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ST. PAUL, Minn. — At the end of each school year at Central High School, seniors grab a paint pen and write their post-graduation plans on a glass wall outside the counseling office.
For many, that means announcing what college they’ve enrolled in. But the goal is to celebrate whatever path students are choosing, whether at a college or not.
“We have a few people that are going to trade school, we have a few people that are going to the military, a few people who wrote ‘still deciding,’” said Lisa Beckham, a staffer for the counseling center, as she helped hand out markers in May as the school year was winding down. Others, she said, are heading straight to a job.
Talking to the students as they signed, it was clear that one factor played an outsized role in the choice: the high cost of college.
“I’m thinking about going to college in California, and my grandparents all went there for a hundred dollars a semester and went into pretty low-paying jobs, but didn't spend years in debt because it was easy to go to college,” said Maya Shapiro, a junior who was there watching the seniors write up their plans. “So now I think it is only worth going to college if you're going to get a job that's going to pay for your college tuition eventually, so if you’re going to a job in English or history you might not find a job that’s going to pay that off.”
When I told her I was an English major back in my own college years, she quickly said, “I’m sorry.”
Even students going to some of the most well-known colleges are mindful of cost.
Harlow Tong, who was recruited by Harvard University to run track, said he had planned to go to the University of Minnesota and is still processing his decision to join the Ivy League.
“After the decision it really hit me that it's really an investment, and every year it feels like it's getting less and less worth the cost,” he said.
A new book lays out the changing forces shaping what students are choosing after high school, and argues for a change in the popular narrative around higher education.
The book is called “Rethinking College,” by longtime journalist and Los Angeles Times opinion writer Karin Klein. She calls for an end to “degree inflation,” where jobs require a college degree even if someone without a degree could do the job just as well. And she advocates for more high school graduates to take gap years to find out what they want to do before enrolling in college, or to seek out apprenticeships in fields that may not need college.
But she admits the issue is complicated. She said one of her own daughters, who is now 26, would have benefitted from a gap year. “The problem was the cost was a major factor,” Klein told me. “She was offered huge financial aid by a very good school, and I said, ‘We don’t know if you take a gap year if that offer is going to be on the table. And I can’t afford this school without that offer.’”
Hear more from Klein, including about programs she sees as models for new post-grad options, as well as from students at Central High School, on this week’s EdSurge Podcast. Check it out on Spotify, Apple Podcasts, or on the player below. It’s the latest episode of our Doubting College podcast series.
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© Photo by Jeffrey R. Young for EdSurge
Here’s a cool tool you can use to help you find inspiration and enjoyment: The Schoolyard Podcast is a new show from School Specialty and teacher Nancy Chung. Twice each month, host Chung, also known as @FancyNancyin5th on Instagram and TikTok, will be joined by industry experts, fellow educators, and subject matter experts from School Specialty to dive into educational trends, seasonally relevant topics, and emerging and proven solutions to create an entertaining and educational listening experience.
Chung is a fun-loving 5th-grade teacher, former robotics coach, and content creator from Orange County, California, in her 26th year of teaching. She is passionate about sharing her ideas on creative projects, designing intentional learning spaces, teaching highly engaging lessons, building meaningful relationships, and cultivating a community that sparks discovery and inclusion.
Each episode will begin with a thought-provoking introduction by Chung, followed by a conversation between Chung and the episode’s guest. In the final segment, launching in episode 5 and dubbed “Tag, You’re It!,” Chung and the featured guest will answer a question submitted by a listener by tagging @SchoolSpecialty with #schoolyardtagyoureit and their question on Facebook, Instagram, Pinterest, or Twitter. Listeners who have their question answered on the air will receive a free Schoolyard Podcast t-shirt.
The first five episodes explore:
The first five episodes are available now on Apple Music, Spotify, Amazon Music, Samsung Podcasts, Podcast Index, and Listen Notes. Learn more.
The post The Schoolyard Podcast from School Specialty and Nancy Chung appeared first on EdTech Digest.
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Two instructors at Vilnius University in Lithuania brought in some unusual teaching assistants earlier this year: AI chatbot versions of themselves.
The instructors — Paul Jurcys and Goda Strikaitė-Latušinskaja — created AI chatbots trained only on academic publications, PowerPoint slides and other teaching materials that they had created over the years. And they called these chatbots “AI Knowledge Twins,” dubbing one Paul AI and the other Goda AI.
They told their students to take any questions they had during class or while doing their homework to the bots first before approaching the human instructors. The idea wasn’t to discourage asking questions, but rather to nudge students to try out the chatbot doubles.
Would you use an AI teaching assistant? Share your thoughts.
“We introduced them as our assistants — as our research assistants that help people interact with our knowledge in a new and unique way,” says Jurcys.
Experts in artificial intelligence have for years experimented with the idea of creating chatbots that can fill this support role in classrooms. With the rise of ChatGPT and other generative AI tools, there’s a new push to try robot TAs.
“From a faculty perspective, especially someone who is overwhelmed with teaching and needs a teaching assistant, that's very attractive to them — then they can focus on research and not focus on teaching,” says Marc Watkins, a lecturer of writing and rhetoric at the University of Mississippi and director of the university’s AI Summer Institute for Teachers of Writing.
But just because Watkins thought some faculty would like it doesn’t mean he thinks it’s a good idea.
“That's exactly why it's so dangerous too, because it basically offloads this sort of human relationships that we're trying to develop with our students and between teachers and students to an algorithm,” he says.
On this week’s EdSurge Podcast, we hear from these professors about how the experiment went — how it changed classroom discussion but sometimes caused distraction. A student in the class, Maria Ignacia, also shares her view on what it was like to have chatbot TAs.
And we listen in as Jurcys asks his chatbot questions — and admits the bot puts things a bit differently than he would.
Listen to the episode on Spotify, Apple Podcasts, or on the player on this page.
The movement to keep smartphones out of schools is gaining momentum.
Just last week, the nation’s second-largest public school system, Los Angeles Unified School District, voted to ban smartphones starting in January, citing adverse health risks of social media for kids. And the U.S. Surgeon General, Vivek Murthy, published an op-ed in The New York Times calling for warning labels on social media systems, saying “the mental health crisis among young people is an emergency.”
But some longtime teachers say that while such moves are a step in the right direction, educators need to take a more-active role in countering some negative effects of excessive social media use by students. Essentially, they should redesign assignments and how they instruct to help teach mental focus, modeling how to read, write and research away from the constant interruptions of social media and app notifications.
That’s the view of Lee Underwood, a 12th grade AP English literature and composition teacher at Millikan High School in Long Beach, California, who was the teacher of the year for his public school system in 2022.
He’s been teaching since 2006, so he remembers a time before the invention of the iPhone, Instagram or TikTok. And he says he is concerned by the change in behavior among his students, which has intensified in recent years.
“There is a lethargy that didn't exist before,” he says. “The responses of students were quicker, sharper. There was more of a willingness to engage in our conversations, and we had dynamic conversations.”
He tried to keep up his teaching style, which he feels had been working, but responses from students were different. “The last three years, four years since COVID, my jokes that I tell in my classroom have not been landing,” he says. “And they're the same jokes.”
Underwood has been avidly reading popular books and articles about the impact of smartphones on today’s young people. For instance, he read the much-talked-about book by Jonathan Haidt, “The Anxious Generation,” that has helped spark many recent efforts by schools to do more to counter the consequences of smartphones and social media.
Some have countered Haidt’s arguments, however, by pointing out that while young people face growing mental health challenges, there is little scientific evidence that social media is causing those issues. And just last month on this podcast, Ellen Galinsky, author of a book on what brain science reveals about how best to teach teens, argued that banning social media might backfire, and that kids need to learn how to regulate smartphone use on their own to prepare them for the world beyond school.
“Evidence shows very, very clearly that the ‘just say no’ approach in adolescence — where there's a need for autonomy — does not work,” she said. “In the studies on smoking, it increased smoking.”
Yet Underwood argues that he has felt the impact of social media on his concentration and focus firsthand. And these days he’s changing what he does in the classroom to bring in techniques and strategies that helped him counter the negative impacts of smartphones he experienced.
And he has a strong reaction to Galinsky’s argument.
“We don't let kids smoke in school,” he points out. “Maybe some parts of the ‘just say no campaigns’ broadly didn't work, but then no one's allowing smoking in schools.”
His hope is that the school day can be reserved as a time where students know they can get away from the downsides of smartphone and social media use.
“That's six hours of a school day where you can show a student, bring them to a kind of homeostasis, where they can see what it would be like without having that constant distraction,” he argues.
Hear the full conversation, as well as examples of how he’s redesigned his lessons, on this week’s episode. Listen on Apple Podcasts, Overcast, Spotify, or wherever you listen to podcasts, or use the player on this page.
© autumnn / Shutterstock
Last year, when Jayla Arensberg was a sophomore at Burnsville High School near St. Paul, Minnesota, a teacher showed her a flier saying that a program at the school could save her $25,000 on college.
“I said, ‘I really need that,’” the student remembers.
She was interested in college, but worried that the cost could keep her from pursuing higher education. “College is insanely expensive,” she says.
So she applied and got accepted to the high school’s “Associate of Arts Degree Pathway,” which essentially turns junior and senior year of high school into a two-year college curriculum. All this year, Arensberg walked the halls of the same high school building and ate in the same cafeteria as before, but now most of her classes earned her college credit, and if she stays on track, she’ll get an associate degree at the same time she receives her high school diploma.
Her plan after graduation is to apply to the University of Minnesota’s main campus to major in psychology, entering halfway to her bachelor’s degree and thereby cutting out two years of paying for college.
The high school is one of a growing number around the country offering a so-called “postsecondary enrollment option,” where students can take college courses during the high school day and get college credit. In fact, the number of high school students taking at least one college course has risen to 34 percent, up from just 10 percent in 2010, according to data from the National Alliance of Concurrent Enrollment Partnerships.
But Burnsville’s program is unusual in offering a full two-year program within its building, rather than just isolated courses or transportation to nearby colleges for part of a day.
“They really are cohorted like they would probably feel in a freshman dorm,” says Rebecca Akerson, who coordinates the Associate of Arts pathway program at the school, of the students in the program, who take most of their courses together. “They’ve gotten to know each other well. When you think about college, that’s what you’re thinking about.”
It’s a stark example of how the line between high school and college is blurring for more students. While such programs may help students access college who may not have been able to before, they also raise questions about the purpose of high school, about what social opportunities might be lost, and about whether the trend pushes students to make decisions about their future careers at too young of an age.
But college is not the only option that students can get a jump on exploring at this high school. The associate degree program is part of one of four career pathways that students can choose, pointing to careers in specialties like culinary arts, manufacturing and automotive technology.
In fact, officials have gone out of their way to highlight the variety of options, to try to attract greater diversity of students to whatever they might be interested in. For instance, the school’s “fabrication lab” — which once might have been called wood shop — is located adjacent to a high-traffic commons area, and glass walls allow anyone walking by to see what the students are doing.
“This was designed very specifically because engineering and fabrication have traditionally been a very white, male-dominated career field,” says Kathy Funston, director of strategic partnerships and pathways for the Burnsville school district. “We really did want our students of color and our females to be able to look through these glass walls and say, ‘That’s cool. I like that. Nobody’s getting dirty in there. I think I want to try that,’” Funston adds. “So it’s a way to help underrepresented populations see career areas and career fields that they would not have been exposed to either in their sphere of influence at home or at other classes. If you go to a lot of other schools these types of classes have been in a remote part of the school.”
Teachers at the school say that they work to communicate these career pathway programs early and often. That means the pathway options are a big part of the tour when middle school students look at the school, and posters featuring the four main career pathways, each with its signature color, adorn hallways throughout the building.
How is the program going? And how do students feel about these options at a time of growing skepticism about higher education?
This is the fifth episode of a podcast series we’re calling Doubting College, where we’re exploring: What happened to the public belief in college? And how is that shaping the choices young people are making about what to do after high school?
Listen to the episode on Apple Podcasts, Overcast, Spotify, YouTube or wherever you listen to podcasts, or use the player on this page.
© Photo by Jeffrey R. Young for EdSurge
Should AI chatbots be used as tutors?
That question has been in the air since ChatGPT was released in late 2022, and since then many developers have experimented with using the latest generative AI technology as a tutor. But not everyone thinks this is a good idea, since the tech is prone to “hallucinations,” where chatbots make up facts, and there’s the bigger issue of whether any machine can fill in for a human in something as deeply personal as one-on-one tutoring.
A video demo of the latest version of ChatGPT tutoring a student that went viral on YouTube has brought fresh attention to this question. In it, Sal Khan, founder of Khan Academy, which has been building a tutoring tool with ChatGPT, sits watching his 15-year old son Imran learn a math concept from a talking version of the chatbot running on an iPad, which can also see what the student is typing on the tablet. As Sal Khan looks on nodding, the chatbot asks his son a question in a friendly female voice about triangles, and Imran answers while indicating which side of the triangle he means using a stylus and tapping on the iPad screen. It’s an interaction that might have seemed like science fiction a couple of years ago. (And that level of functionality isn’t yet available for users.)
Khan has become one of the most well-known boosters of using generative AI for tutoring, and he has a new book that makes an enthusiastic case for it. The book is called “Brave New Words: How AI Will Revolutionize Education (and Why That's a Good Thing).”
But his book, and that demo, are also attracting some pushback from teaching experts who think AI may have lots of uses in education, but that tutoring should be reserved for humans who can motivate and understand the students they work with.
For this week’s EdSurge Podcast, we talked with Khan to hear more about his vision of AI tutors and the arguments from his recent book. And we also heard from Dan Meyer, vice president of user growth at Amplify, a curriculum and assessment company, who writes a newsletter about teaching mathematics where he has raised objections to the idea of using AI chatbots as tutors.
“The kind of math that we saw on there,” Meyer said, referring to the demo, “was an operational problem well summarized in a single diagram that results in a single number. And those have always been the kind of problems that computers have supported students fairly nimbly in solving.” The bigger question, he argues, will be how such chatbots will handle more conceptual problems. And, he asks how well such bots will work “for the average student who's dealing with distraction and feeling socially isolated and not interested in talking to Scarlett-Johansson-esque voices as a tutor bot?”
Hear the full conversation on this week’s episode. Listen on Apple Podcasts, Overcast, Spotify, or wherever you listen to podcasts, or use the player on this page. Or read a partial transcript below, lightly edited for clarity.
EdSurge: When we last talked with you for the podcast, Khan Academy had just released your group’s chatbot tutor, Khanmigo. At the time you were rolling it out slowly because there were many questions about using AI chatbots in education. What was your biggest worry then, and how did the testing go?
Sal Khan: When we launched back in March of 2023, I think the biggest worry was how we would be received by the education community. This was only three or four months after ChatGPT had been released. And obviously the reception to ChatGPT was not a positive one, for good reason. It could be used to cheat. It had no guardrails on it. It was making math errors. It was hallucinating. And so here we are, an education nonprofit that hopefully a lot of folks trust to have high-quality work. And then people might say, ‘Hey, wow, Khan Academy is going with both feet into this AI thing.’
The good news is that the reception was actually more positive than we expected. So four or five months after the release of ChatGPT, most school systems, most educators were saying, ‘You know what, ChatGPT still is a little bit shady for education purposes, but the underlying technology of it is really potentially powerful for helping kids learn the things that we've always tried to teach them, and this type of technology is going to be part of their future. So we should think about how we can expose kids to it, but in a way that it doesn't cheat, in a way that there's guardrails, in the way that we can make sure that everything's on the up-and-up on data security and privacy and that it's pedagogically designed.’
And so when we were able to come with Khanmigo at around that time, the reception has been very positive.
I'll say it's also been a bit of a transition internally at Khan Academy because it is a new muscle that we've been building. … We've always worked on software that personalizes things, videos — I still make videos — and exercises, teacher tools, in a more traditional sense, and now we're moving toward this artificial intelligence world. That is exciting, but it also has a lot of things to keep in consideration. I think it's also been a bit of a transition for our team to feel good and confident and comfortable with where we're going.
It sounds like Khan Academy will continue to make videos?
The rate of change of artificial intelligence is so fast that it feels like it's irresponsible if we don't have these conversations like, ‘How long will Khan Academy videos be relevant?’ A lot of folks probably saw the recent OpenAI demo of me and my son. Will a student find value in a Khan Academy video in that world, or as much value?
A lot of our resources historically have been creating these really high-quality exercises. We've created over 100,000 exercise items on Khan Academy, and that takes a lot of resources. Today, the AI is not good enough to create exercises that are high quality, aligned to standards and are error-free.
So AI is not replacing your job of making educational videos?
My vanity wants to say no, but I don't know. I don't know.
I do want to be clear. I think the safest job in all of this is that of the teacher. I make that very clear in my book, and I'm not just saying it because people want to hear it, but it's that human element of it all being in the room helping guide students, keeping them on task, and you need to be physically there to really, truly keep them on task, to forge those human connections. …
But I think a lot of the other pieces that edtech has traditionally worked on or even other parts of the education system, maybe some of the more administrative tasks, I think it is important for everyone to be wondering how AI might change that.
You note in your book that back when you were an undergraduate at MIT, you originally wanted to be an AI researcher. Why were you drawn to that area?
I've always been fascinated by, ‘What could we learn potentially from technology?’ And I've always read a lot of science fiction books about maybe that could start pushing the frontiers of and even helping us understand what is intelligence and what is consciousness. But I've also been fascinated by the potential of human intelligence. And I've also always been fascinated by the intersection of the two.
And yes, when I was a freshman at MIT, I sought out for my freshman adviser and he ended up being my freshman adviser, Patrick Henry Winston, who was head of the artificial intelligence laboratory. I got in line to take a course with Marvin Minsky and got in. And so if you asked me in 1994 or 1995 what I wanted to do, I would say, ‘Yeah, I might want to be an AI researcher.’
Back then it sounds like you were discouraged by the level of technology at the time, but clearly we’re in a new phase of AI development. Do you think AI is now ready to serve as a viable tutor?
I think it can already do parts of it. I don't think it's able to do the full job, but I think that the technology is improving so fast that you definitely will never say never. And in fact, a lot of things that seem like science fiction are going to be reality in about two years.
[At Khan Academy] we've always been trying to use technology to approximate what a great tutor would do in terms of personalized learning and then also leverage technology to scale that to as many people as possible. And we've never viewed this as somehow a substitute for a teacher. In fact, we said, ‘Hey, this could be really valuable in a teaching setting.’ In fact, it's most valuable in a teaching setting because a teacher's in a class of 30, these kids are at all different levels. Every teacher knows that. How do you address their individual needs? Well, if you had support from a teaching assistant who's also their tutor, that's kind of what Khan Academy has always aspired to be.
I talked with a technologist who worked at IBM and had worked on IBM's Watson many years ago and was asked to use it to build an AI tutor. But after years of work he concluded that it can’t be done, and that it’s not the best way to use AI in education. What would you say to that argument?
Actually when you talk to a lot of the AI researchers, and we've probably helped skew this conversation, the thing that they're most excited about for the next generation models is the tutoring use case because people understand it's a socially positive use case. Obviously there's a bunch of negative use cases of AI — deepfakes, fraud, etc.
I think you've had many people work on this problem for decades using more basic forms of artificial intelligence. I encourage that researcher to watch that video of the GPT-4o tutoring demo with myself and my son.
Dan Meyer recently wrote that while these AI tutors might work for a small percentage of students, most need the kind of human relationship that just can’t be replicated with AI right now. Will a broad range of students want the kind of Khanmigo tutor you show in your demo?
I mean, I think most kids would rather chat or talk to their friends than go to school altogether, than sit through a lecture, than do their homework, etc. And this is why one of the many important things that a teacher does is make sure that students are focused and engaged on the thing that matters most.
There's a broad group of students that, in the moment where they need to understand a concept, where this can be very useful for them. I agree that it's a subset of students, let's call it 10 or 15 percent of students who have maintained their curiosity and might automatically keep going to the AI. And for those students, this is a field day, this is a playground, this is awesome for them. I think there's a broader set of students who are broadly disengaged from what they're doing, and you need to figure out ways to engage them more. And this is one of the many reasons why we view involving teachers in this journey as so important. Letting them know what's going on with the AI. We're working on them being able to assign AI-based activities.
There’s a passage in your book where you describe Khanmigo having a session with a student and then reporting back to their teacher, and you write it might go say something like, “We worked on the paper for about four hours. Sal initially had trouble coming up with a thesis, but I was able to help him by asking some leading questions. The outlining went pretty smoothly. I just had to help him ensure that the conclusion really brought everything together. … based on the rubric for the assignment, I'd recommend Sal get a B plus on the assignment. Here is a detailed breakdown of how I rated this paper in the dimensions of the rubric.” In some ways, this doesn’t leave much left for the teacher to do. What would you say to teachers who worry AI could replace them?
I think every K-12 teacher will look at tenured professors at the local university with envy because those professors have a lot of support. They have these grad students who essentially do exactly what that example the AI was doing. So if you told every teacher in America, ‘Hey, we just found some money and we're going to use it to hire some amazing teaching assistants that can help you write lesson plans, create rubrics, tutor your students, report back to you, what's going on and do preliminary grading. You're still the teacher, you're in charge, but it'll save you the teacher 10, 15 hours of your week. Do you want that?’ And I think the great majority of teachers will say, ‘Hallelujah. Yes, I definitely want that.’ I'm serious that I don't think it in any way undermines the teacher. I think it elevates the teacher.
Back to that recent demo of the next-generation AI tutor. I’ve heard that your son already knew the material being asked and was sort of role-playing there.
Yeah, OpenAI said, ‘Hey, can you bring with you a student who can sign a media release who doesn't work for one of our competitors?’ And I was like, I guess I'm going to bring my son. But yeah, my son, to his credit, he's more low-ego than I am. I mean, he took calculus in seventh grade. He knows what a hypotenuse is. But it made a better demo for him to pretend that he did not know a hypotenuse is because it corrected him, etc.
But yeah, it is powerful to see it in action with a student where it can see what they're drawing and what they're saying, and it's interacting verbally in a very natural way.
How long until the technology in that demo is actually fully functional in your tutoring chatbot?
I think we're a year or a year and a half away from that. But even then to the earlier part of our conversation, even when it's that awesome, I don't know if every student in the world is just going to run to it.
We have a nonprofit called Schoolhouse.world, which gives free live tutoring over Zoom. But still, not every student who finds out about it runs to it. So the AIs are going to get better. There's going to be other things like Schoolhouse World. But we're still going to need engaged parents and teachers that can help motivate and drive kids to get the help that they need.
Stephen Cass: Hello. I’m Stephen Cass, Special Projects Director at IEEE Spectrum. Before starting today’s episode hosted by Eliza Strickland, I wanted to give you all listening out there some news about this show.
This is our last episode of Fixing the Future. We’ve really enjoyed bringing you some concrete solutions to some of the world’s toughest problems, but we’ve decided we’d like to be able to go deeper into topics than we can in the course of a single episode. So we’ll be returning later in the year with a program of limited series that will enable us to do those deep dives into fascinating and challenging stories in the world of technology. I want to thank you all for listening and I hope you’ll join us again. And now, on to today’s episode.
Eliza Strickland: Hi, I’m Eliza Strickland for IEEE Spectrum‘s Fixing the Future podcast. Before we start, I want to tell you that you can get the latest coverage from some of Spectrum’s most important beats, including AI, climate change, and robotics, by signing up for one of our free newsletters. Just go to spectrum.IEEE.org/newsletters to subscribe.
Around the world, about 60 countries are contaminated with land mines and unexploded ordnance, and Ukraine is the worst off. Today, about a third of its land, an area the size of Florida, is estimated to be contaminated with dangerous explosives. My guest today is Gabriel Steinberg, who co-founded both the nonprofit Demining Research Community and the startup Safe Pro AI with his friend, Jasper Baur. Their technology uses drones and artificial intelligence to radically speed up the process of finding land mines and other explosives. Okay, Gabriel, thank you so much for joining me on Fixing the Future today.
Gabriel Steinberg: Yeah, thank you for having me.
Strickland: So I want to start by hearing about the typical process for demining, and so the standard operating procedure. What tools do people use? How long does it take? What are the risks involved? All that kind of stuff.
Steinberg: Sure. So humanitarian demining hasn’t changed significantly. There’s been evolutions, of course, since its inception and about the end of World War I. But mostly, the processes have been the same. People stand from a safe location and walk around an area in areas that they know are safe, and try to get as much intelligence about the contamination as they can. They ask villagers or farmers, people who work around the area and live around the area, about accidents and potential sightings of minefields and former battle positions and stuff. The result of this is a very general idea, a polygon, of where the contamination is. After that polygon and some prioritization based on danger to civilians and economic utility, the field goes into clearance. The first part is the non-technical survey, and then this is clearance. Clearance happens one of three ways, usually, but it always ends up with a person on the ground basically doing extreme gardening. They dig out a certain standard amount of the soil, usually 13 centimeters. And with a metal detector, they walk around the field and a mine probe. They find the land mines and nonexploded ordnance. So that always is how it ends.
To get to that point, you can also use mechanical assets, which are large tillers, and sometimes dogs and other animals are used to walk in lanes across the contaminated polygon to sniff out the land mines and tell the clearance operators where the land mines are.
Strickland: How do you hope that your technology will change this process?
Steinberg: Well, my technology is a drone-based mapping solution, basically. So we provide a software to the humanitarian deminers. They are already flying drones over these areas. Really, it started ramping up in Ukraine. The humanitarian demining organizations have started really adopting drones just because it’s such a massive problem. The extent is so extreme that they need to innovate. So we provide AI and mapping software for the deminers to analyze their drone imagery much more effectively. We hope that this process, or our software, will decrease the amount of time that deminers use to analyze the imagery of the land, thereby more quickly and more effectively constraining the areas with the most contamination. So if you can constrain an area, a polygon with a certainty of contamination and a high density of contamination, then you can deploy the most expensive parts of the clearance process, which are the humans and the machines and the dogs. You can deploy them to a very specific area. You can much more cost-effectively and efficiently demine large areas.
Strickland: Got it. So it doesn’t replace the humans walking around with metal detectors and dogs, but it gets them to the right spots faster.
Steinberg: Exactly. Exactly. At the moment, there is no conception of replacing a human in demining operations, and people that try to push that eventuality are usually disregarded pretty quickly.
Strickland: How did you and your co-founder, Jasper, first start experimenting with the use of drones and AI for detecting explosives?
Steinberg: So it started in 2016 with my partner, Jasper Baur, doing a research project at Binghamton University in the remote sensing and geophysics lab. And the project was to detect a specific anti-personnel land mine, the PFM-1. Then found— it’s a Russian-made land mine. It was previously found in Afghanistan. It still is found in Afghanistan, but it’s found in much higher quantities right now in Ukraine. And so his project was to detect the PFM-1 anti-personnel land mine using thermal imagery from drones. It sort of snowballed into quite an intensive research project. It had multiple papers from it, multiple researchers, some awards, and most notably, it beat NASA at a particular Tech Briefs competition. So that was quite a morale boost.
And at some point, Jasper had the idea to integrate AI into the project. Rightfully, he saw the real bottleneck as not the detecting of land mines in drone imagery, but the analysis of land mines in drone imagery. And that really has become— I mean, he knew, somehow, that that would really become the issue that everybody is facing. And everybody we talked to in Ukraine is facing that issue. So machine learning really was the key for solving that problem. And I joined the project in 2018 to integrate machine learning into the research project. We had some more papers, some more presentations, and we were nearing the end of our college tenure, of our undergraduate degree, in 2020. So at that time– but at that time, we realized how much the field needed this. We started getting more and more into the mine action field, and realizing how neglected the field was in terms of technology and innovation. And we felt an obligation to bring our technology, really, to the real world instead of just a research project. There were plenty of research projects about this, but we knew that it could be more and that it should. It really should be more. And we felt we had the– for some reason, we felt like we had the capability to make that happen.
So we formed a nonprofit, the Demining Research Community, in 2020 to try to raise some funding for this project. Our for-profit end of that, of our endeavors, was acquired by a company called Safe Pro Group in 2023. Yeah, 2023, about one year ago exactly. And the drone and AI technology became Safe Pro AI and our flagship product spotlight. And that’s where we’re bringing the technology to the real world. The Demining Research Community is providing resources for other organizations who want to do a similar thing, and is doing more research into more nascent technologies. But yeah, the real drone and AI stuff that’s happening in the real world right now is through Safe Pro.
Strickland: So in that early undergraduate work, you were using thermal sensors. I know now the Spotlight AI system is using more visual. Can you talk about the different modalities of sensing explosives and the sort of trade-offs you get with them?
Steinberg: Sure. So I feel like I should preface this by saying the more high tech and nascent the technology is, the more people want to see it apply to land mine detection. But really, we have found from the problems that people are facing, by far the most effective modality right now is just visual imagery. People have really good visual sensors built into their face, and you don’t need a trained geophysicist to observe the data and very, very quickly get actionable intelligence. There’s also plenty of other benefits. It’s cheaper, much more readily accessible in Ukraine and around the world to get built-in visual sensors on drones. And yeah, just processing the data, and getting the intelligence from the data, is way easier than anything else.
I’ll talk about three different modalities. Well, I guess I could talk about four. There’s thermal, ground penetrating radar, magnetometry, and lidar. So thermal is what we started with. Thermal is really good at detecting living things, as I’m sure most people can surmise. But it’s also pretty good at detecting land mines, mostly large anti-tank land mines buried under a couple millimeters, or up to a couple centimeters, of soil. It’s not super good at this. The research is still not super conclusive, and you have to do it at a very specific time of day, in the morning and at night when, basically the soil around the land mine heats up faster than the land mine and you cause a thermal anomaly, or the sun causes a thermal anomaly. So it can detect things, land mines, in some amount of depth in certain soils, in certain weather conditions, and can only detect certain types of land mines that are big and hefty enough. So yeah, that’s thermal.
Ground penetrating radar is really good for some things. It’s not really great for land mine detection. You have to have really expensive equipment. It takes a really long time to do the surveys. However, it can get plastic land mines under the surface. And it’s kind of the only modality that can do that with reliability. However, you need to train geophysicists to analyze the data. And a lot of the time, the signatures are really non-unique and there’s going to be a lot of false positives. Magnetometry is the other-- by the way, all of this is airborne that I’m referring to. Ground-based GPR and magnetometry are used in demining of various types, but airborne is really what I’m talking about.
For magnetometry, it’s more developed and more capable than ground penetrating radar. It’s used, actually, in the field in Ukraine in some scenarios, but it’s still very expensive. It needs a trained geophysicist to analyze the data, and the signatures are non-unique. So whether it’s a bottle can or a small anti-personnel land mine, you really don’t know until you dig it up. However, I think if I were to bet on one of the other modalities becoming increasingly useful in the next couple of years, it would be airborne magnetometry.
Lidar is another modality that people use. It’s pretty quick, also very expensive, but it can reliably map and find surface anomalies. So if you want to find former fighting positions, sometimes an indicator of that is a trench line or foxholes. Lidar is really good at doing that in conflicts from long ago. So there’s a paper that the HALO Trust published of flying a lidar mission over former fighting positions, I believe, in Angola. And they reliably found a former trench line. And from that information, they confirmed that as a hazardous area. Because if there is a former front line on this position, you can pretty reliably say that there is going to be some explosives there.
Strickland: And so you’ve done some experiments with some of these modalities, but in the end, you found that the visual sensor was really the best bet for you guys?
Steinberg: Yeah. It’s different. The requirements are different for different scenarios and different locations, really. Ukraine has a lot of surface ordnance. Yeah. And that’s really the main factor that allows visual imagery to be so powerful.
Strickland: So tell me about what role machine learning plays in your Spotlight AI software system. Did you create a model trained on a lot of— did you create a model based on a lot of data showing land mines on the surface?
Steinberg: Yeah. Exactly. We used real-world data from inert, non-explosive items, and flew drone missions over them, and did some physical augmentation and some programmatic augmentation. But all of the items that we are training on are real-life Russian or American ordnance, mostly. We’re also using the real-world data in real minefields that we’re getting from Ukraine right now. That is, obviously, the most valuable data and the most effective in building a machine learning model. But yeah, a lot of our data is from inert explosives, as well.
Strickland: So you’ve talked a little bit about the current situation in Ukraine, but can you tell me more about what people are dealing with there? Are there a lot of areas where the battle has moved on and civilians are trying to reclaim roads or fields?
Steinberg: Yeah. So the fighting is constantly ongoing, obviously, in eastern Ukraine, but I think sometimes there’s a perspective of a stalemate. I think that’s a little misleading. There’s lots of action and violence happening on the front line, which constantly contaminates, cumulatively, the areas that are the front line and the gray zone, as well as areas up to 50 kilometers back from both sides. So there’s constantly artillery shells going into villages and cities along the front line. There’s constantly land mines, new mines, being laid to reinforce the positions. And there’s constantly mortars. And everything is constant. In some fights—I just watched the video yesterday—one of the soldiers said you could not count to five without an explosion going off. And this is just one location in one city along the front. So you can imagine the amount of explosive ordnance that are being fired, and inevitably 10, 20, 30 percent of them are sometimes not exploding upon impact, on top of all the land mines that are being purposely laid and not detonating from a vehicle or a person. These all just remain after the war. They don’t go anywhere. So yeah, Ukraine is really being littered with explosive ordnance and land mines every day.
This past year, there hasn’t been terribly much movement on the front line. But in the Ukrainian counteroffensive in 2020— I guess the last major Ukrainian counteroffensive where areas of Mykolaiv, which is in the southeast, were reclaimed, the civilians started repopulating the city almost immediately. There are definitely some villages that are heavily contaminated, that people just deserted and never came back to, and still haven’t come back to after them being liberated. But a lot of the areas that have been liberated, they’re people’s homes. And even if they’re destroyed, people would rather be in their homes than be refugees. And I mean, I totally understand that. And it just puts the responsibility on the deminers and the Ukrainian government to try to clear the land as fast as possible. Because after large liberations are made, people want to come back almost all the time. So it is a very urgent problem as the lines change and as land is liberated.
Strickland: And I think it was about a year ago that you and Jasper went to the Ukraine for a technology demonstration set up by the United Nations. Can you tell about that, and what the task was, and how your technology fared?
Steinberg: Sure. So yeah, the United Nations Development Program invited us to do a demonstration in northern Ukraine to see how our technology, and other technologies similar to it, performed in a military training facility in Ukraine. So everybody who’s doing this kind of thing, which is not many people, but there are some other organizations, they have their own metrics and their own test fields— not always, but it would be good if they did. But the UNDP said, “No, we want to standardize this and try to give recommendations to the organizations on the ground who are trying to adopt these technologies.” So we had five hours to survey the field and collect as much data as we could. And then we had 72 hours to return the results. We—
Strickland: Sorry. How big was the field?
Steinberg: The field was 25 hectares. So yeah, the audience at home can type 25 hectares to amount of football fields. I think it’s about 60. But it’s a large area. So we’d never done anything like that. That was really, really a shock that it was that large of an area. I think we’d only done half a hectare at a time up to that point. So yeah, it was pretty daunting. But we basically slept very, very little in those 72 hours, and as a result, produced what I think is one of the best results that the UNDP got from that test. We didn’t detect everything, but we detected most of the ordnance and land mines that they had laid. We also detected some that they didn’t know were there because it was a military training facility. So there were some mortars being fired that they didn’t know about.
Strickland: And I think Jasper told me that you had to sort of rewrite your software on the fly. You realized that the existing approach wasn’t going to work and you had to do some all-nighter to recode?
Steinberg: Yeah. Yeah, I remember us sitting in a Georgian restaurant— Georgia, the country, not the state, and racking our brain, trying to figure out how we were going to map this amount of land. We just found out how big the area was going to be and we were a little bit stunned. So we devised a plan to do it in two stages. The first stage was where we figured out in the drone images where the contaminated regions were. And then the second stage was to map those areas, just those areas. Now, our software can actually map the whole thing, and pretty casually too. So not to brag. But at the time, we had lots less development under our belt. And yeah, therefore we just had to brute force it through Georgian food and brainpower.
Strickland: You and Jasper just got back from another trip to the Ukraine a couple of weeks ago, I think. Can you talk about what you were doing on this trip, and who you met with?
Steinberg: Sure. This trip was much less stressful, although stressful in different ways than the UNDP demo. Our main objectives were to see operations in action. We had never actually been to real minefields before. We’d been in some perhaps contaminated areas, but never in a real minefield where you can say, “Here was the Russian position. There are the land mines. Do not go there.” So that was one of the main objectives. That was very powerful for us to see the villages that were destroyed and are denied to the citizens because of land mines and unexploded ordnance. It’s impossible to describe how that feels being there. It’s really impactful, and it makes the work that I’m doing feel not like I have a choice anymore. I feel very much obligated to do my absolute best to help these people.
Strickland: Well, I hope your work continues. I hope there’s less and less need for it over time. But yeah, thank you for doing this. It’s important work. And thanks for joining me on Fixing the Future.
Steinberg: My pleasure. Thank you for having me.
Strickland: That was Gabriel Steinberg speaking to me about the technology that he and Jasper Baur developed to help rid the world of land mines. I’m Eliza Strickland, and I hope you’ll join us next time on Fixing the Future.
Ellen Galinsky has been on a seven-year quest to understand what brain science says about how to better teach and parent adolescent children. The past few years have seen advancements in our understanding of this time — where the brain is going through almost as much change as during the earliest years of a child’s life.
In the past, Galinsky says, researchers and educators have focused too much on portraying the emotional turmoil and risky decision-making that is typical in adolescence as negative. “The biggest breakthrough,” she argues, “is that we now understand that what we saw as problematic, what we saw as deviant, what we saw as immature, was in fact a developmental necessity.”
For her research, Galinsky, who is co-founder of the nonprofit and nonpartisan Families and Work Institute, also surveyed nearly 2,000 parents and students, and found that a large percentage of parents looked at teenage years as a negative time that would be fraught, while students felt they were unfairly stereotyped and misunderstood. She’s gathered her results in a new book, “The Breakthrough Years: A New Scientific Framework for Raising Thriving Teens.”
What her findings mean for educators, she argues, is that lessons for adolescents should be designed to lean into this period of human development.
“Adolescence is a time when young people are moving out into the world — think of the baby bird as leaving the nest,” she says. “And it's important for them to be exploratory. They react very strongly to experiences because they need to understand what's safe, what's not safe, whom they can trust, whom they can't trust, where they belong, where they don't belong, and who they want to be and who they are in a world that is much extended from their families.”
She hopes to reframe this period of development as what she calls “a time of possibility.”
And the work has led her to strong views on the question of whether or not to ban smartphones in schools.
Hear the full conversation on this week’s episode. Listen on Apple Podcasts, Overcast, Spotify, or wherever you listen to podcasts, or use the player on this page. Or read a partial transcript below, lightly edited for clarity.
EdSurge: What's happening in the brain in this phase of human development?
Ellen Galinsky: I love the analogy that Jennifer Silvers from UCLA used. She talked about it as a time when you're laying new roads. And what that means is that the connections among different parts of the brain are being formed and strengthened during adolescence, and she says if it's a stormy day, sometimes the concrete can get wet and mucky and messy, and that's the emotionality of adolescence.
But it is a time when these new connections are being made that help develop particularly what we call executive function skills. And that is a name that I find is pretty misunderstood. If people know it at all, it sounds like, ‘Shut up, sit still, listen to the teacher, be compliant, obey, organize your notebook, remember to bring your homework’ — those kinds of managerial skills. And in part that’s true, these are the brain-based skills that underlie our ability to set goals.
But executive function skills are always driven by goals. It's a time when we can then understand the landscape, the social landscape that we're in. We can understand our own perspective, the perspectives of others and how those differ from our own perspective. It's a time when we learn to communicate. I don't mean just talk, talk, talk. I mean thinking about what we say and better understanding how it's going to be heard by others. It's a time when we can learn to collaborate, which means dealing with the conflict that relationships with people and collaborating can bring.
This country could use a little executive function skills right now and learning how to collaborate. It's a time when we learn how to problem-solve, and that has different components — including making meaning of the situation, thinking creatively in terms of solutions, not just what you've always done, but how might I solve this in a different way? And then understanding what works or what wouldn't work about that solution.
In other words, evaluating solutions, or relational reasoning as it's called in the literature. And then critical thinking, like making a decision on the basis of what you think is valid and accurate information and going forth in implementing that decision. It's also a time when we learn how to take on challenges. Now, there are some core skills, brain-based skills that underlie this, and in addition to people thinking that executive function skills are ‘shut up, you still listen to the teacher, listen to the parents,’ also people think of them as, sometimes, soft skills. These are the most neurocognitive skills we have. They're the part of the brain that coordinates our social, emotional and behavioral capacities in order to achieve goals.
There is this idea that school is mainly for academic content and that's what is usually measured on statewide tests of performance. But it sounds like you're arguing that soft skills are even more important in the teen years than academic skills.
I think they're called soft skills to differentiate them from academic skills, but they're not soft. They're really hard skills. They are pulling together all of our capacities so that we can achieve what we want to achieve and live intentionally. So these are very strongly neurocognitive skills and not something soft and squishy that is beside the point.
We tend to think of learning in the early years as about numbers and letters and math and learning to read. And those sorts of things are critical, but these soft skills are the skills that help us learn those numbers and letters and learning how to do math and learning how to read.
So we have 20 years of research that shows that these soft skills are more predictive of success in school and in life. These skills are more predictive than or as predictive as IQ or socioeconomic status, which are the big things in predicting how well we do in life.
You talk about something I haven’t heard much, which is that schools are often too future-focused, and you quote a 16-year-old who says: “I feel like everything is for the future. In middle school, everyone's pressuring you to be ready for high school. In high school, everyone's pressuring you to be ready for college. In college, everyone's pressuring you to be ready for life.” Can you say more about this?
I can go back historically to 1992 when the first President Bush created educational goals, and the first educational goal was that young children will be ready for school. And that, I think at least in my many years in education, ushered in the period of ‘readiness.’ And we became ready for school and then ready for college and then ready for life. And they work in the sense that people got it that it was a way of understanding the importance of education.
But it has had its downside, I think. Adults have to learn to live in the now. Think about how many books are written to help us as grown-ups be in the present, pay attention to whom we're with. Not always be focusing on our to-do list and what's in the future.
Readiness is important. I'm not throwing the baby out with the bath water. But we need to be in the nowness, too. We need to be able to help children live these years. In that particular group where you just quoted a 16-year-old, another 16-year-old said, ‘My parents are always saying, these are the best years of my life. But why can't I live them? They want to go back to them, but they're not letting me live them now.’
I have to ask you about a big topic in the news these days, about whether to keep smartphones out of schools and keep people younger than 16 off social media. The biggest proponent of this right now is Jonathan Haidt, who has a new book called “The Anxious Generation, How the Great Rewiring of Childhood is Causing an Epidemic of Mental Illness.” Do you agree with Haidt’s argument there, that teens would be far better off without access to social media and smartphones during this developmental time?
I don't have a Yes or No reaction. I think Haidt has raised a very important issue, which is ‘What are cellphones doing in our society?’ I wish that he hadn't called it an anxious generation, though. That's just stereotyping kids. And I wish that he hadn't freaked out parents so that they overreact. Parents are waiting for bad news about their kids. We want to protect our kids. We want them to be safe. We want them to have a good life. Being freaked out about something doesn't always help us do that.
The science is correlational. He does eventually say that, so there isn’t proof that phones and social media are causing anxiety. The National Academies of Sciences put out a report in December of last year that said that the science is correlational. We don't know, particularly for all kids. For some kids there's evidence of harm, but there also is evidence of benefits.
But here's my biggest issue with Haidt. I think he wonderfully understands the importance of play, and he understands the importance of autonomy, but then [he argues for] jumping in and reacting to this without teaching kids the skills to manage it themselves. If we are banning cellphones, first of all, kids will get around it, won't they? It's the kid currency. If we're doing that in a way that doesn't involve them, we're going to repeat the mistakes that we've made with ‘stop smoking.’ Evidence shows very, very clearly that the ‘just say no’ approach in adolescence — where there's a need for autonomy — does not work. In the studies on smoking, it increased smoking.
I wish we would carry out Jon Haidt’s emphasis on autonomy, and if schools would say, look, kids agree, there are bad things about cellphones. They're distracting, they're addictive. You see people who are ‘perfect.’ You see that you weren't invited to the mall with all the girls like Taylor Swift. We can't let the use of it, though, just become negative. So there have to be some rules about it, and the kids could help the adults even come up with the rules. We don't want cellphones in the school, but how would that best work if the kids aren't part of the solution?
One of the most frequent things that young people are asking me is, ‘How am I going to have the skills to fare in the adult world if we fix problems for kids?’
If we fix problems for kids, then they're going to go to college and always be connected with us anytime they have a problem. So we'll continue to fix things for them. They're going to be taking anti-anxiety medication. I mean, I'm exaggerating, but this is the time for them to learn these skills, to begin to deal in constructive ways with society. Young people can be part of the solution, and we'll be developing skills in them. And that's my main beef with the discussion that's going on.
What advice do you have for educators to best embrace this developmental period for teens?
Risk-taking is seen as negative. We have defined it as negative risk-taking, drinking, drugs, bad driving, texting. We say, ‘Why do they make such stupid decisions, kind of risky behavior?’ And we need to understand that this is a period of their lives when they're learning to be brave.
I love the way Ron Dahl at the University of California at Berkeley says it. They have a more of a fear reaction and they are sensation seekers. The highs are higher, the lows are lower. So we need to give them opportunities to take positive risks — positive risks to help those other people who are less fortunate, positive risks to try something that might be hard for them, positive risks to stand up for something that they believe in.
We need to give them opportunities to figure out who they are, to play into their development, which is a time when they are feeling things so strongly, and give them experiences for the benefit of themselves and for the benefits of society.
For example, I think of learning to clean up a pond that is polluted, or giving to kids who don't have toys near their playground or there's just so many things. That's a positive risk. That is so cool. Doing something for the world. Things that young people care about and they're learning the skills that go along with that. They're learning that they can be contributors to society.
Listen to the full conversation on the EdSurge Podcast.
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ST. PAUL, Minn. — What do you want to be when you grow up? That’s a question long faced by high school students. But these days, students have access to far more information than in the past about what, specifically, they could do as a job after they graduate.
And that is changing the way students are thinking about whether or not they want to go to college — or when they want to go.
These shifting attitudes were evident in March at Central High School here, at a daylong event dubbed the “Opportunity Fair.” More than 100 local businesses set up tables with company banners and flyers about what it means to work for them, with representatives on hand to answer questions.
Some of the jobs represented require college degrees. Others don’t. Some of the employers here said they have career paths for both, such as a medical-device company that looks for folks out of high school to work on their factory floor as well as college grads to join their design teams. And other companies look for talented students for entry-level jobs, with the promise to help them pay for college or more training later if needed.
“I don't know if I'm going to go to college right after I get out of high school,” said one junior. “But I think that at some point in my future when I want to get a professional job, I probably will go to college before I do that. I don't think I need to rush into it. I don't don't want to end up failing college or anything like that.”
That’s something that people who work with high school students on their choices are hearing more these days, says Liz Williams, a senior program officer for the Greater Twin Cities United Way. Part of her job is helping high schools set up programs that show students their career options.
“When I think about my own journey,” Williams said, “I have an undergraduate degree in Spanish and Portuguese, so it was a really cool thing to study. I got to travel, I got to learn languages. But it also gave me zero direction as to what careers were possible. And so I had to sort of find that on my own.”
Today students are “asking better questions,” she said. “So I actually think there's a lot of wisdom in that skepticism of, ‘I'm not sure college is right for me. I know I'm going to have to take on debt. I have a cousin, a parent who has taken on that type of debt and I see what that is like.’ They also see adults who maybe don't have debt but hate the work that they do. … And so I think that there's this trend toward taking a step back and really thinking about what they want to do, and if it is college, thinking more critically about ‘Why college?’, and ‘College for what?’”
This is the fourth episode of our podcast series Doubting College, where we’re exploring: What happened to the public belief in college? And how is that shaping the choices young people are making about what to do after high school?
For this installment we’re focusing on the opportunities young people have these days, the changing ways that high school counselors and education leaders are presenting those choices, and what these students think about their options.
Listen to the episode on Apple Podcasts, Overcast, Spotify, YouTube or wherever you listen to podcasts, or use the player on this page.
© Photo by Jeffrey R. Young / EdSurge
Since the sudden rise of ChatGPT and other AI chatbots, many teachers and professors have started using AI detectors to check their students’ work. The idea is that the detectors will catch if a student has had a robot do their work for them.
The approach is controversial, though, since these AI detectors have been shown to return false positives — asserting in some cases that text is AI-generated even when the student did all the work themselves without any chatbot assistance. The false positives seem to happen more frequently with students who don’t speak English as their first language.
So some instructors are trying a different approach to guard against AI cheating — one that borrows a page out of criminal investigations.
It’s called “linguistic fingerprinting,” where linguistic techniques are used to determine whether a text has been written by a specific person based on analysis of their previous writings. The technology, which is sometimes called “authorship identification,” helped catch Ted Kaczynski, the terrorist known as the Unabomber for his deadly series of mail bombs, when an analysis of Kaczynski’s 35,000-word anti-technology manifesto was matched to his previous writings to help identify him.
Mike Kentz is an early adopter of the idea of bringing this fingerprinting technique to the classroom, and he argues that the approach “flips the script” on the usual way to check for plagiarism or AI. He’s an English teacher at Benedictine Military School in Savannah, Georgia, and he also writes a newsletter about the issues AI raises in education.
Kentz shares his experience with the approach — and talks about the pros and cons — in this week’s EdSurge Podcast.
Hear the full story on this week’s episode. Listen on Apple Podcasts, Overcast, Spotify, or wherever you listen to podcasts, or use the player on this page. Or read a partial transcript below, lightly edited for clarity.
EdSurge: What is linguistic fingerprinting?
Mike Kentz: It's a lot like a regular fingerprint, except it has to do with the way that we write. And it's the idea that we each have a unique way of communicating that can be patterned, it can be tracked, it can be identified. If you have a known document written by somebody, you can kind of pattern their written fingerprint.
How is it being used in education?
If you have a document known to be written by a student, you can run a newer essay they turn in against the original fingerprint, and see whether or not the linguistic style matches the syntax, the word choice, and the lexical density. …
And there are tools that produce a report. And it's not saying, ‘Yes, this kid wrote this,’ or ‘No, the student did not write it.’ It's on a spectrum, and there's tons of vectors inside the system that are on a sort of pendulum. It's going to give you a percentage likelihood that the author of the first paper also wrote the second paper.
I understand that there was recently a time at your school when this approach came in handy. Can you share that?
The freshman science teacher came to me and said, ‘Hey, we got a student who produced a piece of writing that really doesn't sound like him. Do you have any other pieces of writing, so that I can compare and make sure that I'm not accusing him of something when he doesn't deserve it?’ And I said, ‘Yeah, sure.’
And we ran it through a [linguistic fingerprint tool] and it produced a report. The report confirmed what we thought that it was unlikely to have been written by that student.
The biology teacher went to the mother — and she didn’t even have to use the report — and said that it doesn’t seem like the student wrote it. And it turned out his mom wrote it for him, more or less. And so in this case it wasn’t AI, but the truth was just that he didn't write it.
Some critics of the idea have noted that a student’s writing should change as they learn, and therefore the fingerprint based on an earlier writing sample might no longer be accurate. Shouldn’t students’ writing change?
If you've ever taught middle school writing, which I have, or if you taught early high school writing, their writing does not change that much in eight months. Yes, it improves, hopefully. Yes, it gets better. But we are talking about a very sophisticated algorithm and so even though there are some great writing teachers out there, it's not going to change that much in eight months. And you can always run a new assignment to get a fresh “known document” of their writing later in the term.
Some people might worry that since this technique came from law enforcement, it has a kind of criminal justice vibe.
If I have a situation next year where I think a kid may have used AI, I am not going to immediately go do the fingerprinting process. That's not gonna be the first thing I do. I'll have a conversation with them first. Hopefully, there's enough trust there, and we can kind of figure it out. But this, I think, is just a nice sort of backup, just in case.
We do have a system of rewards and consequences in a school, and you have to have a system for enforcing rules and disciplining kids if they step out of line. For example, [many schools] have cameras in the hallways. I mean, we do that to make sure that we have documented evidence in case something goes down. We have all kinds of disciplinary measures that are backed up by mechanisms to make sure that that actually gets held up.
How optimistic are you that this and other approaches that you're experimenting with can work?
I think we're in for a very bumpy next five years or so, maybe even longer. I think the Department of Education or local governments need to establish AI literacy as a core competency in schools.
And we need to change our assessment strategies and change what we care about kids producing, and acknowledge that written work really isn't going to be it anymore. You know my new thing also is verbal communication. So when a kid finishes an essay, I'm doing it a lot more now where I'm saying, all right. Everybody's going to go up without their paper and just talk about their argument for three to five minutes, or whatever it may be, and your job is to verbally communicate what you were trying to argue and how you went about proving it. Because that's something AI can't do. So my optimism lies in rethinking assessment strategies.
My bigger fear is that there is going to be a breakdown of trust in the classroom.
I think schools are gonna have a big problem next year, where there's lots of conflicts between students and teachers where a student says, ‘Yeah, I used [AI], but it's still my work.’ and the teacher goes, ‘Any use is too much.’
Or what's too much and what's too little?
Because any teacher can tell you that it's a delicate balance. Classroom management is a delicate balance. You're always managing kids' emotions, and where they're at that day, and your own emotions, too. And you're trying to develop trust, and maintain trust and foster trust. We have to make sure this very delicate, beautiful, important thing doesn't fall to the ground and smash into a million pieces.
Listen to the full conversation on the EdSurge Podcast.
© Pixels Hunter / Shutterstock
When Felecia Russell was a high school student growing up near Los Angeles, she was getting good grades and plenty of encouragement to go to college.
But when it came time to do the paperwork of applying to a campus and financial aid, Russell asked her mom for her social security number.
“My mom was like, ‘yeah, you don’t have one,’” she remembers.
Russell didn’t have a social security number because she didn’t have permanent legal status in the U.S. She was “undocumented.” She had moved to the U.S. from Jamaica when she was about 12. But she hadn’t fully understood until that moment, as she Googled for more details, how her immigration status could dash her dreams.
“All I saw online was ‘illegal, illegal, illegal,’” she remembers. And everything online seemed to tell her “that means you can’t go to college.”
On this week’s EdSurge Podcast, we tell the story of Russell’s fight to get her college degree, and how she has become an advocate for other undocumented students. (She went on to get her Ph.D. and is now an adjunct professor at California Lutheran University.)
Her biggest message is that even when colleges do work to help students who lack permanent legal status, they often aren’t paying attention to Black undocumented students, because the majority of services in this space are designed for Latino students.
“Some of it makes sense,” she says, “because the Latinx population is two-thirds of the undocumented population, so it makes sense that everything is centered around their experience.”
Yet the undocumented population in the U.S. is 6 percent Black, she says, and a sizable share of the 408,000 undocumented students in colleges are Black. Data from the Higher Ed Immigration Portal from the Presidents’ Alliance on Higher Education and Immigration, which Russell directs, shows that as of 2023, 46 percent of undocumented students at college were Hispanic, while 27 percent were Asian, 14 percent were Black and 10 percent were white. Some people identify as both Black and Latino, and commonly describe themselves as Afro Latino.
“And so it's so dangerous, because now we're forcing these people back into the shadows,” says Russell, who became a DACA recipient but as a student often didn’t feel welcome in support groups for undocumented students. “Now they don't have a space to belong.”
Russell shares her story in a new book out this month, called “Amplifying Black Undocumented Student Voices in Higher Education.”
The book also includes deep research on the topic, based on extensive interviews she did with 15 Black undocumented college students. And she has recommendations for school and college leaders on how to better support the full spectrum of students facing immigration issues.
Hear the full story on this week’s episode. Listen on Apple Podcasts, Overcast, Spotify, Stitcher or wherever you listen to podcasts, or use the player on this page.
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