needs to learn all about cells and their parts. Teach me in the voice of Yoda and respond to my follow-up questions.”

The teacher can provide a list of guide questions such as, “Why are mitochondria often called the powerhouses of the cell?”

Yoda’s response: Powerhouses of the cell, mitochondria are called, yes. Energy, they produce, like little engines they work.

You can do this for any character a student is interested in, ideally with a vetted list from the teacher. The chatbot will take on the assigned persona, and the interaction will be ongoing with the character’s tone and delivery. Your students will thank you because it’s a nice break from worksheets — and eye-rolling will diminish.

Caution: A typical chatbot may occasionally provide imprecise responses, so students and their teachers should monitor this for accuracy.

AI tools for research

Challenges often associated with AI as a learning resource include bias in the results

and, worse, inaccurate information. AI can even hallucinate content, something a lawyer learned the hard way when he cited made-up cases in court. How do we ensure that fast and powerful results are accurate? Let’s examine two tools.

Perplexity. You may have heard of this AI tool and the millions of dollars Jeff Bezos from Amazon invested in it. A significant advantage of Perplexity AI is how it shares results. By including footnotes with links to the sources in prompt responses, a user can check sources for fidelity.

Caution: While some may be considered reliable, be mindful that perplexity does not differentiate these from less reliable sources. Consider that a response may include a scholarly journal, right alongside a Reddit or blog post.

There is a way around this. Within the prompt, simply ask for your results to only

include scholarly journals. For example, type this into the prompt: “Why does bullying peak in middle school? Only provide me answers from scholarly journals.”

Elicit. A number of AI resources are dedicated exclusively to providing reliable research-referenced sources.

Caution: Be mindful that the generative answer is designed to respond to your question. While it includes sources, the timeless advice to check those sources stands. Reinforcing this adds to the lessons learned about researching properly and accurately.

Image generators

There are a growing number of these in varying quality. I am not partial to anyone, but I prefer to demonstrate with the image generator from Meta.ai As you shape your prompt, it changes in full view in real-time. The image

almost appears as a claymation construction as it develops.

Disclaimer: You have to have a Facebook or Instagram account to access meta.ai. Image generators are great for students composing presentations and teachers looking to add visuals to their own lesson presentations. They are also free of copyright infringement.

Go to Meta.ai If this is your first time, you will be prompted to sign into Facebook or Instagram.

In the prompt box, type “imagine,” and then the image you desire. For example, I typed in: Imagine a principal going down a slide. The image shapeshifted as I added descriptors, such as when I added students. Suddenly, a group of happy students popped up.

Caution: AI image generation can show bias. I wrote about this last year and haven’t observed a satisfactory improvement from this. All of the principals were white men. Check out my article on biases in AI and how to navigate around such biases.

Other AI tools

■ YouTube videos are great media tools to support teaching and learning, and I recently wrote this article on companion YouTube AI tools that make using them even more impressive.

■ Form feedback is tremendous because qualitative feedback is possible when applying responses to a chatbot, as I explain in this article. Gone are the days of surface feedback from Likert scales. Using AI, I show you how you can dive into qualitative feedback quickly and effectively and use that feedback to improve your school or classroom.

Outsmart “administrivia”

All these tools and ideas are worth considering when you look to improve teaching and learning. I know that’s my core principle in leading my school. Try these ideas and feel liberated from the mundane “administrivia” so you can be a more effective educator.

Michael Gaskell, Ed.D., is the author of a new book, “Radical Principals,” and a veteran principal in NewJerseyworking at Central ElementarySchool in East Brunswick. l

AI: On both sides of the cybersecurity fence

How AI is giving cybersecurity professionals a leg up on hackers, scammers and disgruntled workers.

By Michael Domingo

Threat actors are everywhere, looking for a way into your systems, whether via phishing, planting malware or breaching via social engineering. Just two examples in recent hacking history show the sheer amount of exposed data:

■ The size of the Real Estate Wealth Network breach was 1.16 terabytes of data and included 1.5 billion records, with some famous names like Elon Musk and Kylie Jenner easily identified in the records.

■ UnitedHealth Group paid a ransom on a breach that included data on “a substantial proportion of people in America”; while the exact number isn’t known, imagine what a

“substantial proportion” means when talking about the whole of the US population (currently headed toward around 342 million).

The IT Governance site keeps a running list of some of the larger global attacks on companies and the more notorious perpetrators. It’s likely you or someone you know has data in one of those breaches. Essentially, it means the role of cybersecurity professionals is secure as long as there are threat actors looking for a way in.

AI is on both sides of the fight

Whether there’s any element of AI in any of those attacks isn’t fully known without conducting forensics on the code. Hackers and scammers are coders who know how to

use developer tools and programming languages tuned to their work to squeeze out efficiencies. It’s not a stretch of the imagination to think AI is being used by them to code – and develop attack vectors – faster and with more efficiency.

While AI might be improving the more common brute-force attacks, ransomware and phishing, AI also is improving breaches via social engineering. One type of hack is voice cloning, which seems like it comes right out of the movies, and it’s improving over time. A couple who were tricked into believing a relative was being held ransom through voice cloning is detailed in The New Yorker. Even enterprise companies have no immunity, if this story is true. According to reports in Hong Kong, authorities said a

financial firm was tricked into transferring $25 million to hackers, who used an AI deepfake video of the firm’s CEO to authorize the transfer.

Several companies are developing voice-cloning software with AI improvements, and even OpenAI said it has recently developed some improvements to its technology but is holding back on releasing an update as it assesses the risks of doing so.

Is that really who you think it is?

And just recently, Microsoft’s release of VASA1 shows proof-of-concept wherein it uses sophisticated generative AI technology to turn a still image into a video. The sample shows videos that have audio voices embedded, so

that it seems as though the still image is now animated and speaks. The possibilities for using it to create deepfakes are mind-boggling.

Fighting AI with AI

Cybersecurity professionals have their work cut out for them. If there’s anything that can be done, it’s to be proactive with cybersecurity to try to stay ahead of attacks and use due diligence to maintain sound security practices top to bottom. Already, AI is helping in a number of ways. Here are a few:

■ Cybersecurity analysis tools are using AI to streamline the methods for pinpointing weak points in security. With that, many companies follow guidelines laid down by the

Cybersecurity professionals don’t have to go it alone. AI is on your side, too.

Cybersecurity and Infrastructure Security Agency’s tool and the National Institute of Standards and Technology’s cybersecurity framework, which specifically has a component that takes AI into account. Tools from major companies like IBM, Microsoft and Amazon follow many of the suggestions, and many companies are using AI to create custom apps that follow those guidelines to build internal cybersecurity policies.

■ One of the more common methods of exposure is through the sharing – whether it’s intentional or accidental – of private information within enterprise systems. Here’s where good data governance comes into play, and companies are starting to use AI to gain insight and streamline data governance policies into the software and data connectors. Amazon, IBM, Microsoft and Salesforce have a variety of tools that use AI to enable data sharing with governance policies in place.

■ At the code level, there are a number of application security testing tools now using AI to speed up code vulnerability identification. Companies like Acunetix, CrowdStrike and Snyk offer AI-flavored tools for dynamic and static application testing. Cybersecurity professionals don’t have to go it alone. AI is on your side, too.

Michael Domingo is senior technology editor atSmartBrief, and a technologypublishing veteran whose main beat for more than two decades covered information systems, networking and Microsoft’s peculiarsoftware development stack. l