In an age defined by digital transformation, access to reliable, high-speed internet is not a luxury; it is the bedrock of opportunity. It impacts the school classroom, the doctor’s office, the town square and the job market.
As we stand on the cusp of a workforce revolution driven by the “arrival technology” of artificial intelligence, high-speed internet access has become the critical determinant of our nation’s economic future. Yet, for millions of Americans, this essential connection remains out of reach.
This digital divide is a persistent crisis that deepens societal inequities, and we must rally around one of the most effective tools we have to combat it: the Universal Service Fund. The USF is a long-standing national commitment built on a foundation of bipartisan support and born from the principle that every American, regardless of their location or income, deserves access to communications services.
Without this essential program, over 54 million students, 16,000 healthcare providers and 7.5 million high-need subscribers would lose internet service that connects classrooms, rural communities (including their hospitals) and libraries to the internet.
The discussion about the future of USF has reached a critical juncture: Which communities will have access to USF, how it will be funded and whether equitable access to connectivity will continue to be a priority will soon be decided.
Earlier this year, the Supreme Court found the USF’s infrastructure to be constitutional — and a backbone for access and opportunity in this country. Congress recently took a significant next step by relaunching a bicameral, bipartisan working group devoted to overhauling the fund. Now they are actively seeking input from stakeholders on how to best modernize this vital program for the future, and they need our input.
I’m urging everyone who cares about digital equity to make their voices heard. The window for our input in support of this vital connectivity infrastructure is open through September 15.
While Universal Service may appear as only a small fee on our monthly phone bills, its impact is monumental. The fund powers critical programs that form a lifeline for our nation’s most vital institutions and vulnerable populations. The USF helps thousands of schools and libraries obtain affordable internet — including the school I founded in downtown Brooklyn. For students in rural towns, the E-Rate program, funded by the USF, allows access to the same online educational resources as those available to students in major cities. In schools all over the country, the USF helps foster digital literacy, supports coding clubs and enables students to complete homework online.
By wiring our classrooms and libraries, we are investing in the next generation of innovators.
The coming waves of technological change — including the widespread adoption of AI — threaten to make the digital divide an unbridgeable economic chasm. Those on the wrong side of this divide experienced profound disadvantages during the pandemic. To get connected, students at my school ended up doing homework in fast-food parking lots. Entire communities lost vital connections to knowledge and opportunity when libraries closed.
But that was just a preview of the digital struggle. This time, we have to fight to protect the future of this investment in our nation’s vital infrastructure to ensure that the rising wave of AI jobs, opportunities and tools is accessible to all.
AI is rapidly becoming a fundamental tool for the American workforce and in the classroom. AI tools require robust bandwidth to process data, connect to cloud platforms and function effectively.
The student of tomorrow will rely on AI as a personalized tutor that enhances teacher-led classroom instruction, explains complex concepts and supports their homework. AI will also power the future of work for farmers, mechanics and engineers.
Without access to AI, entire communities and segments of the workforce will be locked out. We will create a new class of “AI have-nots,” unable to leverage the technology designed to propel our economy forward.
The ability to participate in this new economy, to upskill and reskill for the jobs of tomorrow, is entirely dependent on the one thing the USF is designed to provide: reliable connectivity.
The USF is also critical for rural health care by supporting providers’ internet access and making telehealth available in many communities. It makes internet service affordable for low-income households through its Lifeline program and the Connect America Fund, which promotes the construction of broadband infrastructure in rural areas.
The USF is more than a funding mechanism; it is a statement of our values and a strategic economic necessity. It reflects our collective agreement that a child’s future shouldn’t be limited by their school’s internet connection, that a patient’s health outcome shouldn’t depend on their zip code and that every American worker deserves the ability to harness new technology for their career.
With Congress actively debating the future of the fund, now is the time to rally. We must engage in this process, call on our policymakers to champion a modernized and sustainably funded USF and recognize it not as a cost, but as an essential investment in a prosperous, competitive and flourishing America.
Erin Mote is the CEO and founder of InnovateEDU, a nonprofit that aims to catalyze education transformation by bridging gaps in data, policy, practice and research.
The Hechinger Report provides in-depth, fact-based, unbiased reporting on education that is free to all readers. But that doesn’t mean it’s free to produce. Our work keeps educators and the public informed about pressing issues at schools and on campuses throughout the country. We tell the whole story, even when the details are inconvenient. Help us keep doing that.
PITTSBURGH — Saisri Akondi had already started a company in her native India when she came to Carnegie Mellon University to get a master’s degree in biomedical engineering, business and design.
Before she graduated, she had co-founded another: D.Sole, for which Akondi, who is 28, used the skills she’d learned to create a high-tech insole that can help detect foot complications from diabetes, which results in 6.8 million amputations a year.
D.Sole is among technology companies in Pittsburgh that collectively employ a quarter of the local workforce at wages much higher than those in the city’s traditional steel and other metals industries. That’s according to the business development nonprofit the Pittsburgh Technology Council, which says these companies pay out an annual $27.5 billion in salaries alone.
A “significant portion” of Pittsburgh’s transformation into a tech hub has been driven by international students like Akondi, said Sean Luther, head of InnovatePGH, a coalition of civic groups and government agencies promoting innovation businesses.
The Pittsburgh Innovation District along Forbes Avenue in Pittsburgh’s Oakland section, near the campuses of the University of Pittsburgh and Carnegie Mellon University. Credit: Nancy Andrews for The Hechinger Report
“Next Happens Here,” reads the sign above the entrance to the co-working space where Luther works and technology companies are incubated, in an area near Carnegie Mellon and the University of Pittsburgh dubbed the Pittsburgh Innovation District. The neighborhood is filled with people of various ethnicities speaking a variety of languages over lunch and coffee.
What might happen next to the international students and graduates who have helped fuel this tech economy has become an anxiety-inducing subject of those conversations, as the second presidential administration of Donald Trump brings visa crackdowns, funding cuts and other attacks on higher education — including here, in a state that voted for Trump.
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Inside the bubble of the universities and the tech sector, “there’s so much support you get,” Akondi observed, in a gleaming conference room at Carnegie Mellon. “But there still is a part of the population that asks, ‘What are you doing here?’ ”
Much of the ongoing conversation about international students has focused on undergraduates and their importance to university revenues and enrollment. Many of these students — especially in graduate schools — fill a less visible role in the economy, however. They conduct research that can lead to commercial applications, have skills employers need and start a surprising number of their own companies in the United States.
Sean Luther, head of InnovatePGH, at one of the organization’s co-working spaces. One reason tech companies have come to Pittsburgh “is because of those non-native-born workers,” Luther says. Credit: Nancy Andrews for The Hechinger Report
“The high-tech engineering and computer science activities that are central to regional economic development today are hugely dependent on these students,” said Mark Muro, a senior fellow at the Brookings Institution who studies technology and innovation. “If you go into a lab, it will be full of non-American people doing the crucial research work that leads to intellectual property, technology partnerships and startups.”
Some 143 U.S. companies valued at $1 billion or more were started by people who came to the country as international students, according to the National Foundation for American Policy, a nonprofit that conducts research on immigration and trade. These companies have an average of 860 employees each and include SpaceX, founded by Elon Musk, who was born in South Africa and graduated from the University of Pennsylvania.
Whether or not they invent new products or found businesses of their own, international graduates are “a vital source” of workers for U.S.-based tech companies, the National Science Foundation reported last year in an annual survey on the state of American science and engineering.
Dave Mawhinney, founding executive director of the Swartz Center for Entrepreneurship at Carnegie Mellon University, with Saisri Akondi, an international graduate and co-founder of the startup D.Sole. “There still is a part of the population that asks, ‘What are you doing here?’ ” says Akondi. Credit: Nancy Andrews for The Hechinger Report
It’s supply and demand, said Dave Mawhinney, a professor of entrepreneurship at Carnegie Mellon and founding executive director of its Swartz Center for Entrepreneurship, which helps many of that school’s students do research that can lead to products and startups. “And the demand for people with those skills exceeds the supply.”
That’s in part because comparatively few Americans are going into fields including science, technology, engineering and math. Even before the pandemic disrupted their educations, only 20 percent ofcollege-bound American high school students were prepared for college-level courses in these subjects. U.S. students scored lower in math than their counterparts in 21 of the 37 participating nations of the Organization for Economic Cooperation and Development on an international assessment test in 2022, the most recent year for which the outcomes are available.
One result is that international students make up more than a third of master’s and doctoral degree recipients in science and engineering at American universities. Two-thirds of U.S. university graduate students and more than half of workers in AI and AI-related fields are foreign born, according to Georgetown University’s Center for Security and Emerging Technology.
“A real point of strength, and a reason our robotics companies especially have been able to grow their head counts, is because of those non-native-born workers,” said Luther, in Pittsburgh. “Those companies are here specifically because of that talent.”
International students are more than just contributors to this city’s success in tech. “They have been drivers” of it, Mawhinney said, in his workspace overlooking the studio where the iconic children’s television program “Mister Rogers’ Neighborhood” was taped.
Jake Mohin, director of solution engineering at a company that uses AI to predict how chemicals will synthesize, uses a co-working space at InnovatePGH in Pittsburgh’s Innovation District. Credit: Nancy Andrews for The Hechinger Report
“Every year, 3,000 of the smartest people in the world come here, and a large proportion of those are international,” he said of Carnegie Mellon’s graduate students. “Some of them go into the research laboratories and work on new ideas, and some come having ideas already. You have fantastic students who are here to help you build your company or to be entrepreneurs themselves.”
Boosters of the city’s tech-driven turnaround say what’s been happening in Pittsburgh is largely unappreciated elsewhere. It followed the effective collapse of the steel industry in the 1980s, when unemployment hit 18 percent.
In 2006, Google opened a small office at Carnegie Mellon to take advantage of the faculty and student expertise in computer science and other fields there and at neighboring higher education institutions; the company later moved to a nearby former Nabisco factory and expanded its Pittsburgh workforce to 800 employees. Apple, software and AI giant SAP and other tech firms followed.
“It was the talent that brought them here, and so much of that talent is international,” said Audrey Russo, CEO of the Pittsburgh Technology Council.
Sixty-one percent of the master’s and doctoral students at Carnegie Mellon come from abroad, according to the university. So do 23 percent of those at Pitt, an analysis of federal data shows.
The city has become a world center for self-driving car technology. Uber opened an advanced research center here. The autonomous vehicle company Motional — a joint venture between Hyundai and the auto parts supplier Aptiv — moved in. So did the Ford- and Volkswagen-backed Argo AI, which eventually dissolved, but whose founders went on to create the Pittsburgh-based self-driving truck developer Stack AV. The Ford subsidiary Latitude AI and the autonomous flight company Near Earth Autonomy also are headquartered in Pittsburgh.
Among other tech firms with homes here: Duolingo, which has 830 employees and is worth an estimated $22 billion. It was co-founded by a professor at Carnegie Mellon and a graduate of the university who both came to the United States as international students, from Guatemala and Switzerland, respectively.
InnovatePGH tracks 654 startups that are smaller than those big conglomerates but together employ an estimated 25,000 workers. Unemployment in Pittsburgh (3.5 percent in April) is below the national average (3.9 percent). Now Pitt and others are developing Hazelwood Green, which includes a former steel mill that closed in 1999, into a new district housing life sciences, robotics and other technology companies.
In a series of webinars about starting businesses, offered jointly to students at Pitt and Carnegie Mellon, the most popular installment is about how to found a startup on a student visa, said Rhonda Schuldt, director of Pitt’s Big Idea Center, in a storefront on Forbes Avenue in the Innovation District.
One of the co-working spaces operated by InnovatePHG in the Pittsburgh Innovation District. Credit: Nancy Andrews for The Hechinger Report
Some international undergraduates continue into graduate school or take jobs with companies that sponsor them so they can keep working on their ideas, Schuldt said.
“They want to stay in Pittsburgh and build businesses here,” she said.
There are clear worries that this momentum could come to a halt if the supply of international students continues a slowdown that began even before the new Trump term, thanks to visa processing delays and competition from other countries.
The number of international graduate students dropped in the fall by 2 percent, before the presidential election, according to the Institute of International Education. Further declines are expected following the government’s pause on student visa interviews, publicity surrounding visa revocations and arrests and cuts to federal research funding.
Rhonda Schuldt, director of the Big Idea Center at the University of Pittsburgh. International students “want to stay in Pittsburgh and build businesses here,” Schuldt says. Credit: Nancy Andrews for The Hechinger Report
It’s too early to know what will happen this fall. But D. Sole co-founder Saisri Akondi has heard from friends who planned to come to the United States that they can’t get visas. “Most of these students wanted to start companies,” she said.
“I would be lying if I said nothing has changed,” said Akondi, who has been accepted into a master’s degree program in business administration at the Stanford University Graduate School of Business under her existing student visa, though she said her company will stay in Pittsburgh. “The fear has increased.”
This could affect whether tech companies continue to come to Pittsburgh, said Russo, at least unless and until more Americans are better prepared for and recruited into tech-related graduate programs. That’s something universities have not yet begun to do, since the unanticipated threat to their international students erupted only in March, and that would likely take years.
Audrey Russo, CEO of the Pittsburgh Technology Council. If the number of international students declines, “Who’s going to do the research? Who’s going to be in these teams?” she asks. Credit: Nancy Andrews for The Hechinger Report
“Who’s going to do the research? Who’s going to be in these teams?” asked Russo. “We’re hurting ourselves deeply.”
The impact could transcend the research and development ecosystem. “I think we’ll see almost immediate ramifications in Pittsburgh in terms of higher-skilled, higher-wage companies hiring here,” said Sean Luther, at InnovatePGH. “And that affects the grocery shops, the barbershops, the real estate.”
There are other, more nuanced impacts.
Mike Madden, left, vice president of InnovatePGH and director of the Pittsburgh Innovation District, talks with University of Pittsburgh graduate student Jayden Serenari in one of InnovatePGH’s co-working spaces. Credit: Nancy Andrews for The Hechinger Report
“Whether we like it or not, it’s a global world. It’s a global economy. The problems that these students want to solve are global problems,” Schuldt said. “And one of the things that is really important in solving the world’s problems is to have a robust mix of countries, of cultures — that opportunity to learn how others see the world. That is one of the most valuable things students tell us they get here.”
Pittsburgh is a prime example of a place whose economy is vulnerable to a decline in the number of international students, said Brookings’ Muro. But it’s not unique.
“These scholars become entrepreneurs. They’re adding to the U.S. economy new ideas and new companies,” he said. Without them, “the economy would be smaller. Research wouldn’t get done. Journal articles wouldn’t be written. Patents wouldn’t be filed. Fewer startups would occur.”
The United States, said Muro, “has cleaned up by being the absolute central place for this. The system has been incredibly beneficial to the United States. The hottest technologies are inordinately reliant on these excellent minds from around the world. And their being here is critical to American leadership.”
Contact writer Jon Marcus at 212-678-7556, [email protected]orjpm.82 on Signal.
The Hechinger Report provides in-depth, fact-based, unbiased reporting on education that is free to all readers. But that doesn’t mean it’s free to produce. Our work keeps educators and the public informed about pressing issues at schools and on campuses throughout the country. We tell the whole story, even when the details are inconvenient. Help us keep doing that.
Earlier this month, higher education policy leaders from all 50 states gathered in Minneapolis for the 2025 State Higher Education Executive Officers Higher Education Policy Conference. During a plenary session on the future of learning and work and its implications for higher education, Aneesh Raman, chief economic opportunity officer at LinkedIn, reflected on the growing need for people to be able to easily build and showcase their skills.
In response to this need, the avenues for learning have expanded, with high numbers of Americans now completing career-relevant training and skill-building through MOOCs, microcredentials and short-term certificates, as well as a growing number of students completing postsecondary coursework while in high school through dual enrollment.
The time for pontificating about the implications for higher education is past; what’s needed now is a pragmatic examination of our long-standing practices to ask, how do we evolve to keep up? We find it prudent and compelling to begin at the beginning—that is, with the learning-evaluation process (aka credit-evaluation process), as it stands to either help integrate more Americans into higher education or serve to push them out.
A 2024 survey of adult Americans conducted by Public Agenda for Sova and the Beyond Transfer Policy Advisory Board found, for example, that nearly four in 10 respondents attempted to transfer some type of credit toward a college credential. This included credit earned through traditional college enrollment and from nontraditional avenues, such as from trade/vocational school, from industry certification and from work or military experience. Of those who tried to transfer credit, 65 percent reported one or more negative experiences, including having to repeat prior courses, feeling limited in where they could enroll based on how their prior learning was counted and running out of financial aid when their prior learning was not counted. Worse, 16 percent gave up on earning a college credential altogether because the process of transferring credit was too difficult.
What if that process were drastically improved? The Council for Adult and Experiential Learning’s research on adult learners finds that 84 percent of likely enrollees and 55 percent of those less likely to enroll agree that the ability to receive credit for their work and life experience would have a strong influence on their college enrollment plans. Recognizing the untapped potential for both learners and institutions, we are working with a distinguished group of college and university leaders, accreditors, policy researchers and advocates who form the Learning Evaluation and Recognition for the Next Generation (LEARN) Commission to identify ways to improve learning mobility and promote credential completion.
With support from the American Association of Collegiate Registrars and Admissions Officers and Sova, the LEARN Commission has been analyzing the available research to better understand the limitations of and challenges within current learning evaluation approaches, finding that:
Learning-evaluation decision-making is a highly manual and time-intensive process that involves many campus professionals, including back-office staff such as registrars and transcript evaluators and academic personnel such as deans and faculty.
Across institutions, there is high variability in who performs reviews; what information and criteria are used in decision-making; how decisions are communicated, recorded and analyzed; and how long the process takes.
Along with this variability, most evaluation decisions are opaque, with little data used, criteria established or transparency baked in to help campus stakeholders understand how these decisions are working for learners.
While there have been substantial efforts to identify course equivalencies, develop articulation agreements and create frameworks for credit for prior learning to make learning evaluation more transparent and consistent, the data and technology infrastructure to support the work remain woefully underdeveloped. Without adequate data documenting date of assessment and aligned learning outcomes, credit for prior learning is often dismissed in the transfer process; for example, a 2024 survey by AACRAO found that 54 percent of its member institutions do not accept credit for prior learning awarded at a prior institution.
Qualitative research examining credit-evaluation processes across public two- and four-year institutions in California found that these factors create many pain points for learners. For one, students can experience unacceptable wait times—in some cases as long as 24 weeks—before receiving evaluation decisions. When decisions are not finalized prior to registration deadlines, students can end up in the wrong classes, take classes out of sequence or end up extending their time to graduation.
In addition to adverse impacts on students, MDRC research illuminates challenges that faculty and staff experience due to the highly manual nature of current processes. As colleges face dwindling dollars and real personnel capacity constraints, the status quo becomes unsustainable and untenable. Yet, we are hopeful that the thoughtful application of technology—including AI—can help slingshot institutions forward.
For example, institutions like Arizona State University and the City University of New York are leading the way in integrating technology to improve the student experience. The ASU Transfer Guide and CUNY’s Transfer Explorer democratize course equivalency information, “making it easy to see how course credits and prior learning experiences will transfer and count.” Further, researchers at UC Berkeley are studying how to leverage the plethora of data available—including course catalog descriptions, course articulation agreements and student enrollment data—to analyze existing course equivalencies and provide recommendations for additional courses that could be deemed equivalent. Such advances stand to reduce the staff burden for institutions while preserving academic quality.
While such solutions are not yet widely implemented, there is strong interest due to their high value proposition. A recent AACRAO survey on AI in credit mobility found that while just 15 percent of respondents report currently using AI for credit mobility, 94 percent of respondents acknowledge the technology’s potential to positively transform credit-evaluation processes. And just this year, a cohort of institutions across the country came together to pioneer new AI-enabled credit mobility technology under the AI Transfer and Articulation Infrastructure Network.
As the LEARN Commission continues to assess how institutions, systems of higher education and policymakers can improve learning evaluation, we believe that increased attention to improving course data and technology infrastructure is warranted and that a set of principles can guide a new approach to credit evaluation. Based on our emerging sense of the needs and opportunities in the field, we offer some guiding principles below:
Shift away from interrogating course minutiae to center learning outcomes in learning evaluation. Rather than fixating on factors like mode of instruction or grading basis, we must focus on the learning outcomes. To do so, we must improve course data in a number of ways, including adding learning outcomes to course syllabi and catalog descriptions and capturing existing equivalencies in databases where they can be easily referenced and applied.
Provide students with reliable, timely information on the degree applicability of their courses and prior learning, including a rationale when prior learning is not accepted or applied. Institutions can leverage available technology to automate existing articulation rules, recommend new equivalencies and generate timely evaluation reports for students. This can create more efficient advising workflows, empower learners with reliable information and refocus faculty time to other essential work (see No.3).
Use student outcomes data to improve the learning evaluation process. Right now, the default is that all prior learning is manually vetted against existing courses. But what if we shifted that focus to analyzing student outcomes data to understand whether students can be successful in subsequent learning if their credits are transferred and applied? In addition, institutions should regularly review course transfer, applicability and student success data at the department and institution level to identify areas for improvement—including in the design of curricular pathways, student supports and classroom pedagogy.
Overhaul how learning is transcripted and how transcripts are shared. We can shorten the time involved on the front end of credit-evaluation processes by shifting away from manual transcript review to machine-readable transcripts and electronic transcript transmittal. When accepting and applying prior learning—be it high school dual-enrollment credit, credit for prior learning or a course transferred from another institution—document that learning in the transcript as a course (or, as a competency for competency-based programs) to promote its future transferability.
Leverage available technology to help learners and workers make informed decisions to reach their end goals. In the realm of learning evaluation, this can be facilitated by integrating course data and equivalency systems with degree-modeling software to enable learners and advisers to identify the best path to a credential that minimizes the amount of learning that’s left on the table.
In these ways, we can redesign learning evaluation processes to accelerate students’ pathways and generate meaningful value in the changing landscape of learning and work. Through the LEARN Commission, we will continue to refine this vision and identify clear actionable steps. Stay tuned for the release of our full set of recommendations this fall and join the conversation at #BeyondTransfer.
Beth Doyle is chief of strategy at the Council for Adult and Experiential Learning and is a member of the LEARN Commission.
Carolyn Gentle-Genitty is the inaugural dean of Founder’s College at Butler University and is a member of the LEARN Commission.
Jamienne S. Studley is the immediate past president of the WASC Senior College and University Commission and is a member of the LEARN Commission.
By Pete Moss, Business Development Director at Ellucian.
‘Pouvez-vous s’il vous plaît me dire où se trouve la gare?’ – this is the extent that a colleague of mine can remember from his Introductory French module that he completed as part of a computing degree in the late 90s. That institution’s attempt at the time to embed flexibility and cross-curriculum choice to help students develop skills out of their discipline to help with employability. ‘It was easier to pass than the programming courses’ was the authentic feedback that my colleague gave in retrospect, but they did at least have the choice to expand their learning experience and gain some broader foundational skills. That institution, however, has long abandoned much of that flexibility, largely due to the apparent complexity of administration.
That is not to say that there are not fantastic examples of employability related skills initiatives across the sector, but the recent policy landscape (not least the Skills England Sector evidence on the growth and skills offer) and ever-present national growth agenda are now firmly putting the spotlight on the role of HE in this area. The if element of HE holding that key role in the skills agenda is widely held, but now the thorny problem of how must be addressed. Technology advancements, specifically AI, will play a contributory factor in how institutions can remove barriers that caused institutions to reduce flexibility in the past, but what of the wider considerations?
To explore this topic further I asked Ben Rodgers, an experienced academic registrar and AHEP consultant, for his views on the topic:
In today’s fast-moving global economy, the value of a university education is increasingly measured not just by academic achievement, but by the employability of graduates. Employers are no longer looking solely for degrees, they’re looking for skills: digital fluency, critical thinking, communication, and technical know-how that align with the needs of their industries. Meanwhile, universities are under pressure to demonstrate that their programmes deliver real-world value. The challenge is clear: how do we bridge the gap between what is taught and what is needed?
This is where technology can make a transformative difference. At the forefront of this change is a new wave of AI-powered innovation designed to bridge the gap between academic programmes and real-world skill demands. These emerging technologies can analyse curricula, extracting the skills embedded within them and mapping those against labour market data to identify areas of alignment and gaps.
Crucially, they work in both directions; institutions can see what skills a course develops, while students or employers can start with a desired competency like coding or digital marketing and trace back to the programmes that build those capabilities.
It is the kind of innovation that higher education has long needed. For too long, the link between the classroom and the workplace has been inconsistent or poorly articulated. Universities may know they are delivering valuable learning, but haven’t always had the means to evidence that value in terms that resonate with employers and prospective students. These technologies bring much-needed clarity, offering structured and data-informed ways to demonstrate how academic learning contributes directly to employment readiness.
A Game-Changer for the Lifelong Learning Entitlement (LLE)
This kind of technology becomes even more important as the UK rolls out the Lifelong Learning Entitlement (LLE). The LLE is set to reshape the educational landscape by allowing individuals to access student finance for short courses, modular learning and skills-based development over the course of their lives. This shift away from traditional three-year degrees opens new possibilities, but also new challenges.
How will learners know which modules to pick? How will they know what skills they need for the job they want or even the job they haven’t yet imagined? With the support of emerging AI-driven tools, learners can begin to reverse-engineer their career goals. Want to become a Data Scientist? These systems can help identify which combinations of modules across a university lead to that destination. Interested in project management? The technology can pinpoint where those skills are taught, and which courses offer them. It’s like having a careers advisor, curriculum guide, and labour market analyst all in one—offering personalised insights that connect educational choices with professional ambitions.
This sort of capability is vital if LLE is to be more than just a funding mechanism. It needs to be supported by intelligent infrastructure that empowers learners to make informed choices. Otherwise, there’s a risk that modular study becomes a confusing patchwork of disconnected learning.
Towards a Shared, Inter-University Skills Ecosystem
Now imagine if we took this even further. What if a skills platform were adopted not just by individual institutions but as a shared framework across regions or even nationally? In this model, students in Glasgow, Cardiff, Birmingham, or Belfast could see the skills they need for local job markets and be directed to the institutions offering them. This would create a more agile, responsive, and learner-centred education system. Universities wouldn’t just be competing with each other; they’d be collaborating to build a broader skills ecosystem.
The scale of opportunity here is significant and growing fast. Consider this: if every individual in the workforce has access to around £1,800 in personal development funding each year, the cumulative potential across a university’s learner base is vast. Multiply that by hundreds or thousands of learners, and you’re looking at a transformative funding stream that’s currently underutilised.
This is not just an opportunity for students, it’s a strategic imperative for institutions. By enabling individuals to build relevant, targeted skills, universities position themselves as essential engines of workforce development, driving economic resilience at local, regional, and national levels. It’s a win-win: empowered learners, future-ready graduates, and sustainable new revenue for the sector.
Of course, this requires a shift in thinking from institutional autonomy to inter-institutional alignment. But the benefits are compelling: more efficient use of public funding, stronger regional economies, and better outcomes for students.
Making Programme Design More Purposeful
Beyond helping students choose what to study, this technology also has the power to influence what universities choose to offer. If data consistently shows that a particular programme has little connection to current or emerging job markets, it is worth investigating. It does not mean the course should be cut. There may be academic or social reasons to preserve it, but it does mean the institution is equipped with the intelligence needed to make informed decisions.
It also invites a more purposeful approach to curriculum design. Are we including this module because it is pedagogically valuable, or because it’s always been there? Are we assessing this way because it builds a skill, or because it is the easiest to administer? When you can map outcomes to employment skills, these questions become easier to answer.
Moreover, it provides a compelling framework for conversations with students, parents, and policy-makers about the value of university education. It shows that we are listening to what the world needs and responding with academic rigour and strategic intent.
Global Potential, Local Application
The skills gap is not just a UK issue; it’s a global one. The World Economic Forum reports that nearly half of all workers (66 per cent) will need reskilling by 2030. Universities worldwide are grappling with how to stay relevant in an era of automation, AI and constant disruption. Emerging AI tools offer the potential for a globally shared skills taxonomy that could, with appropriate localisation, apply anywhere.
Conclusion
As universities continue to evolve, their role as engines of economic and social mobility becomes more important than ever. To fulfil that role, we must ensure that what we teach aligns with what the world needs. That does not mean turning every degree into job training, but it does mean being thoughtful, strategic, and transparent about the skills our programmes provide.
Emerging technologies offer an exciting glimpse into a more connected, skills-aware future. They empower students to take greater control of their learning, help universities refine and align their programmes and ensure that the promise of Higher Education translates into meaningful, real-world opportunities.
After all, education is a journey. It’s time the map caught up.
Atlanta, Georgia,(GLOBE NEWSWIRE) — Savvy Cyber Kids, a 501(c)(3) non-profit organization, appointed new members to the Board of Directors starting July, 1, 2025.
Joining the Board of Directors for Savvy Cyber Kids are James Azar, Anne-Marie Brockwell, Jason Cenamor, Nelson Soares, and Dr. Jasyn Voshell.
Savvy Cyber Kids enables youth, families and school communities empowerment through technology by providing age-appropriate cyber safety, cyber ethics and digital parenting resources and education starting at three years old.
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“As a father, cybersecurity practitioner, and advocate for creating a safer digital environment for all children, I was compelled to join the board of Savvy Cyber Kids,” states James Azar, CISO and Host, CyberHub Podcast. “The organization’s mission, under the leadership of Ben Halpert, deeply resonates with me. Promoting responsible internet use begins at home, and Savvy Cyber Kids equips parents with the guidance and talking points they need to raise digitally aware and cyber-safe children.”
James Azar is a dedicated cybersecurity practitioner and CISO in industries like FinTech, Banking, Energy and Oil and Gas with over 20 years of experience. He has a passion for aligning security and business goals, believing that innovation and creative thinking are key to solving today’s security challenges. As the host of the CyberHub Podcast, James enjoys sharing insights and fostering conversations around cybersecurity, technology, and business. He’s had the privilege of speaking at industry-leading events like RSA and CyberTech Israel and contributing to well-known publications. When not immersed in security, James enjoys espresso, good food, and a fine whiskey.
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“I’m thrilled to join the board of Savvy Cyber Kids, where I can further my commitment to empowering families, educators, and students with the knowledge to navigate the digital world safely and responsibly,” states Anne-Marie Brockwell, Account Executive, Microsoft. “Through my advocacy for proactive digital learning and community engagement, I aim to expand awareness and foster a more inclusive, ethical online future. I look forward to using my network to amplify this vital mission.”
Anne-Marie Brockwell is a seasoned Account Executive and strategic education leader with a deep commitment to empowering learners and advancing digital citizenship. At Microsoft, she leads partnerships with premier higher education institutions across New England, helping them accelerate AI innovation, modernize infrastructure, transform data strategies, and strengthen cybersecurity postures—all in service of their ultimate stakeholders: the students. With over a decade of experience spanning education technology and enterprise sectors, Anne-Marie brings a global, cross-industry perspective shaped by leadership roles at Rosetta Stone, Sanofi/Genzyme, Imagine Learning, and Deloitte. Her career has consistently focused on consulting selling, strategic partnerships, and operational excellence, underpinned by a passion for equity, access, and innovation in education.
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“As technology becomes increasingly more prominent in our everyday lives, so does the need for increased education around cybersecurity,” states Jason Cenamor, Founder, Confide Group and The CISO Society. “Like all important things, cybersecurity education starts at the grassroots, and organizations like Savvy Cyber Kids will ensure cyber safety becomes as natural as looking both ways before you cross the road. Witnessing so many people fall victim to bad actors every day, I could not be more passionate about ensuring the next generation is prepared to navigate the new world equipped with the knowledge and tools to avoid the same fate.”
Jason is the Founder and CEO of Confide Group – a cybersecurity advisory firm, and the Founder and Chief Community Officer of The CISO Society – a private community where members collaborate and share expertise on security strategy, project roadmaps, technology partners, CISO jobs, talent acquisition, industry news, and more. As a community figurehead and advocate, Jason possesses a passion for relationship building, networking, events, and providing an environment for security leaders to connect and learn from one another.
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“As a father, cybersecurity advocate, and entrepreneur passionate about digital education, I’m honored to join the Board of Directors at Savvy Cyber Kids,” states Nelson Soares, Founder & CEO, C-Vision International and CEO, NS Advisory Group Inc. “Today’s children are growing up in a world shaped by rapid technological change—one that demands both awareness and resilience. I’ve spent my career helping organizations navigate innovation responsibly, and I believe there’s no greater mission than empowering our youth to do the same. I look forward to contributing to this critical cause and supporting Savvy Cyber Kids in building a safer digital future for families everywhere.”
Nelson Soares is a dynamic entrepreneur and executive with deep expertise in leadership, consulting, and go-to-market strategy. As the Founder & CEO of C-Vision International, he has played a pivotal role in producing global thought leadership experiences for C-suite executives. He is also the CEO of NS Advisory Group Inc., where he advises startups and enterprise technology providers on scale, sales, and strategic growth. Nelson’s work bridges innovation and executive influence, particularly in cybersecurity and enterprise software, and his network spans the U.S., EMEA, LATAM, and APAC. He also serves on the board of Pocket Security, a nonprofit. A proud husband and father of two daughters, Nelson brings a personal and professional commitment to helping the next generation thrive in the digital age.
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“I’ve had the privilege of knowing and working with Ben Halpert for over 20 years, including some of his earliest projects in cybersecurity education,” states Dr. Jasyn Voshell, Senior Director, Products and Solutions Security, Zebra Technologies. “Joining the Savvy Cyber Kids Board is especially meaningful to me as an uncle to nieces and nephews who are growing up in a world where digital technology is ever-present. Being part of an organization that empowers families to navigate the online world safely and confidently is both a personal passion and professional commitment I hold close to my heart.”
Dr. Jasyn Voshell is the Senior Director of Products and Solutions Security at Zebra Technologies, where he leads the global Product & Solutions Security Program. He is responsible for the strategy, planning, and execution of Zebra’s enterprise-wide security initiatives across all products and solutions. Jasyn works closely with engineering and business teams to ensure security is embedded throughout the product lifecycle—secure by design, secure in use, and secure through trust. Jasyn was instrumental in establishing the Product Security Organization at Zebra, significantly reducing risk exposure while reinforcing customer trust in Zebra’s solutions. Under his leadership, the organization has delivered measurable improvements in secure software development practices, vulnerability management, and risk governance across the product portfolio. He holds bachelor’s degrees in Mathematics and Physics, a master’s degree in Applied Mathematics and Computer Information Systems, and a doctorate in Civil Law and Cybersecurity. Jasyn also maintains numerous industry-recognized certifications in cybersecurity and audit.
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“Our children are frontline warriors pitted against threats delivered by today’s latest technology they can’t even comprehend,” states Ben Halpert, Founder, Savvy Cyber Kids. “Parents and schools unwittingly place the children they are responsible for up against harms they are not equipped to triumph over in their daily battles, both physically and mentally.”
Making meaningful, long term, generational change for the world’s most vulnerable population which is young children, takes dedication. “In today’s reality of youth sextortion related suicide, AI suicide encouragement, 24/7 cyberbullying, and the realization of harms against our children delivered through technology, educating young children starting at age three is paramount,” said Ben Halpert.
“Most people want to believe quick fixes will work; when it comes to shaping human behaviors to build individual resilience, that is not the case. Our dedicated team looks forward to expanding our reach for the benefit of the world’s children,” said Ben Halpert.
Savvy Cyber Kids is grateful for the ongoing support of its sponsors: CISO Horizon, C-Vision International, VIPRE Security Group, PWC US, Yass Partners, Jodi Fink Halpert Berkshire Hathaway HomeServices Georgia Properties, Vercel,and SecurityScorecard.
About Savvy Cyber Kids
Savvy Cyber Kids (SCK), a 501(c)(3) nonprofit organization whose mission is to enable youth, families, and school communities to be empowered by technology, recognizes that children may be Digital Natives but are also “Digital Naives”, who, without intervention, completely lack understanding of the implications of their digital actions. Founded in 2007 by noted speaker and author Ben Halpert, Savvy Cyber Kids resources are used in 50 states and 54 countries around the world to help parents and teachers educate today’s youth on cyber safety and cyber ethics topics of cyberbullying, digital reputation, technology and screen-time balance, mental health, body and self-image, physical safety, sexting, privacy, gaming, child sexual predators, and more starting at 3 years old.
eSchool Media staff cover education technology in all its aspects–from legislation and litigation, to best practices, to lessons learned and new products. First published in March of 1998 as a monthly print and digital newspaper, eSchool Media provides the news and information necessary to help K-20 decision-makers successfully use technology and innovation to transform schools and colleges and achieve their educational goals.
Francesca Woodward is Group Managing Director for English at Cambridge University Press & Assessment.
Anyone who has ever taken English language tests to advance in their studies or work knows how important it is to have confidence in their accuracy, fairness and transparency.
Trust is fundamental to English proficiency tests. But at a time of digital disruption, with remote testing on the rise and AI tools evolving rapidly, the integrity of English language testing is under pressure.
Applied proportionally and ethically, technology can boost our trust in the exam process –adapting flexibly to test-takers’ skill levels, for instance, or allowing quicker marking and delivery of results. The indiscriminate use of technology, however, is likely to have unintended and undesirable consequences.
Technology is not the problem. Overreliance on technology can be. A case in point is the shift to remote language testing that removes substantial human supervision from the process.
During the pandemic, many educational institutions and test providers were forced to move to online-only delivery. Universities and employers adapted to the exceptional circumstances by recognising results from some of those newer and untried providers.
The consequences of rushed digital adoption are becoming clear. Students arriving at UK universities after passing newer at-home tests have been found to be poorly equipped, relative to their peers – and more prone to academic misconduct. Students were simply not being set up to succeed.
Some new at-home tests have since been de-recognised by universities amid reports that they have enabled fraud in the UK. Elsewhere, students have been paying proxies to sit online exams remotely. Online, videos explaining how to cheat on some of the newer tests have become ubiquitous.
So how can universities mitigate against these risks, while ensuring that genuine test-takers thrive academically?
When it comes to teaching and learning a language – as well as assessing a learner’s proficiency – human expertise cannot be replaced. This is clear to experts – including researchers at Cambridge, which has been delivering innovation in language learning and testing for more than a century.
Cambridge is one of the forces behind IELTS, the world’s most trusted English test. We also deliver Cambridge English Qualifications, Linguaskill and other major assessments. Our experience tells us that people must play a critical role at every step of teaching, assessment and qualification.
While some may be excited by the prospect of an “AI-first” model of testing, we should pursue the best of both worlds – human oversight prioritised and empowered by AI. This means, for instance, human-proctored tests delivered in test centres that use tried and proven tech tools.
In language testing – particularly high-stakes language testing, such as for university or immigration purposes – one size does not fit all. While an online test taken at home may be suitable and even secure for some situations for some learners, others prefer or need to be assessed in test centres, where help is on hand and the technology can be consistently relied upon. For test-takers and universities, choice and flexibility are crucial.
Cambridge has been using and experimenting with AI for decades. We know in some circumstances that AI can be transformative in improving users’ experience. For the highest stakes assessments, innovation alone is no alternative to real human teaching, learning and understanding. And the higher the stakes, the more important human oversight becomes.
The sector must reaffirm its commitment to quality, rigour and fairness in English language testing. This means resisting shortcuts and challenging providers that are all too ready to compromise on standards. It means investing in human expertise. It means using technology to enhance, not undermine, trust.
This is not the time to “move fast and break things”. Every test provider, every university and every policymaker must play their part.
Institutions spend a lot of time surveying students for their feedback on their learning experience, but once you have crunched the numbers the hard bit is working out the “why.”
The qualitative information institutions collect is a goldmine of insight about the sentiments and specific experiences that are driving the headline feedback numbers. When students are especially positive, it helps to know why, to spread that good practice and apply it in different learning contexts. When students score some aspect of their experience negatively, it’s critical to know the exact nature of the perceived gap, omission or injustice so that it can be fixed.
Any conscientious module leader will run their eye down the student comments in a module feedback survey – but once you start looking across modules to programme or cohort level, or to large-scale surveys like NSS, PRES or PTES, the scale of the qualitative data becomes overwhelming for the naked eye. Even the most conscientious reader will find that bias sets in, as comments that are interesting or unexpected tend to be foregrounded as having greater explanatory power over those that seem run of the mill.
Traditional coding methods for qualitative data require someone – or ideally more than one person – to manually break down comments into clauses or statements that can be coded for theme and sentiment. It’s robust, but incredibly laborious. For student survey work, where the goal might be to respond to feedback and make improvements at pace, institutions are open that this kind of robust analysis is rarely, if ever, the standard practice. Especially as resources become more constrained, devoting hours to this kind of detailed methodological work is rarely a priority.
Let me blow your mind
That is where machine learning technology can genuinely change the game. Student Voice AI was founded by Stuart Grey, an academic at the University of Strathclyde (now working at the University of Glasgow), initially to help analyse student comments for large engineering courses. Working with Advance HE he was able to train the machine learning model on national PTES and PRES datasets. Now, further training the algorithm on NSS data, Student Voice AI offers literally same-day analysis of student comments for NSS results for subscribing institutions.
Put the words “AI” and “student feedback” in the same sentence and some people’s hackles will immediately rise. So Stuart spends quite a lot of time explaining how the analysis works. The word he uses to describe the version of machine learning Student Voice AI deploys is “supervised learning” – humans manually label categories in datasets and “teach” the machine about sentiment and topic. The larger the available dataset the more examples the machine is exposed to and the more sophisticated it becomes. Through this process Student Voice AI has landed on a discreet number of comment themes and categories for taught students and the same for postgraduate research students that the majority of student comments consistently fall into – trained on and distinctive to UK higher education student data. Stuart adds that the categories can and do evolve:
“The categories are based on what students are saying, not what we think they might be talking about – or what we’d like them to be talking about. There could be more categories if we wanted them, but it’s about what’s digestible for a normal person.”
In practice that means that institutions can see a quantitative representation of their student comments, sorted by category and sentiment. You can look at student views of feedback, for example, and see the balance of positive, neutral and negative sentiment, overall, segment it into departments or subject areas, or years of study, then click through to see the relevant comments to see what’s driving that feedback. That’s significantly different from, say, dumping your student comments into a third party generative AI platform (sharing confidential data with a third party while you’re at it) and asking it to summarise. There’s value in the time and effort saved, but also in the removal of individual personal bias, and the potential for aggregation and segmentation for different stakeholders in the system. And it also becomes possible to compare student qualitative feedback across institutions.
Now, Student Voice AI is partnering with student insight platform evasys to bring machine learning technology to qualitative data collected via the evasys platform. And evasys and Student Voice AI have been commissioned by Advance HE to code and analyse open comments from the 2025 PRES and PTES surveys – creating opportunities to drill down into a national dataset that can be segmented by subject discipline and theme as well as by institution.
Bruce Johnson, managing director at evasys is enthused about the potential for the technology to drive culture change both in how student feedback is used to inform insight and action across institutions:
“When you’re thinking about how to create actionable insight from survey data the key question is, to whom? Is it to a module leader? Is it to a programme director of a collection of modules? Is it to a head of department or a pro vice chancellor or the planning or quality teams? All of these are completely different stakeholders who need different ways of looking at the data. And it’s also about how the data is presented – most of my customers want, not only quality of insight, but the ability to harvest that in a visually engaging way.”
“Coming from higher education it seems obvious to me that different stakeholders have very different uses for student feedback data,” says Stuart Grey. “Those teaching at the coalface are interested in student engagement; at the strategic level the interest is in strategic level interest in trends and sentiment analysis and there are also various stakeholder groups in professional services who never get to see this stuff normally, but we can generate the reports that show them what students are saying about their area. Frequently the data tells them something they knew anyway but it gives them the ammunition to be able to make change.”
The results are in
Duncan Berryman, student surveys officer at Queens University Belfast, sums up the value of AI analysis for his small team: “It makes our life a lot easier, and the schools get the data and trends quicker.” Previously schools had been supplied with Excel spreadsheets – and his team were spending a lot of time explaining and working through with colleagues how to make sense of the data on those spreadsheets. Being able to see a straightforward visualisation of student sentiment on the various themes means that, as Duncan observes rather wryly, “if change isn’t happening it’s not just because people don’t know what student surveys are saying.”
Parama Chaudhury, professor of economics and pro vice provost education (student academic experience) at University College London explains where qualitative data analysis sits in the wider ecosystem for quality enhancement of teaching and learning. In her view, for enhancement purposes, comparing your quantitative student feedback scores to those of another department is not particularly useful – essentially it’s comparing apples with oranges. Yet the apparent ease of comparability of quantitative data, compared with the sense of overwhelm at the volume and complexity of student comments, can mean that people spend time trying to explain the numerical differences, rather than mining the qualitative data for more robust and actionable explanations that can give context to your own scores.
It’s not that people weren’t working hard on enhancement, in other words, but they didn’t always have the best possible information to guide that work. “When I came into this role quite a lot of people were saying ‘we don’t understand why the qualitative data is telling us this, we’ve done all these things,’” says Parama. “I’ve been in the sector a long time and have received my share of summaries of module evaluations and have always questioned those summaries because it’s just someone’s ‘read.’ Having that really objective view, from a well-trained algorithm makes a difference.”
UCL has tested two-page summaries of student comments to specific departments this academic year, and plans to roll out a version for every department this summer. The data is not assessed in a vacuum; it forms part of the wider institutional quality assurance and enhancement processes which includes data on a range of different perspectives on areas for development. Encouragingly, so far the data from students is consistent with what has emerged from internal reviews, giving the departments that have had the opportunity to engage with it greater confidence in their processes and action plans.
None of this stops anyone from going and looking at specific student comments, sense-checking the algorithm’s analysis and/or triangulating against other data. At the University of Edinburgh, head of academic planning Marianne Brown says that the value of the AI analysis is in the speed of turnaround – the institutionl carries out a manual reviewing process to be sure that any unexpected comments are picked up. But being able to share the headline insight at pace (in this case via a PowerBI interface) means that leaders receive the feedback while the information is still fresh, and the lead time to effect change is longer than if time had been lost to manual coding.
The University of Edinburgh is known for its cutting edge AI research, and boasts the Edinburgh (access to) Language Models (ELM) a platform that gives staff and students access to generative AI tools without sharing data with third parties, keeping all user data onsite and secured. Marianne is clear that even a closed system like ELM is not appropriate for unfettered student comment analysis. Generative AI platforms offer the illusion of a thematic analysis but it is far from robust because generative AI operates through sophisticated guesswork rather than analysis of the implications of actual data. “Being able to put responses from NSS or our internal student survey into ELM to give summaries was great, until you started to interrogate those summaries. Robust validation of any output is still required,” says Marianne. Similarly Duncan Berryman observes: “If you asked a gen-AI tool to show you the comments related to the themes it had picked out, it would not refer back to actual comments. Or it would have pulled this supposed common theme from just one comment.”
The holy grail of student survey practice is creating a virtuous circle: student engagement in feedback creates actionable data, which leads to education enhancement, and students gain confidence that the process is authentic and are further motivated to share their feedback. In that quest, AI, deployed appropriately, can be an institutional ally and resource-multiplier, giving fast and robust access to aggregated student views and opinions. “The end result should be to make teaching and learning better,” says Stuart Grey. “And hopefully what we’re doing is saving time on the manual boring part, and freeing up time to make real change.”
When hackers hit a school district, they can expose Social Security numbers, home addresses, and even disability and disciplinary records. Now, cybersecurity advocates warn that the Trump administration’s budget and personnel cuts, along with rule changes, are stripping away key defenses that schools need.
“Cyberattacks on schools are escalating and just when we need federal support the most, it’s being pulled away,” said Keith Krueger, chief executive officer of the Consortium for School Networking, an association of technology officials in K-12 schools.
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The stakes are high. Schools are a top target in ransomware attacks, and cyber criminals have sometimes succeeded in shutting down whole school districts. The largest such incident occurred in December, when hackers stole personal student and teacher data from PowerSchool, a company that runs student information systems and stores report cards. The theft included data from more than 60 million students and almost 10 million teachers. PowerSchool paid an undisclosed ransom, but the criminals didn’t stop. Now, in a second round of extortion, the same cyber criminals are demanding ransoms from school districts.
Of chief concern is a cybersecurity service known as MS-ISAC, which stands for Multi-State Information Sharing and Analysis Center. It warns more than 5,700 schools around the country that have signed up for the service about malware and other threats and recommends security patches. This technical service is free to schools, but is funded by an annual congressional appropriation of $27 million through the Cybersecurity and Infrastructure Security Agency (CISA), an agency within the Department of Homeland Security.
On March 6, the Trump administration announced a $10 million funding cut as part of broader budget and staffing cuts throughout CISA. That was ultimately negotiated down to $8.3 million, but the service still lost more than half of its remaining $15.7 budget for the year. The non-profit organization that runs it, the Center for Internet Services, is digging into its reserves to keep it operating. But those funds are expected to run out in the coming weeks, and it is unclear how the service will continue operating without charging user fees to schools.
“Many districts don’t have the budget or resources to do this themselves, so not having access to the no cost services we offer is a big issue,” said Kelly Lynch Wyland, a spokeswoman for the Center for Internet Services.
Sharing threat information
Another concern is the effective disbanding of the Government Coordinating Council, which helps schools address ransomware attacks and other threats through policy advice, including how to respond to ransom requests, whom to inform when an attack happens and good practices for preventing attacks. This coordinating council was formed only a year ago by the Department of Education and CISA. It brings together 13 nonprofit school organizations representing superintendents, state education leaders, technology officers and others. The council met frequently after the PowerSchool data breach to share information.
Now, amid the second round of extortions, school leaders have not been able to meet because of a change in rules governing open meetings. The group was originally exempt from meeting publicly because it was discussing critical infrastructure threats. But the Department of Homeland Security, under the Trump administration, reinstated open meeting rules for certain advisory committees, including this one. That makes it difficult to speak frankly about efforts to thwart criminal activity.
Non-governmental organizations are working to resurrect the council, but it would be in a diminished form without government participation.
“The FBI really comes in when there’s been an incident to find out who did it, and they have advice on whether you should pay or not pay your ransom,” said Krueger of the school network consortium.
A federal role
A third concern is the elimination in March of the education Department’s Office of Educational Technology. This seven-person office dealt with education technology policies — including cybersecurity. It issued cybersecurity guidance to schools and held webinars and meetings to explain how schools could improve and shore up their defenses. It also ran a biweekly meeting to talk about K-12 cybersecurity across the Education Department, including offices that serve students with disabilities and English learners.
Eliminating this office has hampered efforts to decide which security controls, such as encryption or multi-factor authentication, should be in educational software and student information systems.
Many educators worry that without this federal coordination, student privacy is at risk. “My biggest concern is all the data that’s up in the cloud,” said Steve Smith, the founder of the Student Data Privacy Consortium and the former chief information officer for Cambridge Public Schools in Massachusetts. “Probably 80 to 90 percent of student data isn’t on school-district controlled services. It’s being shared with ed tech providers and hosted on their information systems.”
Security controls
“How do we ensure that those third-party providers are providing adequate security against breaches and cyber attacks?” said Smith. “The office of ed tech was trying to bring people together to move toward an agreed upon national standard. They weren’t going to mandate a data standard, but there were efforts to bring people together and start having conversations about the expected minimum controls.”
That federal effort ended, Smith said, with the new administration. But his consortium is still working on it.
In an era when policymakers are seeking to decrease the federal government’s involvement in education, arguing for a centralized, federal role may not be popular. But there’s long been a federal role for student data privacy, including making sure that school employees don’t mishandle and accidentally expose students’ personal information. The Family Educational Rights and Privacy Act, commonly known as FERPA, protects student data. The Education Department continues to provide technical assistance to schools to comply with this law. Advocates for school cybersecurity say that the same assistance is needed to help schools prevent and defend against cyber crimes.
“We don’t expect every town to stand up their own army to protect themselves against China or Russia,” said Michael Klein, senior director for preparedness and response at the Institute for Security and Technology, a nonpartisan think tank. Klein was a senior advisor for cybersecurity in the Education Department during the previous administration. “In the same way, I don’t think we should expect every school district to stand up their own cyber-defense army to protect themselves against ransomware attacks from major criminal groups.”
And it’s not financially practical. According to the school network consortium only a third of school districts have a full-time employee or the equivalent dedicated to cybersecurity.
Budget storms ahead
Some federal programs to help schools with cybersecurity are still running. The Federal Communications Commission launched a $200 million pilot program to support cybersecurity efforts by schools and libraries. FEMA funds cybersecurity for state and local governments, which includes public schools. Through these funds, schools can obtain phishing training and malware detection. But with budget battles ahead, many educators fear these programs could also be cut.
Perhaps the biggest risk is the end to the entire E-Rate program that helps schools pay for the internet access. The Supreme Court is slated to decide this term on whether the funding structure is an unconstitutional tax.
“If that money goes away, they’re going to have to pull money from somewhere,” said Smith of the Student Data Privacy Consortium. “They’re going to try to preserve teaching and learning, as they should. Cybersecurity budgets are things that are probably more likely to get cut.
“It’s taken a long time to get to the point where we see privacy and cybersecurity as critical pieces,” Smith said. “I would hate for us to go back a few years and not be giving them the attention they should.”
The Hechinger Report provides in-depth, fact-based, unbiased reporting on education that is free to all readers. But that doesn’t mean it’s free to produce. Our work keeps educators and the public informed about pressing issues at schools and on campuses throughout the country. We tell the whole story, even when the details are inconvenient. Help us keep doing that.
Microsoft Corp. and the National FFA Organization on Tuesday announced the national expansion of FarmBeats for Students, a cutting-edge educational program integrating smart sensors, data science and artificial intelligence (AI) to teach precision agriculture in classrooms. Starting today, FFA teachers and students throughout the United States, including FFA chapters in 185 middle and high schools, will receive a classroom set of FarmBeats for Students kits free of charge. The kits include ready-to-use sensor systems along with curriculum for teachers and are designed for classrooms of all kinds; no prior technical experience is required.
More and more farmers are adopting advanced technology, including automating systems such as tractors and harvesters and using drones and data analysis to intervene early against pests and disease, to maximize crop yield, optimize resource usage, and adjust to changing weather patterns. Gaining hands-on experience with machine automation, data science and AI will help American agricultural students remain competitive in the global market.
Using the FarmBeats for Students kits and free curriculum, students build environmental sensor systems and use AI to monitor soil moisture and detect nutrient deficiencies — allowing them to understand what is happening with their plants and make data-driven decisions in real time. Students can adapt the kit to challenges unique to their region — such as drought, frost and pests — providing them with practical experience in tackling real-world issues in their hometowns.
“Microsoft is committed to ensuring students and teachers have the tools they need to succeed in today’s tech-driven world, and that includes giving students hands-on experience with precision farming, data science and AI,” said Mary Snapp, Microsoft vice president, Strategic Initiatives. “By teaming up with FFA to bring FarmBeats for Students to students across the country, we hope to inspire the next generation of agriculture leaders and equip them with the skills to tackle any and all challenges as they guide us into the future.”
“Our partnership with Microsoft exemplifies the power of collaboration in addressing industry needs while fostering personal and professional growth among students,” said Christine White, chief program officer, National FFA Organization. “Supporting agricultural education and leadership development is crucial for shaping the next generation of innovators and problem solvers. Programs like this equip students with technical knowledge, confidence and adaptability to thrive in diverse and evolving industries. Investing in these young minds today sets the stage for a more sustainable, innovative and resilient agricultural future.”
In addition, teachers, students or parents interested in FarmBeats for Students can purchase a kit for $35 at this link and receive free training at Microsoft Learn.
Any educator interested in implementing the FarmBeats for Students program can now access a new, free comprehensive course on the Microsoft Educator Learn Center, providing training on precision agriculture, data science and AI, allowing teachers to earn professional development hours and badges.
FarmBeats for Students was co-developed by Microsoft, FFA and agriculture educators. The program aligns with the AI for K-12 initiative guidelines; Agriculture, Food and Natural Resources career standards; Computer Science Teachers Association standards; and Common Core math standards.
For more information about FarmBeats for Students, visit aka.ms/FBFS.
Kevin is a forward-thinking media executive with more than 25 years of experience building brands and audiences online, in print, and face to face. He is an acclaimed writer, editor, and commentator covering the intersection of society and technology, especially education technology. You can reach Kevin at [email protected]
Math anxiety isn’t just about feeling nervous before a math test. It’s been well-known for decades that students who are anxious about math tend to do worse on math tests and in math classes.
But recently, some of us who research math anxiety have started to realize that we may have overlooked a simple yet important reason why students who are anxious about math underperform: They don’t like doing math, and as a result, they don’t do enough of it.
We wanted to get a better idea of just what kind of impact math anxiety could have on academic choices and academic success throughout college. In one of our studies, we measured math anxiety levels right when students started their postsecondary education. We then followed them throughout their college career, tracking what classes they took and how well they did in them.
We found that highly math-anxious students went on to perform worse not just in math classes, but also in STEM classes more broadly. This means that math anxiety is not something that only math teachers need to care about — science, technology and engineering educators need to have math anxiety on their radar, too.
We also found that students who were anxious about math tended to avoid taking STEM classes altogether if they could. They would get their math and science general education credits out of the way early on in college and never look at another STEM class again. So not only is math anxiety affecting how well students do when they step into a STEM classroom, it makes it less likely that they’ll step into that classroom in the first place.
This means that math anxiety is causing many students to self-sort out of the STEM career pipeline early, closing off career paths that would likely be fulfilling (and lucrative).
Our study’s third major finding was the most surprising. When it came to predicting how well students would do in STEM classes, math anxiety mattered even more than math ability. Our results showed that if you were a freshman in college and you wanted to do well in your STEM classes, you would likely be better off reducing your math anxiety than improving your math ability.
We wondered: How could that be? How could math anxiety — how you feel about math — matter more for your academic performance than how good you are at it? Our best guess: avoidance.
If something makes you anxious, you tend to avoid doing it if you can. Both in our research and in that of other researchers, there’s been a growing understanding that in addition to its other effects, math anxiety means that you’ll do your very best to engage with math as little as possible in situations where you can’t avoid it entirely.
In some of our other work, we found that math-anxious students were less interested in doing everyday activities precisely to the degree that they thought those activities involved math. The more a math-anxious student thought an activity involved math, the less they wanted to do it.
If math anxiety is causing students to consistently avoid spending time and effort on their classes that involve math, this would explain why their STEM grades suffer.
What does all of this mean for educators? Teachers need to be aware that students who are anxious about math are less likely to engage with math during class, and they’re less likely to put in the effort to study effectively. All of this avoidance means missed opportunities for practice, and that may be the key reason why many math-anxious students struggle not only in math class, but also in science and engineering classes that require some math.
Math anxiety researchers are at the very beginning of our journey to understand ways to make students who are anxious about math stop avoiding it but have already made some promising suggestions for how teachers can help. One study showed that a direct focus on study skills could help math-anxious students.
Giving students clear structure on how they should be studying (trying lots of practice problems) and how often they should be studying (spaced out over multiple days, not just the night before a test) was effective at helping students overcome their math anxiety and perform better.
Especially heartening was the fact that the effects seen during the study persisted in semesters beyond the intervention; these students tended to make use of the new skills into the future.
Math anxiety researchers will continue to explore new ways to help math-anxious students fight their math-avoidant proclivities. In the meantime, educators should do what they can to help their students struggling with math anxiety overcome this avoidance tendency — it could be one of the most powerful ways a math teacher can help shape their students’ futures.
Rich Daker is a researcher and founder of Pinpoint Learning, an education company that makes research-backed tools to help educators identify why their students make mistakes. Ian Lyons is an associate professor in Georgetown University’s Department of Psychology and principal investigator for the Math Brain Lab.
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