Category: Students

  • The maintenance loan now covers only half of students’ costs

    The maintenance loan now covers only half of students’ costs

    I’m in two minds over whether it was a curse or a blessing – and I may be retrospectively overstating its impact.

    But when I sat down to watch a bit of telly back on Tuesday 13th May 2003, I had no real sense of the extent to which it would end up causing me lost sleep over silos.

    The Day Britain Stopped was a BBC1 docudrama, set in the near future, that explored how a devastating chain of events could leave the country completely paralysed.

    First, a national rail strike pushes huge volumes of passengers and freight onto the roads, overwhelming the motorway network.

    Then the M25 becomes jammed after multiple accidents, including one on the Dartford Crossing. Poor coordination between highways management, police, and emergency services slows response times, and conflicting rerouting decisions worsen the congestion, leaving rescue crews unable to reach incidents.

    Then severe delays ripple through the air transport system, compounded by diverted flights and congested airports. And these all lead to a mid-air collision between two aircraft near Heathrow – killing hundreds – as communication and coordination systems fail under strain.

    Gridlock

    I was thinking about The Day Britain Stopped on a campus a few weeks ago. Student leaders were explaining a proposal from their university to take 30 ECTS credits or so of most degrees (ie a semester) and turn them into a compulsory placement.

    A “mini sandwich” is not, all things considered, a terrible idea. Students would gain valuable work experience – which we know helps with graduate outcomes – and in aggregate there would end up being a moderate reduction in teaching and assessment costs.

    But on the assumption that it would often be unpaid, given the maximum maintenance loan is now significantly below the National Minimum Wage (when chunked out at 30 weeks for 35 hours a week), working full-time for a semester would pretty much prohibit students from earning the extra that many need to now.

    Just like the two teams each re-routing traffic down the same country lanes around the M25, it’s a classic case of not seeing the full picture – and when combined with the HE sector’s preference for policy over scenario planning, potentially disastrous. But nothing like that could be coming in the year ahead, surely?

    Britain’s best days are ahead

    This does nothing for my doom-mongering street cred, but back in May 2024 – when HEPI and TechnologyOne published work from Loughborough University on a Minimum Income for Students (MIS) – I allowed myself a little optimism.

    In a sea of information that seemed to be designed to entice participation rather than be realistic about the costs of it, I imagined that the headline figure – that students need £18,632 per year outside of London to achieve a baseline student experience – would start to adorn .ac.uk cost of living webpages offering budgeting advice to students.

    Given the methodology for calculating the MIS was close to that used by the Living Wage Foundation, and given the Westminster government’s intent to ask the Low Pay Commission to (to all intents and purposes) replicate that methodology for the National Living Wage, I even allowed myself to imagine for a few moments that government might commit to closing the gap between available support and liveable income. It surely wouldn’t be committed to a liveable income for work but not one for study?

    Alas, it wasn’t to be. Vanishingly few of the universities that offer “typical” or “sample” student budgets quote anything like that figure – and that’s if they offer one at all. International students are still misled into thinking that the maximum maintenance loan will cover their costs, parents are still completely in the dark about what they’ll really need to contribute, and many of the survival stories that I’m told by new student leaders every summer have gone from amusing to heartbreaking.

    The MIS report even recommended that when students apply to higher education, UCAS could compare the support available from the student’s home UK nation with their expected living costs. But at the time of writing, the admissions service’s webpage on budgeting instead offers “average” spend figures from 2020, and somehow omits the £2,110 that the source study found students spending when preparing for higher education.

    Governments, meanwhile, did little. This coming September, Scotland is offering up a freeze (real terms cut) on maintenance support, Northern Ireland has an increase that still falls significantly short, and both Wales and England are increasing the maximum by 3.1 per cent. A frozen means test threshold means even fewer will get that max in England – and right now both RPI inflation and CPI inflation are in fact running at 4.1 per cent.

    Update: It’s all worse

    As such, if last year’s report was like a warming sign, the 2025 update to the MIS report ought to be like a fire alarm. The update expands on the 2024 research by examining first-year students and those living in halls for the first time – and through focus groups across five UK cities, researchers found that first-year students face the highest costs of any student group – £418 per week including rent to reach a minimum acceptable standard of living.

    This represents a “first-year premium” of around £14-20 more per week than continuing students, driven by both “setting-up” costs (laptops, kitchen equipment, bedding) and “settling-in” costs (freshers week activities, food wastage while learning to budget, and higher social spending to establish friendships).

    The financial pressure on students has intensified dramatically across all UK nations. In England, even students receiving maximum maintenance support can only cover half (50 per cent) of their actual living costs, forcing them to work over 20 hours per week at minimum wage to make ends meet.

    That, I add in passing, is 20 hours more a week than most politicians’ alma mater allows students to work to have a fulfilling student experience:

    Studying at Oxford is an exciting experience with plenty of opportunities and a high number of contact hours. For this reason, paid term-time employment is not permitted except under exceptional circumstances and in consultation with your Tutor and the Senior Tutor.

    Students from different UK nations face different circumstances – Welsh students have 63 per cent of their costs covered by maintenance support, while those from Northern Ireland receive support covering just 42 per cent of their needs. The gap between what students need and what they receive has created what the researchers term a “hidden parental contribution” – one that now exceeds £10,000 annually for English families.

    I still regularly encounter those who expect to see mass dropouts as a result of the growing gap – but anyone that works closely with students will tell you that it’s a slow participation implosion that we’re seeing rather than a non-continuation explosion.

    Two-thirds of students now work during term time, the highest on record – pressure that is squeezing out various aspects of university life, as students report less time for independent study, fewer opportunities to join activities, and increased commuting distances. Many are experiencing a fundamentally different university experience than they expected, with a third having less disposable income than planned, and 1 in 5 buying fewer books or course materials.

    Over a three-year degree, the total cost of reaching minimum living standards ranges from approximately £59,000 in Wales to £77,000 in London, excluding tuition fees. And these figures are what students need not for luxury, but simply to participate fully in university life with dignity. Even living in accommodation that is “purpose built” for students, while providing important social opportunities, is typically more expensive than shared private housing – with rent making up to 47 per cent of total living costs in London.

    Thanks to Terry Nutkins, Gordon Banks and Let Loose

    One particularly pleasing aspect of the report is the “surprising” costs that so many miss when casting round the marcomms office for a couple of student ambassadors to cobble up a budget.

    Practical necessities include storage costs between academic years when halls contracts end, insurance for phones and laptops used outside accommodation, and mattress protectors for the “really cheap and uncomfortable” beds typically provided.

    First-year students face particular financial pressures during their settling-in period, wasting money on food while learning to shop and cook independently, plus ongoing laundry costs in halls that can reach £5 weekly for basic washing needs.

    Academic periods bring additional expenses, from extra food costs during exam sessions when students spend long hours in libraries, to transport costs for third-year students attending job interviews and graduate recruitment events.

    Basic costs related to social participation and mental health are also included. They include individual crockery and cutlery in halls to avoid hygiene issues when sharing with strangers, a £20 (!) annual personalisation budget for room decoration that prevents students feeling like they’re “in prison,” and £50 annually for clothing required for university social events and society activities.

    They are seemingly minor expenses – but they all add up, and they highlight how the “minimum” standard isn’t about luxury, but about enabling students to participate fully in university life, maintain their mental health, and avoid social exclusion.

    There’s also dehumidifier packs to combat poor ventilation and condensation from drying clothes, tabletop ironing boards to fit cramped spaces, and overdoor hooks because standard furniture is insufficient for storing belongings across shared living arrangements.

    Technical necessities include extension leads for inadequate electrical outlets and Wi-Fi boosters for poor connectivity, while protective measures like upholstery and carpet cleaners become crucial for avoiding deposit losses. Even basic items like door mats for communal cleanliness and shower caddies for bathroom storage represent additional shared costs when five people live together.

    Beyond accommodation, students face numerous individual costs related to campus life and practical necessities that all accumulate quickly. They include water bottles and Tupperware containers for daily campus use and food storage, delivery and returns costs reflecting modern shopping patterns, and small airers for bedroom clothes drying when shared facilities are limited.

    Admin costs like provisional driving licences at £34 become the most practical form of student ID, cheaper and more portable than passports. And there’s eye tests every two years with potential glasses purchases, and a small budget for everyday medicines and a couple of prescriptions annually – along with significant variations in personal care costs, the report particularly noting “the higher cost of hairdressing for afro hair in particular,” while emphasising that regular haircuts are deemed essential for being “presentable” and maintaining “self-respect”. Luxuries these are not.

    Parental contribution

    The report repeats last year’s calls for urgent, system-wide reform based on five principles: simplicity, transparency, independence, sufficiency, and fiscal neutrality. Key recommendations include increasing maintenance support so students can reach minimum living standards through a combination of government support and reasonable part-time work, providing a “first-year boost” to help new students establish themselves, and raising parental contribution thresholds so families only contribute when they themselves have achieved minimum living standards.

    The researchers argue reforms could be implemented without additional government spending – although the proposal is to reintroduce much-maligned but fairly progressive real interest rates on student loans, ensuring those who benefit most from higher education contribute accordingly. Sadly, they’re usually the loudest too.

    Without reforms, they warn of three critical risks – increasingly unequal access to higher education, declining quality of student experience, and threats to sector sustainability as students struggle to afford university attendance.

    But forgive me for the doom. Any or all of that will have to wait until at least September 2026, and even then is looking increasingly unlikely, given that the Treasury is said to be staring at a £41bn hole in its budget, and is currently borrowing the money on the bond markets to lend to students at an interest rate of 4.5 per cent – a far cry from 0.5 per cent nine years ago.

    And it could all be about to get much much worse.

    Basket cases

    Whether you use RPI or CPI is almost immaterial – it’s the basket of goods that matters, and neither basket captures the basket of a student typified in the MIS. Students spend more on food than the average consumer, and in that basket they’re less able to “trade down” through the brands.

    The Bank of England expects food inflation to be around 5 per cent Q3, rising to 5.5 per cent by the end of the year – higher global commodity prices, higher labour costs and Extended Producer Responsibility regulations that come into effect from October of this year all driving the change.

    In June, Beef and Butter were up at 20 per cent, Coffee was at 12.5 per cent and Chocolate was running at 16 per cent. Decent rent data is hard to come by – but it always seems to increase by more than inflation. If not included in their rent, energy prices have shifted from being a drag on inflation to providing a boost – Ofgem’s price cap for households is £1,720 for July-September 2025, almost 10 per cent higher than the same period last year.

    And the BoE’s key mitigation measure – to cut the Bank Rate by 0.25 percentage points to 4 per cent at its August meeting – might be helping students’ landlords, but it won’t be impacting student budgets.

    Meanwhile, if students have been steadily increasing their term-time work (both in numbers of students and hours worked), that could be a coming problem too. Employment growth has stagnated, and job vacancies have fallen significantly. And while two-thirds of students say they’ve been in work during term time, 89 per cent of applicants are now expecting to find work – rising to 93 per cent of care leavers, 94 per cent of international students and 96 per cent of estranged students.

    Either there’s lots of spare jobs going, or the UK may be about to run out of part-time work for students. That’s a problem few will see coming, will be almost certainly be worse in some cities than in others, and would be exacerbated if the usual ratio of students spending in businesses v those working in those businesses shifts significantly – both having grown gently in tandem as student numbers have grown. The need to convert more jobs on campus to those that students can do has never been greater – even if they sound like the first to have gone as teams have contracted in recent years.

    Some will find work that’s further and further away from campus, some will find work that’s more and more punishing on them both mentally and physically, and some simply won’t find it at all. Many – like the international student leader I met last week – will find themselves working for less than minimum wage just to pay their fees, in a country that couldn’t seem less interested in those sorts of labour market abuses if it tried.

    God forbid a student has a setback, an accident or a costly health problem. Or happens to be a student in a year when if nothing else, there will be major and un-modelled impacts on student housing supply as a result of dramatic reforms to the way that an already scandalously poor rental market is regulated.

    Implosions v explosions

    Maybe a crisis is coming – the classic unplanned-for crisis of the sort in The Day Britain Stopped, when various factors conspire in a single period to multiply each other into something that few saw coming. But even if it isn’t an explosion and we see non-continuation rates fall off a cliff, we can see what’s coming – students choosing to stay at home just as their local university closes courses, students choosing against the extracurriculars that would make up for the skills their course supplies but are no longer needed.

    Students breathing in the spores of black mould as they literally choose between heating, and eating.

    In the 2024 MIS report, the authors warned against any increases to maintenance support that would come at the cost of lower participation in higher education, “for example if an increase could only be paid for by capping the number of students who can study in higher education”. The kneejerk makes sense – neither governments, universities nor students are ever keen on measures that might limit opportunity.

    But offering students a loan that only covers half of their basic living costs, and then asking them to work a minimum 20 hours a week during term-time isn’t “opportunity”, it’s a scam – one that sells “student life” but for those on low incomes offers the kind of experience associated with labour market outcomes they’re less likely to achieve anyway, and one that allows lots of people to pat themselves on the participation back while plunging unsuspecting students into poverty.

    If the country really can’t afford mass participation in higher education, and students can’t afford to be students, the only morally right thing to do is admit it. And if telling students they need £21,126 per year to live on might put some of them off, then maybe it should.

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  • North Carolina Launches Expanded Direct Admission Program for 62,000 High School Seniors

    North Carolina Launches Expanded Direct Admission Program for 62,000 High School Seniors

    North Carolina is taking bold steps to democratize college access with the expansion of its NC College Connect program, which will offer direct admission to more than 62,000 public high school seniors this fall. The initiative represents a significant shift toward equity-focused admissions practices that prioritize accessibility over traditional application barriers.

    The program targets students who complete their junior year with a weighted GPA of 2.8 or higher. By eliminating the often overwhelming application process, NC College Connect removes financial and procedural obstacles that disproportionately affect first-generation college students and those from underrepresented communities.

    “NC College Connect represents a fundamental shift in how we approach college admissions in North Carolina,” said Peter Hans, President of the University of North Carolina System. The initiative reflects growing national recognition that traditional admissions processes can perpetuate educational inequities.

    Maurice “Mo” Green, State Superintendent of Public Instruction, praised the collaborative nature of the effort.

    “When our entire education community works together like this, students win. NC College Connect removes barriers and creates clear pathways to college for thousands of our students,” he said.

    The program’s inclusive design addresses systemic challenges that have historically limited college access for students from diverse backgrounds. By providing direct admission letters and eliminating complex application requirements, the initiative particularly benefits students who might otherwise be deterred by navigating multiple institutional processes.

    Participating institutions span the full spectrum of North Carolina’s higher education landscape, including UNC System universities, independent colleges and universities, and community colleges. This comprehensive approach ensures students have pathways to various types of post-secondary education that align with their academic goals and financial circumstances.

    Dr. Jeff Cox, President of the North Carolina Community College System, highlighted the program’s potential to transform access to affordable education. 

    “By removing barriers and simplifying the process, we’re helping more students access the life-changing opportunities our community colleges provide—close to home and at a price they can afford,” he said.

    Community colleges have long served as crucial entry points for students from diverse socioeconomic backgrounds, offering both career preparation and transfer pathways to four-year institutions. The inclusion of community colleges in NC College Connect recognizes their vital role in democratizing higher education access.

    The program’s commitment to equity extends beyond admissions to address affordability concerns through targeted financial aid initiatives. The Next NC Scholarship and NC Need-Based Scholarship specifically support students from households earning $80,000 or less, covering tuition and fees at participating institutions.

    Additionally, students attending Elizabeth City State University, Fayetteville State University, University of North Carolina at Pembroke, and Western Carolina University benefit from the NC Promise plan’s $500 per semester tuition rate. These historically Black institutions and regional universities serve particularly diverse student populations, making the affordable tuition structure especially impactful for underrepresented students.

    Hope Williams, President of North Carolina Independent Colleges and Universities, noted the unique value proposition of smaller institutions: the personalized attention and specialized programs that can be particularly beneficial for students who might struggle in larger university environments.

    The program builds on a successful pilot year that served more than 70,000 students, demonstrating the demand for streamlined college access. The expansion indicates that initial outcomes validated the approach’s effectiveness in connecting students with higher education opportunities.

    Students can verify their eligibility through the NCCollegeConnect.com portal or by consulting with high school counselors, ensuring multiple touchpoints for information and support. Eligible seniors will receive official admission letters this fall for the 2026-27 academic year, providing ample time for planning and preparation.

    NC College Connect positions North Carolina as a leader in reimagining college admissions to prioritize access and equity. As higher education institutions nationwide grapple with declining enrollment and questions about traditional admissions practices, North Carolina’s comprehensive approach offers a replicable model for other states.

    The initiative’s success will likely be measured not just in enrollment numbers, but in its ability to diversify the state’s college-going population and create pathways for students who might otherwise forego higher education. By removing procedural barriers and addressing financial constraints, NC College Connect represents a holistic approach to educational equity that extends well beyond the admissions office.

     

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  • 4 tips to support the literacy needs of middle and high school students

    4 tips to support the literacy needs of middle and high school students

    Key points:

    Today’s middle schoolers continue to struggle post-pandemic to read and write at the level needed to successfully navigate more complex academic content in the upper grades and beyond, according to a new report from NWEA, a K-12 assessment and research organization.

    Based on NWEA’s research, current 8th graders would need close to a full academic year of additional instruction to catch up to their pre-pandemic peers in reading. This trend was reiterated in recent assessment results from the National Assessment on Educational Progress (NAEP), with only 30 percent of eighth-grade students performing at or above the NAEP proficient level.

    While early literacy initiatives have garnered attention in recent years, the fact remains that many students struggle to read and are not prepared for the rigors of middle school. Students quickly find themselves challenged to keep up as they no longer receive explicit, structured reading instruction, even as they are expected to comprehend increasingly complex materials across subjects, like science, history, or English Language Arts.

    The report, Policy recommendations for addressing the middle school reading crisis, is co-authored by Miah Daughtery, EdD, NWEA VP of Academic Advocacy at HMH (NWEA’s parent company), and Chad Aldeman, founder of Read Not Guess.

    “Our current middle and high schoolers were just starting their literacy journey when the pandemic hit, and we cannot lessen the urgency to support them. But, middle school literacy is complex even for students who are reading on grade level. This demands intentional, well-funded, and focused policy leadership that includes support across the K-12 spectrum,” said Daughtery. “Simply put, learning to read is not done when a student exits elementary school; support cannot stop there either.”

    Policymakers and district leaders must adopt a systems-level approach that supports both early learners and the unique literacy needs of middle and high school students.

    The new report provides four components that can be leveraged to make this happen:

    1. Use high-quality, grade-appropriate assessments that provide specific data on the literacy needs of middle schoolers.
    2. Look at flexible scheduling and policies that promote literacy development throughout the entire school day and help districts more effectively use instructional time.
    3. Understand and support the unique literacy needs of middle schoolers across subjects and disciplines from a systems perspective and invest in teacher professional learning in all disciplines, including at the upper grades, within state and district literacy plans.
    4. Curate relationships with external partners, like community organizations and nonprofits, who share similar goals in improving literacy outcomes, and can both support and reinforce literacy development, stretching beyond the school’s hours and resources.
    eSchool News Staff
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  • AI teacher tools display racial bias when generating student behavior plans, study finds

    AI teacher tools display racial bias when generating student behavior plans, study finds

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

    Asked to generate intervention plans for struggling students, AI teacher assistants recommended more-punitive measures for hypothetical students with Black-coded names and more supportive approaches for students the platforms perceived as white, a new study shows.

    These findings come from a report on the risks of bias in artificial intelligence tools published Wednesday by the non-profit Common Sense Media. Researchers specifically sought to evaluate the quality of AI teacher assistants — such as MagicSchool, Khanmingo, Curipod, and Google Gemini for Education — that are designed to support classroom planning, lesson differentiation, and administrative tasks.

    Common Sense Media found that while these tools could help teachers save time and streamline routine paperwork, AI-generated content could also promote bias in lesson planning and classroom management recommendations.

    Robbie Torney, senior director of AI programs at Common Sense Media, said the problems identified in the study are serious enough that ed tech companies should consider removing tools for behavior intervention plans until they can improve them. That’s significant because writing intervention plans of various sorts is a relatively common way teachers use AI.

    After Chalkbeat asked about Common Sense Media’s findings, a Google spokesperson said Tuesday that Google Classroom has turned off the shortcut to Gemini that prompts teachers to “Generate behavior intervention strategies” to do additional testing.

    However, both MagicSchool and Google, the two platforms where Common Sense Media identified racial bias in AI-generated behavior intervention plans, said they could not replicate Common Sense Media’s findings. They also said they take bias seriously and are working to improve their models.

    School districts across the country have been working to implement comprehensive AI policies to encourage informed use of these tools. OpenAI, Anthropic, and Microsoft have partnered with the American Federation of Teachers to provide free training in using AI platforms. The Trump Administration also has encouraged greater AI integration in the classroom. However, recent AI guidelines released by the U.S. Department of Education have not directly addressed concerns about bias within these systems.

    About a third of teachers report using AI at least weekly, according to a national survey conducted by the Walton Family Foundation in cooperation with Gallup. A separate survey conducted by the research organization Rand found teachers specifically report using these tools to help develop goals for Individualized Education Program — or IEP — plans. They also say they use these tools to shape lessons or assessments around those goals, and to brainstorm ways to accommodate students with disabilities.

    Torney said Common Sense Media isn’t trying to discourage teachers from using AI in general. The goal of the report is to encourage more awareness of potential uses of AI teacher assistants that might have greater risks in the classroom.

    “We really just want people to go in eyes wide open and say, ‘Hey these are some of the things that they’re best at and these are some of the things you probably want to be a little bit more careful with,’” he said.

    Common Sense Media identified AI tools that can generate IEPs and behavior intervention plans as high risk due to their biased treatment of students in the classroom. Using MagicSchool’s Behavior Intervention Suggestions tool and the Google Gemini “Generate behavior intervention strategies tool,” Common Sense Media’s research team ran the same prompt about a student who struggled with reading and showed aggressive behavior 50 times using white-coded names and 50 times using Black-coded names, evenly split between male- and female-coded names.

    The AI-generated plans for the students with Black-coded names didn’t all appear negative in isolation. But clear differences emerged when those plans from MagicSchool and Gemini were compared with plans for students with white-coded names.

    For example, when prompted to provide a behavior intervention plan for Annie, Gemini emphasized addressing aggressive behavior with “consistent non-escalating responses” and “consistent positive reinforcement.” Lakeesha, on the other hand, should receive “immediate” responses to her aggressive behaviors and positive reinforcement for “desired behaviors,” the tool said. For Kareem, Gemini simply said, “Clearly define expectations and teach replacement behaviors,” with no mention of positive reinforcement or responses to aggressive behavior.

    Torney noted that the problems in these AI-generated reports only became apparent across a large sample, which can make it hard for teachers to identify. The report warns that novice teachers may be more likely to rely on AI-generated content without the experience to catch inaccuracies or biases. Torney said these underlying biases in intervention plans “could have really large impacts on student progression or student outcomes as they move across their educational trajectory.”

    Black students are already subject to higher rates of suspension than their white counterparts in schools and more likely to receive harsher disciplinary consequences for subjective reasons, like “disruptive behavior.” Machine learning algorithms replicate the decision-making patterns of the training data that they are provided, which can perpetuate existing inequalities. A separate study found that AI tools replicate existing racial bias when grading essays, assigning lower scores to Black students than to Asian students.

    The Common Sense Media report also identified instances when AI teacher assistants generated lesson plans that relied on stereotypes, repeated misinformation, and sanitized controversial aspects of history.

    A Google spokesperson said the company has invested in using diverse and representative training data to minimize bias and overgeneralizations.

    “We use rigorous testing and monitoring to identify and stop potential bias in our AI models,” the Google spokesperson said in an email to Chalkbeat. “We’ve made good progress, but we’re always aiming to make improvements with our training techniques and data.”

    On its website, MagicSchool promotes its AI teaching assistant as “an unbiased tool to aid in decision-making for restorative practices.” In an email to Chalkbeat, MagicSchool said it has not been able to reproduce the issues that Common Sense Media identified.

    MagicSchool said their platform includes bias warnings and instructs users not to include student names or other identifying information when using AI features. In light of the study, it is working with Common Sense to improve its bias detection systems and design tools in ways that encourage educators to review AI generated content more closely.

    “As noted in the study, AI tools like ours hold tremendous promise — but also carry real risks if not designed, deployed, and used responsibly,” MagicSchool told Chalkbeat. “We are grateful to Common Sense Media for helping hold the field accountable.”

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

    For more news on AI, visit eSN’s Digital Learning hub.

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  • Adding a trauma-responsive lens for student support

    Adding a trauma-responsive lens for student support

    Key points:

    Across the country, our schools are being taxed beyond their capacity to support educational success. We’ve known for a long time that students need a three-dimensional structure of guidance and encouragement to thrive. That’s why the Multi-Tiered System of Supports (MTSS) framework was created–it’s a prevention framework for early identification of varying student needs and the responses needed to maximize academic success. In theory, an MTSS supports academic, social-emotional, and behavioral needs in equal measure. However, in practice, many schools are struggling to incorporate social-emotional and behavioral components in their MTSS–even as many of their students come to school bearing the effects of adversity, trauma, or crisis.

    This imbalance is leaving millions of children behind.

    Each year, at least 1 in 7 children in the United States experience abuse, violence, natural disasters, or other adverse childhood experiences (ACEs). By age 16, roughly two-thirds of children will have been exposed to at least one traumatic event. This can impair their ability to learn well and contribute to absenteeism, while secondary trauma spirals out from these students to classmates and teachers, multiplying the overall impact. Left unaddressed, the imprint of such events could warp the future of our school and public communities.

    Since COVID-19, schools have reported unprecedented levels of absenteeism and student distress, and supporting trauma-exposed students without training puts more pressure on teachers, who are already burned out and leaving the profession at high rates. Therefore, it is clear to me that creating school-wide networks of trauma-informed adults is essential for fostering supportive learning and growth for students, enhancing educator capacity to nurture trauma-affected learners, and ensuring effective trauma resource management within districts.

    Research has identified a supportive school community as a strong childhood protective factor against the effects of trauma. We should be hopeful about our path forward. But the vision and blueprint for this enhancement of MTSS need to come as soon as possible, and it needs to come from state-level education leaders and school district leaders.

    Gaps in support and expertise

    Consider this scenario: A student who recently experienced a traumatic car accident sits near a window in class, experiencing significant distress or dysregulation without outward signs. A sudden screech of tires outside activates their sympathetic nervous system (the one associated with fight or flight), and the student shuts down, withdrawing into themselves. Their teacher, unaware of the student’s trauma history and unequipped with relevant training, interprets the response as a continuation of past misbehavior or as an academic deficit.

    This sort of misunderstanding takes place in a thousand places every day. I would stress that this isn’t a reflection of bad intentions, but rather a symptom of fragmented systems and knowledge. Even when trauma is recognized, lack of intentional collaboration and training often result in missed opportunities or inconsistent support, which cannot maximize recovery from trauma and may, in fact, hinder it, as research on retraumatization suggests.

    There might be mismatched expectations when teachers send students to the counselor, not knowing that they themselves have a role to play in the healing. In other cases, students may be referred to a school counselor and have a productive support session–but on their way back to class, a seemingly benign statement from a third party can be misconstrued or cause dysregulation, unintentionally undoing the support they’ve received. The solution to all these problems is school-wide training on trauma-informed skills. This way, all educators and staff alike develop a shared knowledge, understanding, language, and responses as they collaborate and connect with students. With the right tools, adults on campus have better trauma-informed strategies to use in their relationships with students and in building a safe and supportive school community.

    The proof is all around us

    Trauma training works synergistically within MTSS: social-emotional and trauma-responsive support allows for better academic outcomes, which work to further reduce behavioral problems, and so on. At the Center for Safe & Resilient Schools and Workplaces, we see this play out often with our school district partners. For example, at Pasadena Unified School District, which was recently ravaged by the Eaton Canyon Fire, trauma-informed best practices and preparations have enabled district leaders to reopen schools with sufficient psychological understanding and interventions along with the needed material support for the 10,000 students who were affected.

    A truly effective MTSS model does not treat trauma as a peripheral concern. It integrates trauma-responsive strategies into every tier of support–from universal practices, to targeted interventions, to intensive mental health services. In that environment, every adult who comes in contact with students has the training to adhere to trauma best practices.

    We are at a juncture where the impact of trauma poses serious risks to the education system, but evidence-based approaches exist to solve the problem. Change from the state level down is the best way to transform school cultures quickly, and I urge state education leaders to take action. Any MTSS plan isn’t complete without a trauma-informed foundation, lens, and programming. And our students–each and every one–deserve nothing less.

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  • Call to promote university racism survey – Campus Review

    Call to promote university racism survey – Campus Review

    The Australian Human Rights Commission’s landmark Racism@Uni survey will appear in student and staff inboxes from August 11.

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  • Gen Z craves purpose. Universities must catch up – Campus Review

    Gen Z craves purpose. Universities must catch up – Campus Review

    Speak to young university students today and a picture emerges of deep concern for justice, hunger for real-world connection, and an urgent desire to belong to something bigger than themselves.

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  • Visa Processing Delays Could Cost U.S. Universities $7 Billion and 60,000 Jobs This Fall

    Visa Processing Delays Could Cost U.S. Universities $7 Billion and 60,000 Jobs This Fall

    Recent disruptions to student visa processing could trigger a 30-40% decline in new international student enrollment this fall, potentially costing the U.S. economy $7 billion and more than 60,000 jobs, according to a new analysis by NAFSA: Association of International Educators and JB International.

    The preliminary projections, based on SEVIS and State Department data, paint a stark picture for higher education institutions that have come to rely heavily on international students for both revenue and academic diversity. The analysis predicts an overall 15% drop in international enrollment for the 2025-26 academic year, which would reverse years of steady growth in this critical sector.

    “This analysis, the first to calculate the potential economic impact of fewer international students on cities and towns across the country, should serve as a clarion call to the State Department that it must act,” said Dr. Fanta Aw, executive director and CEO of NAFSA. “The immediate economic losses projected here are just the tip of the iceberg.”

    The projected decline stems from a confluence of policy changes and administrative challenges that have created significant barriers for prospective international students:

    Visa Interview Suspension: Between May 27 and June 18, 2025, student visa interviews were paused during the peak issuance season—precisely when students needed to secure visas for fall enrollment. When interviews resumed on June 18, consulates received a directive to implement new social media vetting protocols within five days, but with minimal guidance.

    Appointment Bottlenecks: Reports indicate limited or no visa appointment availability in key countries including India, China, Nigeria, and Japan. India and China alone represent the top two sources of international students to the United States, while Nigeria ranks seventh and Japan 13th among sending countries.

    Declining Visa Issuance: F-1 student visa issuance dropped 12% from January to April 2025 and plummeted 22% in May 2025 compared to the same period in 2024. While June 2025 data has not been published, the analysis suggests a possible 80-90% decrease based on the identified disruptions.

    Travel Restrictions: A June 4, 2025 executive order imposed restrictions on nationals from 19 countries, with reports suggesting another 36 countries could be added. These restrictions alone threaten $3 billion in annual economic contributions and more than 25,000 American jobs.

    The economic implications extend far beyond university campuses. International students contributed $46.1 billion to the U.S. economy in 2024-25 and supported nearly 400,000 jobs across various sectors including housing, dining, retail, and transportation.

    The projected 15% enrollment decline would reduce international student economic contributions to $39.2 billion in 2025-26, down from an expected $46.1 billion. This represents not just a loss to individual institutions, but to entire communities that have built economic ecosystems around international education.

    “Without significant recovery in visa issuance in July and August, up to 150,000 fewer students may arrive this fall,” the report warns, highlighting the narrow window remaining for policy corrections.

    Beyond immediate economic impacts, education leaders worry about long-term consequences for American higher education’s global competitiveness. International students contribute to research innovation, provide diverse perspectives in classrooms, and often remain in the United States after graduation, filling critical roles in STEM fields and other high-demand sectors.

    The timing is particularly concerning given increased competition from other English-speaking countries like Canada, Australia, and the United Kingdom, which have positioned themselves as more welcoming alternatives for international students.

    To mitigate what NAFSA calls a “devastating outcome,” the organization is urging Congress to direct the State Department to take two immediate actions:

    1. Provide expedited visa appointments and processing for all F-1 and M-1 students and J-1 exchange visitor visa applicants
    2. Exempt F and M students as well as J exchange visitors from current travel restrictions affecting nationals from 19 countries, while maintaining required background checks and vetting

    The report argues that these policy changes could help institutions avoid the projected enrollment cliff and preserve the economic benefits that international students bring to American communities.

    For institutions planning fall enrollment, the report suggests the need for contingency planning and advocacy efforts to address visa processing challenges. With the traditional summer months representing the final opportunity for students to secure visas for fall enrollment, time is running short for policy interventions.

     

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  • What we lose when AI replaces teachers

    What we lose when AI replaces teachers

    Key points:

    A colleague of ours recently attended an AI training where the opening slide featured a list of all the ways AI can revolutionize our classrooms. Grading was listed at the top. Sure, AI can grade papers in mere seconds, but should it?

    As one of our students, Jane, stated: “It has a rubric and can quantify it. It has benchmarks. But that is not what actually goes into writing.” Our students recognize that AI cannot replace the empathy and deep understanding that recognizes the growth, effort, and development of their voice. What concerns us most about grading our students’ written work with AI is the transformation of their audience from human to robot.

    If we teach our students throughout their writing lives that what the grading robot says matters most, then we are teaching them that their audience doesn’t matter. As Wyatt, another student, put it: “If you can use AI to grade me, I can use AI to write.” NCTE, in its position statements for Generative AI, reminds us that writing is a human act, not a mechanical one. Reducing it to automated scores undermines its value and teaches students, like Wyatt and Jane, that the only time we write is for a grade. That is a future of teaching writing we hope to never see.

    We need to pause when tech companies tout AI as the grader of student writing. This isn’t a question of capability. AI can score essays. It can be calibrated to rubrics. It can, as Jane

    said, provide students with encouragement and feedback specific to their developing skills. And we have no doubt it has the potential to make a teacher’s grading life easier. But just because we can outsource some educational functions to technology doesn’t mean we should.

    It is bad enough how many students already see their teacher as their only audience. Or worse, when students are writing for teachers who see their written work strictly through the lens of a rubric, their audience is limited to the rubric. Even those options are better than writing for a bot. Instead, let’s question how often our students write to a broader audience of their peers, parents, community, or a panel of judges for a writing contest. We need to reengage with writing as a process and implement AI as a guide or aide rather than a judge with the last word on an essay score.

    Our best foot forward is to put AI in its place. The use of AI in the writing process is better served in the developing stages of writing. AI is excellent as a guide for brainstorming. It can help in a variety of ways when a student is struggling and looking for five alternatives to their current ending or an idea for a metaphor. And if you or your students like AI’s grading feature, they can paste their work into a bot for feedback prior to handing it in as a final draft.

    We need to recognize that there are grave consequences if we let a bot do all the grading. As teachers, we should recognize bot grading for what it is: automated education. We can and should leave the promises of hundreds of essays graded in an hour for the standardized test providers. Our classrooms are alive with people who have stories to tell, arguments to make, and research to conduct. We see our students beyond the raw data of their work. We recognize that the poem our student has written for their sick grandparent might be a little flawed, but it matters a whole lot to the person writing it and to the person they are writing it for. We see the excitement or determination in our students’ eyes when they’ve chosen a research topic that is important to them. They want their cause to be known and understood by others, not processed and graded by a bot.

    The adoption of AI into education should be conducted with caution. Many educators are experimenting with using AI tools in thoughtful and student-centered ways. In a recent article, David Cutler describes his experience using an AI-assisted platform to provide feedback on his students’ essays. While Cutler found the tool surprisingly accurate and helpful, the true value lies in the feedback being used as part of the revision process. As this article reinforces, the role of a teacher is not just to grade, but to support and guide learning. When used intentionally (and we emphasize, as in-process feedback) AI can enhance that learning, but the final word, and the relationship behind it, must still come from a human being.

    When we hand over grading to AI, we risk handing over something much bigger–our students’ belief that their words matter and deserve an audience. Our students don’t write to impress a rubric, they write to be heard. And when we replace the reader with a robot, we risk teaching our students that their voices only matter to the machine. We need to let AI support the writing process, not define the product. Let it offer ideas, not deliver grades. When we use it at the right moments and for the right reasons, it can make us better teachers and help our students grow. But let’s never confuse efficiency with empathy. Or algorithms with understanding.

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  • What really shapes the future of AI in education?

    What really shapes the future of AI in education?

    This post originally appeared on the Christensen Institute’s blog and is reposted here with permission.

    Key points:

    A few weeks ago, MIT’s Media Lab put out a study on how AI affects the brain. The study ignited a firestorm of posts and comments on social media, given its provocative finding that students who relied on ChatGPT for writing tasks showed lower brain engagement on EEG scans, hinting that offloading thinking to AI can literally dull our neural activity. For anyone who has used AI, it’s not hard to see how AI systems can become learning crutches that encourage mental laziness.

    But I don’t think a simple “AI harms learning” conclusion tells the whole story. In this blog post (adapted from a recent series of posts I shared on LinkedIn), I want to add to the conversation by tackling the potential impact of AI in education from four angles. I’ll explore how AI’s unique adaptability can reshape rigid systems, how it both fights and fuels misinformation, how AI can be both good and bad depending on how it is used, and why its funding model may ultimately determine whether AI serves learners or short-circuits their growth.

    What if the most transformative aspect of AI for schools isn’t its intelligence, but its adaptability?

    Most technologies make us adjust to them. We have to learn how they work and adapt our behavior. Industrial machines, enterprise software, even a basic thermostat—they all come with instructions and patterns we need to learn and follow.

    Education highlights this dynamic in a different way. How does education’s “factory model” work when students don’t come to school as standardized raw inputs? In many ways, schools expect students to conform to the requirements of the system—show up on time, sharpen your pencil before class, sit quietly while the teacher is talking, raise your hand if you want to speak. Those social norms are expectations we place on students so that standardized education can work. But as anyone who has tried to manage a group of six-year-olds knows, a class of students is full of complicated humans who never fully conform to what the system expects. So, teachers serve as the malleable middle layer. They adapt standardized systems to make them work for real students. Without that human adaptability, the system would collapse.

    Same thing in manufacturing. Edgar Schein notes that engineers aim to design systems that run themselves. But operators know systems never work perfectly. Their job—and often their sense of professional identity—is about having the expertise to adapt and adjust when things inevitably go off-script. Human adaptability in the face of rigid systems keeps everything running.

    So, how does this relate to AI? AI breaks the mold of most machines and systems humans have designed and dealt with throughout history. It doesn’t just follow its algorithm and expect us to learn how to use it. It adapts to us, like how teachers or factory operators adapt to the realities of the world to compensate for the rigidity of standardized systems.

    You don’t need a coding background or a manual. You just speak to it. (I literally hit the voice-to-text button and talk to it like I’m explaining something to a person.) Messy, natural human language—the age-old human-to-human interface that our brains are wired to pick up on as infants—has become the interface for large language models. In other words, what makes today’s AI models amazing is their ability to use our interface, rather than asking us to learn theirs.

    For me, the early hype about “prompt engineering” never really made sense. It assumed that success with AI required becoming an AI whisperer who knew how to speak AI’s language. But in my experience, working well with AI is less about learning special ways to talk to AI and more about just being a clear communicator, just like a good teacher or a good manager.

    Now imagine this: what if AI becomes the new malleable middle layer across all kinds of systems? Not just a tool, but an adaptive bridge that makes other rigid, standardized systems work well together. If AI can make interoperability nearly frictionless—adapting to each system and context, rather than forcing people to adapt to it—that could be transformative. It’s not hard to see how this shift might ripple far beyond technology into how we organize institutions, deliver services, and design learning experiences.

    Consider two concrete examples of how this might transform schools. First, our current system heavily relies on the written word as the medium for assessing students’ learning. To be clear, writing is an important skill that students need to develop to help them navigate the world beyond school. Yet at the same time, schools’ heavy reliance on writing as the medium for demonstrating learning creates barriers for students with learning disabilities, neurodivergent learners, or English language learners—all of whom may have a deep understanding but struggle to express it through writing in English. AI could serve as that adaptive layer, allowing students to demonstrate their knowledge and receive feedback through speech, visual representations, or even their native language, while still ensuring rigorous assessment of their actual understanding.

    Second, it’s obvious that students don’t all learn at the same pace—yet we’ve forced learning to happen at a uniform timeline because individualized pacing quickly becomes completely unmanageable when teachers are on their own to cover material and provide feedback to their students. So instead, everyone spends the same number of weeks on each unit of content and then moves to the next course or grade level together, regardless of individual readiness. Here again, AI could serve as that adaptive layer for keeping track of students’ individual learning progressions and then serving up customized feedback, explanations, and practice opportunities based on students’ individual needs.

    Third, success in school isn’t just about academics—it’s about knowing how to navigate the system itself. Students need to know how to approach teachers for help, track announcements for tryouts and auditions, fill out paperwork for course selections, and advocate for themselves to get into the classes they want. These navigation skills become even more critical for college applications and financial aid. But there are huge inequities here because much of this knowledge comes from social capital—having parents or peers who already understand how the system works. AI could help level the playing field by serving as that adaptive coaching layer, guiding any student through the bureaucratic maze rather than expecting them to figure it out on their own or rely on family connections to decode the system.

    Can AI help solve the problem of misinformation?

    Most people I talk to are skeptical of the idea in this subhead—and understandably so.

    We’ve all seen the headlines: deep fakes, hallucinated facts, bots that churn out clickbait. AI, many argue, will supercharge misinformation, not solve it. Others worry that overreliance on AI could make people less critical and more passive, outsourcing their thinking instead of sharpening it.

    But what if that’s not the whole story?

    Here’s what gives me hope: AI’s ability to spot falsehoods and surface truth at scale might be one of its most powerful—and underappreciated—capabilities.

    First, consider what makes misinformation so destructive. It’s not just that people believe wrong facts. It’s that people build vastly different mental models of what’s true and real. They lose any shared basis for reasoning through disagreements. Once that happens, dialogue breaks down. Facts don’t matter because facts aren’t shared.

    Traditionally, countering misinformation has required human judgment and painstaking research, both time-consuming and limited in scale. But AI changes the equation.

    Unlike any single person, a large language model (LLM) can draw from an enormous base of facts, concepts, and contextual knowledge. LLMs know far more facts from their training data than any person can learn in a lifetime. And when paired with tools like a web browser or citation database, they can investigate claims, check sources, and explain discrepancies.

    Imagine reading a social media post and getting a sidebar summary—courtesy of AI—that flags misleading statistics, offers missing context, and links to credible sources. Not months later, not buried in the comments—instantly, as the content appears. The technology to do this already exists.

    Of course, AI is not perfect as a fact-checker. When large language models generate text, they aren’t producing precise queries of facts; they’re making probabilistic guesses at what the right response should be based on their training, and sometimes those guesses are wrong. (Just like human experts, they also generate answers by drawing on their expertise, and they sometimes get things wrong.) AI also has its own blind spots and biases based on the biases it inherits from its training data. 

    But in many ways, both hallucinations and biases in AI are easier to detect and address than the false statements and biases that come from millions of human minds across the internet. AI’s decision rules can be audited. Its output can be tested. Its propensity to hallucinate can be curtailed. That makes it a promising foundation for improving trust, at least compared to the murky, decentralized mess of misinformation we’re living in now.

    This doesn’t mean AI will eliminate misinformation. But it could dramatically increase the accessibility of accurate information, and reduce the friction it takes to verify what’s true. Of course, most platforms don’t yet include built-in AI fact-checking, and even if they did, that approach would raise important concerns. Do we trust the sources that those companies prioritize? The rules their systems follow? The incentives that guide how their tools are designed? But beyond questions of trust, there’s a deeper concern: when AI passively flags errors or supplies corrections, it risks turning users into passive recipients of “answers” rather than active seekers of truth. Learning requires effort. It’s not just about having the right information—it’s about asking good questions, thinking critically, and grappling with ideas. That’s why I think one of the most important things to teach young people about how to use AI is to treat it as a tool for interrogating the information and ideas they encounter, both online and from AI itself. Just like we teach students to proofread their writing or double-check their math, we should help them develop habits of mind that use AI to spark their own inquiry—to question claims, explore perspectives, and dig deeper into the truth. 

    Still, this focuses on just one side of the story. As powerful as AI may be for fact-checking, it will inevitably be used to generate deepfakes and spin persuasive falsehoods.

    AI isn’t just good or bad—it’s both. The future of education depends on how we use it.

    Much of the commentary around AI takes a strong stance: either it’s an incredible force for progress or it’s a terrifying threat to humanity. These bold perspectives make for compelling headlines and persuasive arguments. But in reality, the world is messy. And most transformative innovations—AI included—cut both ways.

    History is full of examples of technologies that have advanced society in profound ways while also creating new risks and challenges. The Industrial Revolution made it possible to mass-produce goods that have dramatically improved the quality of life for billions. It has also fueled pollution and environmental degradation. The internet connects communities, opens access to knowledge, and accelerates scientific progress—but it also fuels misinformation, addiction, and division. Nuclear energy can power cities—or obliterate them.

    AI is no different. It will do amazing things. It will do terrible things. The question isn’t whether AI will be good or bad for humanity—it’s how the choices of its users and developers will determine the directions it takes. 

    Because I work in education, I’ve been especially focused on the impact of AI on learning. AI can make learning more engaging, more personalized, and more accessible. It can explain concepts in multiple ways, adapt to your level, provide feedback, generate practice exercises, or summarize key points. It’s like having a teaching assistant on demand to accelerate your learning.

    But it can also short-circuit the learning process. Why wrestle with a hard problem when AI will just give you the answer? Why wrestle with an idea when you can ask AI to write the essay for you? And even when students have every intention of learning, AI can create the illusion of learning while leaving understanding shallow.

    This double-edged dynamic isn’t limited to learning. It’s also apparent in the world of work. AI is already making it easier for individuals to take on entrepreneurial projects that would have previously required whole teams. A startup no longer needs to hire a designer to create its logo, a marketer to build its brand assets, or an editor to write its press releases. In the near future, you may not even need to know how to code to build a software product. AI can help individuals turn ideas into action with far fewer barriers. And for those who feel overwhelmed by the idea of starting something new, AI can coach them through it, step by step. We may be on the front end of a boom in entrepreneurship unlocked by AI.

    At the same time, however, AI is displacing many of the entry-level knowledge jobs that people have historically relied on to get their careers started. Tasks like drafting memos, doing basic research, or managing spreadsheets—once done by junior staff—can increasingly be handled by AI. That shift is making it harder for new graduates to break into the workforce and develop their skills on the job.

    One way to mitigate these challenges is to build AI tools that are designed to support learning, not circumvent it. For example, Khan Academy’s Khanmigo helps students think critically about the material they’re learning rather than just giving them answers. It encourages ideation, offers feedback, and prompts deeper understanding—serving as a thoughtful coach, not a shortcut. But the deeper issue AI brings into focus is that our education system often treats learning as a means to an end—a set of hoops to jump through on the way to a diploma. To truly prepare students for a world shaped by AI, we need to rethink that approach. First, we should focus less on teaching only the skills AI can already do well. And second, we should make learning more about pursuing goals students care about—goals that require curiosity, critical thinking, and perseverance. Rather than training students to follow a prescribed path, we should be helping them learn how to chart their own. That’s especially important in a world where career paths are becoming less predictable, and opportunities often require the kind of initiative and adaptability we associate with entrepreneurs.

    In short, AI is just the latest technological double-edged sword. It can support learning, or short-circuit it. Boost entrepreneurship—or displace entry-level jobs. The key isn’t to declare AI good or bad, but to recognize that it’s both, and then to be intentional about how we shape its trajectory. 

    That trajectory won’t be determined by technical capabilities alone. Who pays for AI, and what they pay it to do, will influence whether it evolves to support human learning, expertise, and connection, or to exploit our attention, take our jobs, and replace our relationships.

    What actually determines whether AI helps or harms?

    When people talk about the opportunities and risks of artificial intelligence, the conversation tends to focus on the technology’s capabilities—what it might be able to do, what it might replace, what breakthroughs lie ahead. But just focusing on what the technology does—both good and bad—doesn’t tell the whole story. The business model behind a technology influences how it evolves.

    For example, when advertisers are the paying customer, as they are for many social media platforms, products tend to evolve to maximize user engagement and time-on-platform. That’s how we ended up with doomscrolling—endless content feeds optimized to occupy our attention so companies can show us more ads, often at the expense of our well-being.

    That incentive could be particularly dangerous with AI. If you combine superhuman persuasion tools with an incentive to monopolize users’ attention, the results will be deeply manipulative. And this gets at a concern my colleague Julia Freeland Fisher has been raising: What happens if AI systems start to displace human connection? If AI becomes your go-to for friendship or emotional support, it risks crowding out the real relationships in your life.

    Whether or not AI ends up undermining human relationships depends a lot on how it’s paid for. An AI built to hold your attention and keep you coming back might try to be your best friend. But an AI built to help you solve problems in the real world will behave differently. That kind of AI might say, “Hey, we’ve been talking for a while—why not go try out some of the things we’ve discussed?” or “Sounds like it’s time to take a break and connect with someone you care about.”

    Some decisions made by the major AI companies seem encouraging. Sam Altman, OpenAI’s CEO, has said that adopting ads would be a last resort. “I’m not saying OpenAI would never consider ads, but I don’t like them in general, and I think that ads-plus-AI is sort of uniquely unsettling to me.” Instead, most AI developers like OpenAI and Anthropic have turned to user subscriptions, an incentive structure that doesn’t steer as hard toward addictiveness. OpenAI is also exploring AI-centric hardware as a business model—another experiment that seems more promising for user wellbeing.

    So far, we’ve been talking about the directions AI will take as companies develop their technologies for individual consumers, but there’s another angle worth considering: how AI gets adopted into the workplace. One of the big concerns is that AI will be used to replace people, not necessarily because it does the job better, but because it’s cheaper. That decision often comes down to incentives. Right now, businesses pay a lot in payroll taxes and benefits for every employee, but they get tax breaks when they invest in software and machines. So, from a purely financial standpoint, replacing people with technology can look like a smart move. In the book, The Once and Future Worker, Oren Cass discusses this problem and suggests flipping that script—taxing capital more and labor less—so companies aren’t nudged toward cutting jobs just to save money. That change wouldn’t stop companies from using AI, but it would encourage them to deploy it in ways that complement, rather than replace, human workers.

    Currently, while AI companies operate without sustainable business models, they’re buoyed by investor funding. Investors are willing to bankroll companies with little or no revenue today because they see the potential for massive profits in the future. But that investor model creates pressure to grow rapidly and acquire as many users as possible, since scale is often a key metric of success in venture-backed tech. That drive for rapid growth can push companies to prioritize user acquisition over thoughtful product development, potentially at the expense of safety, ethics, or long-term consequences. 

    Given these realities, what can parents and educators do? First, they can be discerning customers. There are many AI tools available, and the choices they make matter. Rather than simply opting for what’s most entertaining or immediately useful, they can support companies whose business models and design choices reflect a concern for users’ well-being and societal impact.

    Second, they can be vocal. Journalists, educators, and parents all have platforms—whether formal or informal—to raise questions, share concerns, and express what they hope to see from AI companies. Public dialogue helps shape media narratives, which in turn shape both market forces and policy decisions.

    Third, they can advocate for smart, balanced regulation. As I noted above, AI shouldn’t be regulated as if it’s either all good or all bad. But reasonable guardrails can ensure that AI is developed and used in ways that serve the public good. Just as the customers and investors in a company’s value network influence its priorities, so too can policymakers play a constructive role as value network actors by creating smart policies that promote general welfare when market incentives fall short.

    In sum, a company’s value network—who its investors are, who pays for its products, and what they hire those products to do—determines what companies optimize for. And in AI, that choice might shape not just how the technology evolves, but how it impacts our lives, our relationships, and our society.

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