The Pending Emerging Technology Revolution Perhaps the best way to examine the issues and opportunities created by this period of emerging technology-driven disruptive change is to ask ourselves these questions: Are you as an individual/professional and as a leader willing to accept that a course correction is becoming necessary? Given the emerging technology adoption that … Read more
Though many are eager to forget 2020, data scientists will be keeping the year top of mind as we determine whether the pandemic’s impact makes 2020 data anomalous or an indication of more permanent change in higher ed. As we develop new predictive models and update the existing ones with data collected in the last … Read more
Over the last few years, artificial intelligence (AI) has been delivering competitive advantage to businesses across a wide spectrum of industries. By Deloitte’s most recent count, 37 percent of organizations have deployed AI solutions (up 270 percent from 2016) and a majority predict it will “substantially transform” their companies by 2023. The shift may also … Read more
Colby College is carving out space in the liberal arts canon for artificial intelligence. Thanks to a $30 million gift from an alumnus, the small, selective college in Maine is establishing the Davis Institute for Artificial Intelligence, which aims to integrate machine learning, natural language processing and big data into instruction and research across the … Read more
During tricky situations in the new PBS KIDS show “Elinor Wonders Why,” a curious rabbit directs a question to viewers, pausing to give them a chance to answer. This invitation to participate in the plot of the story is a hallmark of educational programs for young children, a moment designed to check their comprehension and … Read more
The demand for innovative digital learning technology has never been higher. And investment continues to flow into the edtech space. But companies looking to differentiate themselves in this increasingly competitive sector have to bring something new to the table. Esme Learning Solutions is banking on artificial intelligence (AI), collaborative learning experiences and relationships with some … Read more
The original version of this article appeared in Toward Data Science. When I started teaching data science and artificial intelligence in Duke University’s Pratt School of Engineering, I was frustrated by how little insight I actually felt I had into how effective my teaching was, until the end-of-semester final exam grades and student assessments came … Read more
At a time when a global pandemic has laid bare—and exacerbated—many of the inequities that exist in education, a new nonprofit organization has emerged that aims to tackle at least some of them. The AI Education Project, founded in 2019, hopes to teach young people about artificial intelligence and the way it will impact—and is already impacting—their lives and livelihoods. The primary way the nonprofit is doing this is through an AI curriculum it launched in May in Akron Public Schools in Ohio but which has already spread to six states and more than 2,500 students. The curriculum was designed specifically for Generation Z, which research shows is interested in both high-paying jobs and promoting civil rights and social justice issues, says Ora Tanner, co-founder and chief learning officer at the AI Education Project. The nonprofit convened a virtual forum on AI and workforce readiness earlier in December, during which EdSurge moderated a conversation with Tanner and Girls Who Code COO Tarika Barrett. Both women are committed to making education more equitable and technology fields more diverse, especially in the face of a pandemic that has disproportionately affected the populations they seek to elevate. This includes girls, who were already underrepresented in STEM fields before the pandemic added new caregiving responsibilities for many of them that sidelined their education. What follows is a transcript of the discussion, lightly edited and condensed.EdSurge: Why do you feel an urgency for students from untapped communities to develop a foundational understanding about not just technology, but AI specifically?Ora Tanner: Artificial intelligence is expected to impact and transform every area of students’ lives and our society. Students need to be equipped with the knowledge and skills required to navigate what’s being called “the new electricity.” And we’ve heard various predictions from different reports—the World Economic Forum predicts that 75 million jobs will be eliminated by 2022. A McKinsey report estimates that 50 percent of jobs are at risk of being highly automated. But if you drill down into those numbers, workers who are ages 16 through 24—also known as Gen Z—are overrepresented in the repetitive types of jobs that are at the highest risk of being displaced due to automation.That’s why this urgency is there, specifically because they’re in jobs such as fast food, grocery and retail, and we already see those being replaced by self checkout and kiosks. Also, Hispanic, American Indian or indigenous people, Black workers face on average an automation potential that’s well above their white and Asian counterparts. I’ve seen research where students feel like classes in schools are not preparing them adequately for the careers of the future and that they haven’t had an opportunity to explore careers, especially as they’re impacted by AI. Can you discuss the design considerations that you made to ensure that the content in your curriculum is accessible to the diverse students that you’re trying to serve?Tanner: First we centered the students themselves in our design process. Beyond race and gender, they’re young people, and so their beliefs, their values and their communities should be centered in the design process. Also, because we launched in the middle of COVID, we had to look at some situational factors. Everyone’s going online. Students are now at home, they might have to be caring for siblings and there’s access issues. We have to keep all of that in mind—what they realistically could and could not do. Our learning objectives focus on the social, political, economical and cultural aspects of AI. And we did that because we believe it lowers the barrier to entry to learning about AI for more types of students. Also, we have what I like to call a pedagogy stack. We really focused on culturally relevant pedagogy as one of the foundational theoretical frameworks. We really want to empower students to celebrate their communities and reflect that throughout all of the content.And we use asset-based approaches versus deficit-oriented teaching methods. And then just a little bit about the Gen Z—what they really care about. At the forefront of their thinking, they want well-paying jobs. That’s a huge motivation. But they also have civil rights and social justice issues at the forefront of their thinking. So we weave that throughout all of our content. I’ve heard you say the curriculum is more like TikTok than Scholastic.Tanner: I would say the persona of the course is what students are used to finding online, on social media platforms. I call it “Gen Z curriculum design.” Instead of saying, ’These are your learning objectives,’ we just have #goals. We talk about the platforms they’re on such as TikTok, Google. We have lots of case studies and examples that really allow them to explore different concepts, such as one about bias that might be on TikTok. Also there’s a game-based learning element to it. There’s a lot of scenario-based prompts, so it’s really playful. It connects with who they are as young people, and we’ve seen it resonate with them. And just a point about the diversity piece—we look at our content, teaching them about AI in the context of jobs and careers, since that is what they care most about. Through 21 different careers, we teach them about data algorithms, predictive analytics, machine learning. And these are not just STEM jobs. This is fashion design, culinary arts, urban city design. But we’ve seen that it’s really resonating with them.It’s impossible for us to sit here and talk about education and equity and not discuss the pandemic that has disproportionately impacted low-income families and families of color. What challenges has this pandemic created for you and the work that you’re doing, particularly since COVID-19 has worsened inequities among the very groups that your organizations are trying to reach?Tarika Barrett: I think we all know the truth about the inequity of education in this country. Students from low-income or minority communities are routinely left behind, and the pandemic has only made that more clear. When schools closed their doors this past March, they left as many as 12 million students without access to Wi-Fi. We didn’t give much thought or simply weren’t prepared to support the 1.4 million kids in this country who are actually caregivers. They have these responsibilities, and most of them are actually girls. Days turned into weeks, turned into months, and over time, fewer and fewer public school students as compared to their private school peers actually attended their online classes. At Girls Who Code, we transformed our in-person summer coding program to a virtual offering in a matter of weeks, making it our absolute highest priority to serve the most vulnerable girls. Half the girls we serve are Black, Latinx or low income. They live in our most densely populated cities and in our most rural parts of the country. They’re caregivers, babysitters. And in some cases they’re working hourly as essential employees at grocery stores or hospitals, just to help with household income. We also raised funds to get the girls the necessary hardware and Wi-Fi hotspots. Our team’s educators, coders and data scientists had to innovate and adapt the place-based program that we’ve run for years into one that ran a few hours a day with both live and asynchronous instruction, group work and office hours. And we are so happy to report that it actually worked. I want to say upfront that we are absolutely far from a national model for education during this crisis or for the long term, but even so, some of the adjustments that we made as a nonprofit in our programming are the kinds of adjustments that we need to see implemented for education and tech to actually be equitable. Tanner: We actually saw the demand for what we’re doing expand. Currently our curriculum is spread across six states serving 2,500 students—and this is just having launched earlier in the school year. There’s just a demand from teachers and students. One thing we’ve heard again and again, talking with educators and administrators, is that need for engagement. I think this is kind of an overlooked part of the accessibility. One of my many sayings is “availability does not equal accessibility.” So just because you put something out there online, students come to it and they can’t relate, or they can’t understand, or it’s bogged down with terminology and jargon, or you did not have them in mind when you created it. You have to design equity. It doesn’t just happen.Tarika, I’m curious, given the distinction between availability and accessibility Ora just made, about what Girls Who Code did to make the summer immersion program accessible to so many more girls than are usually able to attend. Was there anything done to try to reach those students who are also caregivers or who have a part-time job or do not have reliable internet access?Barrett: That was really at the forefront of our thinking. We did a survey of our girls before they even entered the program to really get a handle on what were their needs: How many hours could they give, did they have the hardware? Did they have the tech, would they be able to attend? That was absolutely the No. 1 thing that we had to do. And so we were able to identify those broadband issues. We were able to get girls laptops. But the entire design of the program had that orientation. We recognize that if you’re a caregiver, you can’t just ask a girl to join a program and be there all day. You can’t expect that they’re going to not have to turn their camera off. Everything that we did was strengths-based and thought about meeting those girls where they were, and, you know, even things like office hours, we contemplated the ways in which there’s some girls who are going to be very comfortable going to office hours, culturally, based on school experience, where they already had systems like that, and other girls for whom it will be completely foreign.We interrogated every aspect of the program that we tried to bring to market to think about what it would mean, because we knew that girls were driving to Burger King parking lots to get Wi-Fi, and that they were immensely vulnerable at this moment. And that we had to have something that would work for the most marginalized students. Typically when we run our summer immersion program, it’s girls coding from 9-5, seven days a week, in tech companies. And we usually would have about 80 of these programs, so about 1,600 girls. This year, we served 5,000 girls with a radically overhauled program that was all online. And as Ora said, it became all about engagement. What platforms should we use? How are we going to make the breakout rooms really meaningful? There was a lot around engagement that really pushed our educators who execute this program to think differently. And there was a tremendous amount of learning, but what was amazing was that the girls and the teachers reported such strong outcomes on par with what we would normally have in our seven-week immersive program, which just blew our minds. And so it can be done. If you start with thinking about who you’re serving and how to make it engaging, meaningful and transformational for that student, if that’s your bedrock, then I think there’s a lot that we can do to transform these educational experiences.
Humans tutoring other humans works pretty well. The trouble is, it requires a lot of people. Artificially intelligent tools tutoring humans works pretty well, too—but building those digital systems takes time and expertise. So researchers hoping to engineer better teaching and learning systems are working to unlock a new level of education efficiency by creating AI tools that make it easier for almost anyone to build an AI tutor. “We are trying to leverage the joint power of human tutoring and computer tutoring,” says Ken Koedinger, a professor of human-computer interaction and psychology at Carnegie Mellon University. Speedier Solutions to Answering Student Questions Creating the kind of AI tutoring tool that complements or even replaces the work of a human tutor can take skilled computer programmers hundreds or thousands of hours. That puts such tools out of reach for most teachers looking for new ways to provide their students with personalized support. “No teacher is going to put in 1,000 person-hours of his or her time in order to get a benefit of 200 person-hours that he or she may save,” Ashok Goel, a professor of computer science and cognitive science at Georgia Institute of Technology, told EdSurge in an interview earlier this year. “It’s not something I could hand over to you or to some colleague and say, ‘Go run it in your class.’”A thousand hours is about how long it took Goel and his team to create Jill Watson, an AI teaching assistant chatbot that can answer student questions. Now, Goel and his colleagues are working on a new tool that can build a Jill Watson with just a bit of human help. Called Agent Smith, it’s an artificially intelligent system that absorbs information from a course syllabus and uses it to build a Jill Watson customized to that class. Doing so takes only about 10 hours of work from a human. The power to produce AI education tools in a fraction of the original time is exciting to Goel, who thinks every teacher, child and parent should have access to a Jill Watson. “I think it’s doable now that we have Agent Smith,” he says. “If we can do it in two hours—we’re not there yet, but if we can do it in two hours, then I can see the scaling up really happen.” Minting More Math Tutors Meanwhile, Koedinger and other researchers at Carnegie Mellon University are working to create a system that can easily learn math skills from a human teacher, and then tutor students in those skills. When the first AI tool in the system, called the Apprentice Learner, encounters a new type of math problem, it will ask a human user to demonstrate a step-by-step solution. The Apprentice Learner then makes hypotheses about how the solution steps work and tests those theories on subsequent problems. The human user offers positive or negative feedback from which the tool learns. See the tool in action here. Building a tool that learns the same way a student learns—through practice and feedback—means that “a nonprogrammer now can essentially teach the computer by demonstrating,” Koedinger says. And it can also yield insight about what makes learning hard for humans, he adds, because when the Apprentice Learner struggles, “it’s pretty predictive of when a real student is going to struggle, often in ways human experts don’t realize.” In turn, the Apprentice Learner uses what it knows to create intelligent tutoring systems that offer that same kind of math practice and feedback to human students. “The teacher teaches one ‘student,’ and the computer teaches all the rest,” Koedinger says. “The code is getting written by artificial intelligence.” The researchers would like to improve this system such that teaching it a new skill takes a human educator the same amount of time as it takes to tutor a student directly.“Even faster would be great,” says Carnegie Mellon doctoral student Daniel Weitekamp. “There are still a few bugs, but we’re rapidly getting there.” And because teachers often prefer differing strategies for solving math problems, the system can learn alternative solution paths to suit a variety of methods.“One teacher can make their tutor strict. Another can make it more flexible,” Koedinger says. “You can do it your way. It opens up more doors.” Building Better Online Courses Slashing the time it takes to create an entire online course—one that incorporates artificially intelligent personalized tutoring—is the goal of Korbit, a Canandian startup founded by alumni of Montreal’s Mila artificial intelligence research institute and Cambridge University. Online education tends to be widely accessible, but online course completion rates are low. AI tutors can boost student learning, but they’re resource-intensive to make. Korbit aims to combine the best of both education systems without all the human labor that typically goes into creating either. “It takes a really long time to build these programs—a year and a team of 10 people to build one physics course,” says Iulian Vlad Serban, CEO of Korbit. “There are lots of issues, and the biggest one [is] scalability.” The company is working on AI technology—called Korbi—that reduces the time it takes to create effective, interactive online courses that include chatbot-based tutoring supports such as hints and definitions. It’s based on “an algorithm that sits on top of other algorithms,” Serban says. Teachers construct the building blocks—the course modules—and Korbi organizes them for students according to their personal goals and what lessons the tool discerns they need. For the tutoring component, the tool draws on data that teachers put in the system—and from information it gathers from Wikipedia and open educational resources. “We don’t write a thousand rules,” Serban says. “A teacher writes the questions, writes one or two answers. Korbi analyzes that, and scrapes data from the web and builds out the course.” Pulling information from the internet hasn’t resulted in a lot of inaccuracies so far, he adds, but it does sometimes pull in irrelevant facts. “The main problem we are working on is finding the most relevant piece of information the student needs,” Serban says.Korbi is as much a student as it is a tutor. Over time, the system adapts the interventions it offers human users as it learns what works. The fact that the tool can teach at scale, for thousands of people at once, also means it has access to large quantities of the information it uses to improve. “We let the AI algorithm figure it out from its own data,” Serban says. “Most of what it does is learning from the students. Students are teaching it to do better.”
K-12 technology integration specialists like Jill Hill and Kim Logie-Bates are always on the lookout for new and compelling ways to integrate tech into learning for the thousands of students in their diverse Metro Detroit area school district. For them, signing up for AI Explorations and Their Practical Use in School Environments—a professional learning course by ISTE and General Motors—was a no-brainer.Most of what we do in our professional world—no matter what job you have—you need to be able to work in teams with people who have different interests and skills.
– Jill Hill“It was just a great chance to learn more about artificial intelligence and machine learning and how to encourage K-12 teachers to use more AI tools in their classrooms,” said Hill, the technology integration specialist at her middle school. “And since Kim and I are connected to all of these great tech integrators and the hundreds of K-12 teachers they work with in our county, it seemed like a great way to scale up and introduce these ideas into our area.”Hill had previously taken an ISTE AI course that she enjoyed. So, when this small-group, cohort-based AI program became available, she jumped at the chance. She and Logie-Bates recruited their fellow Oakland Schools tech education enthusiasts to take advantage of the opportunity: 3rd grade teacher Jeremy Letkiewicz and two other K-12 technology integration specialists, Priscila Fojan and Stefanie Hebden.We spoke with this dynamic group of educators about how the AI Explorations course helped reshape and expand their efforts to integrate AI tools and teaching into K-12 classrooms.EdSurge: How has your experience with AI Explorations impacted your practice?Letkiewicz: As an elementary school teacher, I’m really interested in how we can use AI in classrooms and the tools we can give teachers to make learning more engaging for students, especially this year for the schools that are going all online. Going through this course really gave me concrete and compelling ways to use AI with my students. Even the yoga and machine learning capstone project we created for the program—it’s something fun. When you tell people about it, they get excited and want to know more. I’m looking forward to integrating more fun AI activities like that in my classroom in the fall.Hill: I have a makers club that I’ve been running for five or six years at the middle school that has anywhere between 30 and 50 kids in it every year. There is a lot of focus on coding, and just creation and working with all kinds of textiles, everything from 3-D printing to artificial intelligence. Introducing that group of kids to AI is another way to help bring it into the school because they bring those conversations into the classroom and share with their friends and teachers. I’ve talked a lot with math teachers about computational thinking and pulling those terms into their classrooms, but the program has helped me think about how to apply that across the board with other subjects. Just getting those conversations started and bringing that terminology—whether it’s design thinking, machine learning or computational thinking—to teachers who may not have heard it before or think it doesn’t relate to them. The more we use it, the more it becomes part of their language and what they can incorporate into their classes.Hebden: As tech integration specialists, the program really gave us a lot of ways to support teachers in their practice. The resources that were provided are so helpful, especially now with remote learning because I have so many teachers asking, “How am I going to do my multiple choice tests now online because students can Google all the answers?” Well, we shouldn’t be doing that now. Have your students do projects and collaborate online, that’s the most important thing. The course gave us a ton of resources for what that can look like and how we can bring it back to teachers.Logie-Bates: In my role, I work with teachers, so I’m really looking forward to developing these projects and lessons with them. In several of the schools I work with, STEM, design thinking and project-based learning are really starting to take hold, and it’s exciting because there are people genuinely interested in incorporating these ideas into their classes.How did the course help you integrate Project-Based Learning (PBL) into your practice? Why is it important for students to learn how to collaboratively solve real-world problems?Hill: Most of what we do in our professional world—no matter what job you have—you need to be able to work in teams with people who have different interests and skills. In the U.S., our schools emphasize creativity and big picture thinking, and we thrive when we take into consideration each person’s strengths and what they can bring to the team. Teaching kids how to do that is really valuable because they need to know that not every person can do every thing, but we can accomplish a lot together. They need to know how to take a problem apart and figure out a solution together.Fojan: I remember growing up and being the kid that got assigned into a group and ending up doing the majority of the work, oftentimes because the assignments were not as robust and could essentially be completed by one person. With project-based learning, there’s so much that has to be done, and everyone has an important role in the project. When you’re working on a complex problem, there’s a lot that gets built into solving it. You have to communicate and learn how to work together, and every person plays a critical part. PBL goes beyond just a school assignment—it prepares kids for the real world that we live in.Logie-Bates: One of the things this course gave me was validity when speaking to other educators. I could say, “Look, here’s an ISTE course that is all about AI for K-12 and how to incorporate student voice and choice in your project-based lessons.” It’s not just me talking—I have actual research and data backing me up that confirms this is a better way to do it, and this is really what we need to be teaching our kids to do.What was the inspiration for your group’s AI Explorations capstone project? How and why did you develop this particular lesson?Logie-Bates: We chose a project where students work with Google’s Teachable Machine site to learn yoga because it was fun and creative and could cross over the multiple grades we represent, all kids K-12. We targeted 3rd-5th grade for Jeremy as something that he could use right away as a classroom teacher, but also wanted something that could be modified for any age.Fojan: We originally looked at social-emotional learning and using the Teachable Machine to recognize facial expressions, but when Jill tested it with her kids, it really wasn’t working so we iterated and transformed it into yoga.Hill: Yeah, it just wouldn’t recognize the different facial expressions, so we shifted to machine learning yoga, which is another way for them to learn self awareness and managing emotions and stress. The kids liked yoga to help calm down and take deep breaths. The machine actually learned to recognize their poses. It was fun for them to teach a machine, but it was also great to have them practicing to get the poses right and just talking to each other about how movement and mindfulness helps calm them down.One of the things that I was really thankful for is that I was able to work with a group of people that I don’t normally work with.
– Kim Logie-BatesLetkiewicz: I think it’s pretty cool. I’ve been looking at our project again. I’m personally excited about it, especially being at home and kids being at home—this is something that kids any age can do.How did your students respond?Hill: My kids loved it. I was the only one who was able to run the lesson with actual students this year because of COVID-19, but they loved the yoga and loved learning about technology and how it all works. They’re a whole different generation that’s grown up with touchscreens, and everything tech to them is supposed to be reactive and interactive. But talking about how you teach a machine to be reactive, what part of it is recognizing what you’re doing, and how you can teach it to recognize what you’re doing was kind of a mind-blowing experience for them. They felt very empowered in wanting to learn more. How has being a part of ISTE’s professional learning network impacted you?Fojan: The Facebook group, Twitter and using hashtags and social media to get and share information has been really helpful for us. There were countless times I found resources in my news feed that I grabbed and shared out. Just one person communicating with one other tech integrator reaches multiple other districts and hundreds of other educators. Having that network to quickly get and share information is really useful for all of us.Hebden: We have access to the ISTE website now, so I’ve joined a few different forums on there too. I get the Daily Digest email and click on those remote learning links every single day because it helps me so much right now. I’ve created a resource list that I constantly add to, so if a teacher says, “Hey, I need something for music,” or “I’m a reading specialist, do you have anything?,” I can easily find and share what I’ve collected. Those resources have been especially helpful during this time. I was part of the ISTE community for the past year, but I’ve used it the most in the past three months.Hill: I absolutely agree. I have my digest that comes through on six different forums, so I feel like we learn a lot through just the ISTE community in general. I even got a chance to meet with one of the instructors and course creators from GM who is actually in Sterling Heights, which is right next to our town, within 10 miles of our school.What stood out to you most from participating in this program? Download the free Hands-On AI Projects for the Classroom guides to start engaging your students in AI creation today.Logie-Bates: One of the things that I was really thankful for is that I was able to work with a group of people that I don’t normally work with. As technology integration specialists in our districts, I work with Stefanie and Priscila, but we essentially work on islands most of the time, even more so now than before. We see each other on Zoom meetings or chat on our WebEx channel, but this was an opportunity to get a group working together that was really diverse. We all service completely different kinds of districts, have different jobs, and impact different groups of students. ISTE allowing this diverse cohort that wasn’t just all of the same teachers from the same school or all people from the same grades was really forward-thinking. I appreciate they recognized the strength of that.Letkiewicz: That’s exactly what I was going to say. It was amazing being able to interact with all these different perspectives because it really got me thinking about how to add artificial intelligence into my classroom in creative ways. Doing this course gave me a better understanding of how to make learning really fun for kids who have that tech brain that maybe don’t click with just reading a regular book in front of them. They need something more interactive. I kept going to online forums and reading things about artificial intelligence, which I would not have done if not for this course. I’m really thankful for working with everyone and doing this. It really got the wheels turning in my head.Fojan: The biggest thing that I took away, other than our strong collaboration is that when I used to think of AI, it was way up there, outside of my realm of understanding. Yes, I could introduce a few examples with my students, but the program filled in such a big void I had when it came to the history of AI and getting a deeper understanding of what it is and isn’t. The topic can be vast, but it can also be understood by an elementary student when you bring it down to its basic level. It isn’t like we all need to have engineering degrees to understand and teach the fundamentals.