artificial intelligence in education newspaper

AI Will Transform Teaching and Learning. Let’s Get it Right.

At the recent AI+Education Summit, Stanford researchers, students, and industry leaders discussed both the potential of AI to transform education for the better and the risks at play.

children work on computers in a classroom

When the Stanford Accelerator for Learning and the Stanford Institute for Human-Centered AI began planning the inaugural AI+Education Summit last year, the public furor around AI had not reached its current level. This was the time before ChatGPT. Even so, intensive research was already underway across Stanford University to understand the vast potential of AI, including generative AI, to transform education as we know it.

By the time the summit was held on Feb. 15, ChatGPT had reached more than 100 million unique users , and 30% of all college students had used it for assignments, making it one of the fastest-ever applications ever adopted overall – and certainly in education settings. Within the education world, teachers and school districts have been wrestling with how to respond to this emerging technology.

The AI+Education Summit explored a central question: How can AI like this and other applications be best used to advance human learning?

“Technology offers the prospect of universal access to increase fundamentally new ways of teaching,” said Graduate School of Education Dean Daniel Schwartz in his opening remarks. “I want to emphasize that a lot of AI is also going to automate really bad ways of teaching. So [we need to] think about it as a way of creating new types of teaching.”

Researchers across Stanford – from education, technology, psychology, business, law, and political science – joined industry leaders like Sal Khan, founder and CEO of Khan Academy, in sharing cutting-edge research and brainstorming ways to unlock the potential of AI in education in an ethical, equitable, and safe manner.

Participants also spent a major portion of the day engaged in small discussion groups in which faculty, students, researchers, staff, and other guests shared their ideas about AI in education. Discussion topics included natural language processing applied to education; developing students’ AI literacy; assisting students with learning differences; informal learning outside of school; fostering creativity; equity and closing achievement gaps; workforce development; and avoiding potential misuses of AI with students and teachers.

Several themes emerged over the course of the day on AI’s potential, as well as its significant risks.

First, a look at AI’s potential:

1. Enhancing personalized support for teachers at scale

Great teachers remain the cornerstone of effective learning. Yet teachers receive limited actionable feedback to improve their practice. AI presents an opportunity to support teachers as they refine their craft at scale through applications such as:

Simulating students: AI language models can serve as practice students for new teachers. Percy Liang , director of the Stanford HAI Center for Research on Foundation Models , said that they are increasingly effective and are now capable of demonstrating confusion and asking adaptive follow-up questions.
Real-time feedback and suggestions: Dora Demszky , assistant professor of education data science, highlighted the ability for AI to provide real-time feedback and suggestions to teachers (e.g., questions to ask the class), creating a bank of live advice based on expert pedagogy.
Post-teaching feedback: Demszky added that AI can produce post-lesson reports that summarize the classroom dynamics. Potential metrics include student speaking time or identification of the questions that triggered the most engagement. Research finds that when students talk more, learning is improved.
Refreshing expertise: Sal Khan, founder of online learning environment Khan Academy, suggested that AI could help teachers stay up-to-date with the latest advancements in their field. For example, a biology teacher would have AI update them on the latest breakthroughs in cancer research, or leverage AI to update their curriculum.

2. Changing what is important for learners

Stanford political science Professor Rob Reich proposed a compelling question: Is generative AI comparable to the calculator in the classroom, or will it be a more detrimental tool? Today, the calculator is ubiquitous in middle and high schools, enabling students to quickly solve complex computations, graph equations, and solve problems. However, it has not resulted in the removal of basic mathematical computation from the curriculum: Students still know how to do long division and calculate exponents without technological assistance. On the other hand, Reich noted, writing is a way of learning how to think. Could outsourcing much of that work to AI harm students’ critical thinking development?

Liang suggested that students must learn about how the world works from first principles – this could be basic addition or sentence structure. However, they no longer need to be fully proficient – in other words, doing all computation by hand or writing all essays without AI support.

In fact, by no longer requiring mastery of proficiency, Demszky argued that AI may actually raise the bar. The models won’t be doing the thinking for the students; rather, students will now have to edit and curate, forcing them to engage deeper than they have previously. In Khan’s view, this allows learners to become architects who are able to pursue something more creative and ambitious.

And Noah Goodman , associate professor of psychology and of computer science, questioned the analogy, saying this tool may be more like the printing press, which led to democratization of knowledge and did not eliminate the need for human writing skills.

3. Enabling learning without fear of judgment

Ran Liu, chief AI scientist at Amira Learning, said that AI has the potential to support learners’ self-confidence. Teachers commonly encourage class participation by insisting that there is no such thing as a stupid question. However, for most students, fear of judgment from their peers holds them back from fully engaging in many contexts. As Liu explained, children who believe themselves to be behind are the least likely to engage in these settings.

Interfaces that leverage AI can offer constructive feedback that does not carry the same stakes or cause the same self-consciousness as a human’s response. Learners are therefore more willing to engage, take risks, and be vulnerable.

One area in which this can be extremely valuable is soft skills. Emma Brunskill , associate professor of computer science, noted that there are an enormous number of soft skills that are really hard to teach effectively, like communication, critical thinking, and problem-solving. With AI, a real-time agent can provide support and feedback, and learners are able to try different tactics as they seek to improve.

4. Improving learning and assessment quality

Bryan Brown , professor of education, said that “what we know about learning is not reflected in how we teach.” For example, teachers know that learning happens through powerful classroom discussions. However, only one student can speak up at a time. AI has the potential to support a single teacher who is trying to generate 35 unique conversations with each student.

This also applies to the workforce. During a roundtable discussion facilitated by Stanford Digital Economy Lab Director Erik Brynjolfsson and Candace Thille , associate professor of education and faculty lead on adult learning at the Stanford Accelerator for Learning, attendees noted that the inability to judge a learner’s skill profile is a leading industry challenge. AI has the potential to quickly determine a learner’s skills, recommend solutions to fill the gaps, and match them with roles that actually require those skills.

Of course, AI is never a panacea. Now a look at AI’s significant risks:

1. Model output does not reflect true cultural diversity

At present, ChatGPT and AI more broadly generates text in language that fails to reflect the diversity of students served by the education system or capture the authentic voice of diverse populations. When the bot was asked to speak in the cadence of the author of The Hate U Give , which features an African American protagonist, ChatGPT simply added “yo” in front of random sentences. As Sarah Levine , assistant professor of education, explained, this overwhelming gap fails to foster an equitable environment of connection and safety for some of America’s most underserved learners.

2. Models do not optimize for student learning

While ChatGPT spits out answers to queries, these responses are not designed to optimize for student learning. As Liang noted, the models are trained to deliver answers as fast as possible, but that is often in conflict with what would be pedagogically sound, whether that’s a more in-depth explanation of key concepts or a framing that is more likely to spark curiosity to learn more.

3. Incorrect responses come in pretty packages

Goodman demonstrated that AI can produce coherent text that is completely erroneous. His lab trained a virtual tutor that was tasked with solving and explaining algebra equations in a chatbot format. The chatbot would produce perfect sentences that exhibited top-quality teaching techniques, such as positive reinforcement, but fail to get to the right mathematical answer.

4. Advances exacerbate a motivation crisis

Chris Piech , assistant professor of computer science, told a story about a student who recently came into his office crying. The student was concerned about the rapid progress of ChatGPT and how this would deter future job prospects after many years of learning how to code. Piech connected the incident to a broader existential motivation crisis, where many students may no longer know what they should be focusing on or don’t see the value of their hard-earned skills.

The full impact of AI in education remains unclear at this juncture, but as all speakers agreed, things are changing, and now is the time to get it right.

Watch the full conference:

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition. Learn more

How Schools Can Survive (and Maybe Even Thrive) With A.I. This Fall

Step 1: Assume all students are going to use the technology.

An illustration renders a classroom, including desks, bookshelves and a chalkboard, in bright colors with random spheres, triangles and objects like a light bulb floating into the scene.

By Kevin Roose

Last November, when ChatGPT was released, many schools felt as if they’d been hit by an asteroid.

In the middle of an academic year, with no warning, teachers were forced to confront the new, alien-seeming technology, which allowed students to write college-level essays, solve challenging problem sets and ace standardized tests.

Some schools responded — unwisely, I argued at the time — by banning ChatGPT and tools like it. But those bans didn’t work, in part because students could simply use the tools on their phones and home computers. And as the year went on, many of the schools that restricted the use of generative A.I. — as the category that includes ChatGPT, Bing, Bard and other tools is called — quietly rolled back their bans.

Ahead of this school year, I talked with numerous K-12 teachers, school administrators and university faculty members about their thoughts on A.I. now. There is a lot of confusion and panic, but also a fair bit of curiosity and excitement. Mainly, educators want to know: How do we actually use this stuff to help students learn , rather than just try to catch them cheating?

I’m a tech columnist, not a teacher, and I don’t have all the answers, especially when it comes to the long-term effects of A.I. on education. But I can offer some basic, short-term advice for schools trying to figure out how to handle generative A.I. this fall.

First, I encourage educators — especially in high schools and colleges — to assume that 100 percent of their students are using ChatGPT and other generative A.I. tools on every assignment, in every subject, unless they’re being physically supervised inside a school building.

At most schools, this won’t be completely true. Some students won’t use A.I. because they have moral qualms about it, because it’s not helpful for their specific assignments, because they lack access to the tools or because they’re afraid of getting caught.

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Artificial Intelligence and Education: A Reading List

A bibliography to help educators prepare students and themselves for a future shaped by AI—with all its opportunities and drawbacks.

Young black student studying at night at home, with a help of a laptop computer.

How should education change to address, incorporate, or challenge today’s AI systems, especially powerful large language models? What role should educators and scholars play in shaping the future of generative AI? The release of ChatGPT in November 2022 triggered an explosion of news, opinion pieces, and social media posts addressing these questions. Yet many are not aware of the current and historical body of academic work that offers clarity, substance, and nuance to enrich the discourse.

Linking the terms “AI” and “education” invites a constellation of discussions. This selection of articles is hardly comprehensive, but it includes explanations of AI concepts and provides historical context for today’s systems. It describes a range of possible educational applications as well as adverse impacts, such as learning loss and increased inequity. Some articles touch on philosophical questions about AI in relation to learning, thinking, and human communication. Others will help educators prepare students for civic participation around concerns including information integrity, impacts on jobs, and energy consumption. Yet others outline educator and student rights in relation to AI and exhort educators to share their expertise in societal and industry discussions on the future of AI.

Nabeel Gillani, Rebecca Eynon, Catherine Chiabaut, and Kelsey Finkel, “ Unpacking the ‘Black Box’ of AI in Education ,” Educational Technology & Society 26, no. 1 (2023): 99–111.

Whether we’re aware of it or not, AI was already widespread in education before ChatGPT. Nabeel Gillani et al. describe AI applications such as learning analytics and adaptive learning systems, automated communications with students, early warning systems, and automated writing assessment. They seek to help educators develop literacy around the capacities and risks of these systems by providing an accessible introduction to machine learning and deep learning as well as rule-based AI. They present a cautious view, calling for scrutiny of bias in such systems and inequitable distribution of risks and benefits. They hope that engineers will collaborate deeply with educators on the development of such systems.

Jürgen Rudolph, Samson Tan, and Shannon Tan, “ ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education? ” The Journal of Applied Learning and Teaching 6, no. 1 (January 24, 2023).

Jürgen Rudolph et al. give a practically oriented overview of ChatGPT’s implications for higher education. They explain the statistical nature of large language models as they tell the history of OpenAI and its attempts to mitigate bias and risk in the development of ChatGPT. They illustrate ways ChatGPT can be used with examples and screenshots. Their literature review shows the state of artificial intelligence in education (AIEd) as of January 2023. An extensive list of challenges and opportunities culminates in a set of recommendations that emphasizes explicit policy as well as expanding digital literacy education to include AI.

Emily M. Bender, Timnit Gebru, Angela McMillan-Major, and Shmargaret Shmitchell, “ On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 ,” FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (March 2021): 610–623.

Student and faculty understanding of the risks and impacts of large language models is central to AI literacy and civic participation around AI policy. This hugely influential paper details documented and likely adverse impacts of the current data-and-resource-intensive, non-transparent mode of development of these models. Bender et al. emphasize the ways in which these costs will likely be borne disproportionately by marginalized groups. They call for transparency around the energy use and cost of these models as well as transparency around the data used to train them. They warn that models perpetuate and even amplify human biases and that the seeming coherence of these systems’ outputs can be used for malicious purposes even though it doesn’t reflect real understanding.

The authors argue that inclusive participation in development can encourage alternate development paths that are less resource intensive. They further argue that beneficial applications for marginalized groups, such as improved automatic speech recognition systems, must be accompanied by plans to mitigate harm.

Erik Brynjolfsson, “ The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence ,” Daedalus 151, no. 2 (2022): 272–87.

Erik Brynjolfsson argues that when we think of artificial intelligence as aiming to substitute for human intelligence, we miss the opportunity to focus on how it can complement and extend human capabilities. Brynjolfsson calls for policy that shifts AI development incentives away from automation toward augmentation. Automation is more likely to result in the elimination of lower-level jobs and in growing inequality. He points educators toward augmentation as a framework for thinking about AI applications that assist learning and teaching. How can we create incentives for AI to support and extend what teachers do rather than substituting for teachers? And how can we encourage students to use AI to extend their thinking and learning rather than using AI to skip learning?

Kevin Scott, “ I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale ,” Daedalus 151, no. 2 (2022): 75–84.

Brynjolfsson’s focus on AI as “augmentation” converges with Microsoft computer scientist Kevin Scott’s focus on “cognitive assistance.” Steering discussion of AI away from visions of autonomous systems with their own goals, Scott argues that near-term AI will serve to help humans with cognitive work. Scott situates this assistance in relation to evolving historical definitions of work and the way in which tools for work embody generalized knowledge about specific domains. He’s intrigued by the way deep neural networks can represent domain knowledge in new ways, as seen in the unexpected coding capabilities offered by OpenAI’s GPT-3 language model, which have enabled people with less technical knowledge to code. His article can help educators frame discussions of how students should build knowledge and what knowledge is still relevant in contexts where AI assistance is nearly ubiquitous.

Laura D. Tyson and John Zysman, “ Automation, AI & Work ,” Daedalus 151, no. 2 (2022): 256–71.

How can educators prepare students for future work environments integrated with AI and advise students on how majors and career paths may be affected by AI automation? And how can educators prepare students to participate in discussions of government policy around AI and work? Laura Tyson and John Zysman emphasize the importance of policy in determining how economic gains due to AI are distributed and how well workers weather disruptions due to AI. They observe that recent trends in automation and gig work have exacerbated inequality and reduced the supply of “good” jobs for low- and middle-income workers. They predict that AI will intensify these effects, but they point to the way collective bargaining, social insurance, and protections for gig workers have mitigated such impacts in countries like Germany. They argue that such interventions can serve as models to help frame discussions of intelligent labor policies for “an inclusive AI era.”

Todd C. Helmus, Artificial Intelligence, Deepfakes, and Disinformation: A Primer (RAND Corporation, 2022).

Educators’ considerations of academic integrity and AI text can draw on parallel discussions of authenticity and labeling of AI content in other societal contexts. Artificial intelligence has made deepfake audio, video, and images as well as generated text much more difficult to detect as such. Here, Todd Helmus considers the consequences to political systems and individuals as he offers a review of the ways in which these can and have been used to promote disinformation. He considers ways to identify deepfakes and ways to authenticate provenance of videos and images. Helmus advocates for regulatory action, tools for journalistic scrutiny, and widespread efforts to promote media literacy. As well as informing discussions of authenticity in educational contexts, this report might help us shape curricula to teach students about the risks of deepfakes and unlabeled AI.

William Hasselberger, “ Can Machines Have Common Sense? ” The New Atlantis 65 (2021): 94–109.

Students, by definition, are engaged in developing their cognitive capacities; their understanding of their own intelligence is in flux and may be influenced by their interactions with AI systems and by AI hype. In his review of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do by Erik J. Larson, William Hasselberger warns that in overestimating AI’s ability to mimic human intelligence we devalue the human and overlook human capacities that are integral to everyday life decision making, understanding, and reasoning. Hasselberger provides examples of both academic and everyday common-sense reasoning that continue to be out of reach for AI. He provides a historical overview of debates around the limits of artificial intelligence and its implications for our understanding of human intelligence, citing the likes of Alan Turing and Marvin Minsky as well as contemporary discussions of data-driven language models.

Gwo-Jen Hwang and Nian-Shing Chen, “ Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions ,” Educational Technology & Society 26, no. 2 (2023).

Gwo-Jen Hwang and Nian-Shing Chen are enthusiastic about the potential benefits of incorporating generative AI into education. They outline a variety of roles a large language model like ChatGPT might play, from student to tutor to peer to domain expert to administrator. For example, educators might assign students to “teach” ChatGPT on a subject. Hwang and Chen provide sample ChatGPT session transcripts to illustrate their suggestions. They share prompting techniques to help educators better design AI-based teaching strategies. At the same time, they are concerned about student overreliance on generative AI. They urge educators to guide students to use it critically and to reflect on their interactions with AI. Hwang and Chen don’t touch on concerns about bias, inaccuracy, or fabrication, but they call for further research into the impact of integrating generative AI on learning outcomes.

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Lauren Goodlad and Samuel Baker, “ Now the Humanities Can Disrupt ‘AI’ ,” Public Books (February 20, 2023).

Lauren Goodlad and Samuel Baker situate both academic integrity concerns and the pressures on educators to “embrace” AI in the context of market forces. They ground their discussion of AI risks in a deep technical understanding of the limits of predictive models at mimicking human intelligence. Goodlad and Baker urge educators to communicate the purpose and value of teaching with writing to help students engage with the plurality of the world and communicate with others. Beyond the classroom, they argue, educators should question tech industry narratives and participate in public discussion on regulation and the future of AI. They see higher education as resilient: academic skepticism about former waves of hype around MOOCs, for example, suggests that educators will not likely be dazzled or terrified into submission to AI. Goodlad and Baker hope we will instead take up our place as experts who should help shape the future of the role of machines in human thought and communication.

Kathryn Conrad, “ Sneak Preview: A Blueprint for an AI Bill of Rights for Education ,” Critical AI 2.1 (July 17, 2023).

How can the field of education put the needs of students and scholars first as we shape our response to AI, the way we teach about it, and the way we might incorporate it into pedagogy? Kathryn Conrad’s manifesto builds on and extends the Biden administration’s Office of Science and Technology Policy 2022 “Blueprint for an AI Bill of Rights.” Conrad argues that educators should have input into institutional policies on AI and access to professional development around AI. Instructors should be able to decide whether and how to incorporate AI into pedagogy, basing their decisions on expert recommendations and peer-reviewed research. Conrad outlines student rights around AI systems, including the right to know when AI is being used to evaluate them and the right to request alternate human evaluation. They deserve detailed instructor guidance on policies around AI use without fear of reprisals. Conrad maintains that students should be able to appeal any charges of academic misconduct involving AI, and they should be offered alternatives to any AI-based assignments that might put their creative work at risk of exposure or use without compensation. Both students’ and educators’ legal rights must be respected in any educational application of automated generative systems.

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Khan Academy Blog

Top AI-in-Education Moments of 2023: The Year Artificial Intelligence Dominated Education News

posted on January 20, 2024

By Head of Khan Academy’s Digital Marketing Team

Stephanie Yamkovenko

What was the timeline of AI in education in 2023? The year 2023 started with school districts scrambling to respond to a newly launched free app called ChatGPT and ended with more than 40 school districts and 28,000 students and teachers piloting Khan Academy’s AI-powered tutor and teaching assistant, Khanmigo, in the classroom. AI and large language models dominated headlines throughout the year, and knowledge of generative AI became even more mainstream. Take a look at a timeline of AI in education and explore the top moments in 2023, including the number of times Khan Academy made headlines with our AI-powered tutor and teaching assistant, Khanmigo.

2023 Timeline of AI in Education

January 2023

NYC education department banned ChatGPT on education department devices and internet networks . Districts and schools across the country grappled with how to respond to generative AI.

The Khan Academy team was working furiously to make Khanmigo the best possible AI-powered tutor and teaching assistant. Our Chief Learning Officer, Kristen DiCerbo, described our process in this Linkedin post .

“In September 2022, I didn’t know the term ‘prompt engineering’ but I wrote to our contacts at OpenAI that it needed ‘the right instructions’ to act like a tutor. We quickly learned how to write (‘engineer’) the instructions (‘prompts’) to the model to get it to ask questions. Even with those instructions, it really defaulted to answering questions…But we got better at prompt engineering. And we got new versions of the model, and they got better at following our instructions…I went back to two of the real experts in the field and read papers by Micki Chi and Art Graesser. Their work analyzing the moves of human tutors and this paper that summarizes the AutoTutor work over 17 years were foundational. We thought a lot about the back-and-forth between the tutor and the student, creating over 100 examples of the kinds of interactions we wanted.”

February 2023

ChatGPT was estimated to have reached 100 million monthly active users in late January, making it the fastest-growing consumer application in history. In February, OpenAI announced a monthly premium subscription.

Google launched AI chatbot Bard , Meta unveiled LLaMA, Microsoft integrated GPT into their Bing search engine, and Snapchat launched My AI.

OpenAI released a new model, GPT-4, and as a launch partner, Khan Academy had early access to the model.

On March 14, Khan Academy released our new AI-powered tutor and teaching assistant, Khanmigo , in a limited pilot period . Founder and CEO Sal Khan spoke to NBC News about our pilot.

Khan Academy released a free course entitled AI for education , which featured practical tips and strategies for using generative AI to create engaging learning experiences and improve learning outcomes.

Educators embraced AI in the classroom. Instead of running away from AI and banning it in schools, the administrators and teachers who tested Khanmigo were excited about the possibilities and understood its benefits. “Hopefully we are showing how positive this can be,” said Sal Khan in a Washington Post interview . “Most people see the power here; they just want reasonable guardrails.”

U.S. Department of Commerce Secretary Raimondo convened a task force to be competitive on the technologies that would become key to economic and national security over the coming decades. Sal Khan and six other individuals would serve on the U.S. Section of the U.S.-EU Trade and Technology Council (TTC) Talent for Growth Task Force.

Sal Khan delivered a TED Talk at TED 2023 in Vancouver on how AI can save (not destroy) education . “We’re at the cusp of using AI for probably the biggest positive transformation that education has ever seen,” he said in his talk. TED announced that Sal Khan’s talk was one of the top 10 most popular in 2023.

In May, the U.S. Department of Education released a report on artificial intelligence highlighting opportunities and possible risks of using AI to improve teaching and learning.

UNESCO brought together 40 education ministers from around the world to create a coordinated response to generative AI tools and to share policy approaches and plans on how best to integrate these tools into education.

Several school districts piloted Khanmigo with students and educators during the last few months of the 2022-23 school year . “It has been a game changer,” said a high school teacher at a partner district in Hobart, Indiana . “I’ve been able to differentiate in ways I haven’t been able to before.” A reporter from the New York Times witnessed Khan Academy’s AI-powered tutor in action at Khan Lab School and wrote that “automated study aides could usher in a profound shift in classroom teaching and learning.”

At one of the year’s biggest education technology conferences, 40 sessions, posters and presentations focused on AI in the classroom. Education leaders, teachers, coaches, and more shared everything from tips on using AI creatively in the classroom to how to make art, poetry, and music with AI. The Khan Academy team attended the conference and had a booth where educators were able to interact with live demos of Khanmigo .

Sal Khan met with President Biden and a group of AI experts on June 20 to discuss artificial intelligence’s benefits and risks . Sal shared how AI can benefit education by providing a tutor for every student and an assistant for every teacher.

Khan Academy reduced the price of Khanmigo and removed the waitlist. Thousands of parents, teachers, and adult learners signed up for access to the AI-powered tutor and teaching assistant .

President Biden announced that seven leading AI companies had voluntarily committed to managing the risks posed by AI . Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI committed to working with the White House to move toward the safe, secure, and transparent development of AI technology.

Indiana Secretary of Education Katie Jenner announced Indiana’s AI-Powered Platform Pilot Grant to help schools and districts explore opportunities for AI to help support students and teachers. Indiana school districts were invited to apply for grants, and more than $2 million was awarded to 36 recipients (a total of 112 schools). These grants made it possible for more than 45,000 students statewide to interact with an AI-powered platform during the remainder of the 2023-2024 school year.

Thousands of educators attended Khan Academy’s webinar about how to use AI in the classroom. Alongside a group of other educators, Kristen DiCerbo, Khan Academy’s Chief Academic Officer, presented a webinar to teachers that answered questions about using AI to design lesson plans, integrating AI into the classroom routine, and using AI to save time.

August 2023

Khan Academy collaborated with Code.org, ETS, and ISTE to bring an AI 101 course to teachers , a free professional learning series that instructs every teacher on how to use AI safely and ethically in their classrooms.

Bill Gates interviewed Sal Khan on the Unconfuse Me with Bill Gates podcast to discuss how AI can help close the education gap. “I’ve been a fan and supporter of Sal Khan’s work for a long time and recently had him on my podcast to talk about education and AI,” Gates said on Linkedin . “For decades, I’ve been excited about all the ways that software would make teachers’ jobs easier and help students learn. These changes are finally starting to happen in a dramatic way. The current state of the art is Khanmigo, a text-based bot created by Khan Academy.”

IBM released a survey about the massive need to reskill the workforce. More than half of the 3,000 executives surveyed estimated that 40% of their workforce would need to be reskilled as their businesses implemented AI and automation over the next three years. Millions of workers raced to acquire new AI-related skills.

September 2023

Gallup released a survey citing fears among 22% of American workers that technology would make their jobs obsolete in the near future. The fear of tech grew more in the past two years than at any time since Gallup started measuring the trend in 2017. Other job concerns remained stable.

October 2023

Business Insider released its AI 100 list , which included people who were not only pushing the boundaries of the field but who were also trying to ensure that AI developed steadily and responsibly. Sal Khan was included on the list for launching Khanmigo and “embracing new technology again in the form of generative AI.”

Khan Academy announced free new courses in digital literacy . The courses were designed to help learners stay informed and learn digital literacy skills as they navigated the digital world. The courses included those on AI, internet safety, and social media literacy.

TeachAI released the AI Guidance for Schools Toolkit geared toward school district administrators, state education officials, and global education leaders. The toolkit provided useful guidance for setting policies and spotlighted examples of exemplary practices.

November 2023

Khan Academy further reduced the price of Khanmigo thanks to significant engineering strides that reduced the high computational costs of AI . As a nonprofit, Khan Academ’y’s goal has always been to ensure that cutting-edge AI educational tools like Khanmigo were not a luxury but instead a resource available to all. For $4/month or $44/year , parents, educators, and adult learners can enjoy unlimited access to Khanmigo. Khan Academy also reduced the district price from $60 per student/per year to $35 per student/per year. During this school year, more than 40 school districts and 28,000 students and teachers are piloting Khanmigo in the classroom. Learn more about our district Khanmigo offerings .

Common Sense Media launched inaugural AI product ratings so parents could better understand how AI works and find out which tools were the most trustworthy. Khanmigo received an overall 4-star rating from Common Sense Media , making it one of their top-rated AI-for-education tools, above others like ChatGPT and Bard.

Good Morning America showcased how Khanmigo is transforming the classroom experience and bridging the tutoring gap. The segment took viewers inside First Avenue Elementary School in Newark, New Jersey, to show Khanmigo in action.

Only two states—California and Oregon—have issued policy guidance for schools on AI platforms , according to a report by The Center on Reinventing Public Education (CRPE) . Eleven other states are developing guidance: Arizona, Connecticut, Maine, Mississippi, Nebraska, New York, Ohio, Pennsylvania, Virginia, Vermont, and Washington.

December 2023

A research study by Stanford University found that AI tools have not boosted the overall cheating rates in high schools in the U.S., despite the widespread fears in the beginning of the year as school administrators and educators grappled with the popularization of AI-powered chatbots.

Fortune hosted an AI conference to examine new business cases for AI with C-suite executives, leading academics, and prominent policymakers. Sal Khan spoke to the audience about why Khan Academy decided not to run away from AI but, instead, vowed to be the trusted brand that puts the right guardrails in place.

“In hindsight, it was a blessing that ChatGPT launched when it did,” Sal Khan said at the Fortune conference . “Because it allowed everyone to process a very imperfect tool and, frankly, by about March 2023, they started saying, ‘If only someone we could trust would put the right guardrails around this, so it avoids cheating, makes it transparent, helps solve the bias.’ Then we’re like, ‘Here you go.’”

Bill Gates hails AI education tools in year-end letter — calls Khanmigo ‘mind blowing.’ In his annual end-of-year letter, Bill Gates praised Khanmigo and other advancements in AI-powered education. In his own words he calls Khanmigo and other AI learning tools “mind-blowing because they are tailored to each individual learner.” Gates emphasized how Khanmigo is “already remarkable” and shared he has confidence Khanmigo and similar platforms will only get better in the years to come.

What will the timeline of AI in 2024 look like?

We hope you enjoyed this look back of the top moments from 2023. Looking ahead, it’s likely that the timeline of AI in education has only just begun. The year 2023 has been a pivotal chapter, showcasing how AI can enhance learning and teaching. The journey along the AI timeline is just beginning, holding immense promise for the future of education.

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A new cross-disciplinary research initiative at MIT aims to promote the understanding and use of AI across all segments of society. The effort, called Responsible AI for Social Empowerment and Education ( RAISE ), will develop new teaching approaches and tools to engage learners in settings from preK-12 to the workforce.

“People are using AI every day in our workplaces and our private lives. It’s in our apps, devices, social media, and more. It’s shaping the global economy, our institutions, and ourselves. Being digitally literate is no longer enough. People need to be AI-literate to understand the responsible use of AI and create things with it at individual, community, and societal levels,” says RAISE Director Cynthia Breazeal, a professor of media arts and sciences at MIT.

“But right now, if you want to learn about AI to make AI-powered applications, you pretty much need to have a college degree in computer science or related topic,” Breazeal adds. “The educational barrier is still pretty high. The vision of this initiative is: AI for everyone else — with an emphasis on equity, access, and responsible empowerment.”

Headquartered in the MIT Media Lab, RAISE is a collaboration with the MIT Schwarzman College of Computing and MIT Open Learning. The initiative will engage in research coupled with education and outreach efforts to advance new knowledge and innovative technologies to support how diverse people learn about AI as well as how AI can help to better support human learning. Through Open Learning and the Abdul Latif Jameel World Education Lab (J-WEL), RAISE will also extend its reach into a global network where equity and justice are key.

The initiative draws on MIT’s history as both a birthplace of AI technology and a leader in AI pedagogy. “MIT already excels at undergraduate and graduate AI education,” says Breazeal, who heads the Media Lab’s Personal Robots group and is an associate director of the Media Lab. “Now we’re building on those successes. We’re saying we can take a leadership role in educational research, the science of learning, and technological innovation to broaden AI education and empower society writ large to shape our future with AI.”

In addition to Breazeal, RAISE co-directors are Hal Abelson, professor of computer science and education; Eric Klopfer, professor and director of the Scheller Teacher Education Program; and Hae Won Park, a research scientist at the Media Lab. Other principal leaders include Professor Sanjay Sarma, vice president for open learning. RAISE draws additional participation from dozens of faculty, staff, and students across the Institute.

“In today’s rapidly changing economic and technological landscape, a core challenge nationally and globally is to improve the effectiveness, availability, and equity of preK-12 education, community college, and workforce development. AI offers tremendous promise for new pedagogies and platforms, as well as for new content. Developing and deploying advances in computing for the public good is core to the mission of the Schwarzman College of Computing, and I’m delighted to have the College playing a role in this initiative,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing.

The new initiative will engage in research, education, and outreach activities to advance four strategic impact areas: diversity and inclusion in AI, AI literacy in preK-12 education, AI workforce training, and AI-supported learning. Success entails that new knowledge, materials, technological innovations, and programs developed by RAISE are leveraged by other stakeholder AI education programs across MIT and beyond to add value to their efficacy, experience, equity, and impact.

RAISE will develop AI-augmented tools to support human learning across a variety of topics. “We’ve done a lot of work in the Media Lab around companion AI,” says Park. “Personalized learning companion AI agents such as social robots support individual students’ learning and motivation to learn. This work provides an effective and safe space for students to practice and explore topics such as early childhood literacy and language development.”

Diversity and inclusion will be embedded throughout RAISE’s work, to help correct historic inequities in the field of AI. “We're seeing story after story of unintended bias and inequities that are arising because of these AI systems,” says Breazeal. “So, a mission of our initiative is to educate a far more diverse and inclusive group of people in the responsible design and use of AI technologies, who will ultimately be more representative of the communities they will be developing these products and services for.”

This spring, RAISE is piloting a K-12 outreach program called Future Makers. The program brings engaging, hands-on learning experiences about AI fundamentals and critical thinking about societal implications to teachers and students, primarily from underserved or under-resourced communities, such as schools receiving Title I services.

To bring AI to young people within and beyond the classroom, RAISE is developing and distributing curricula, teacher guides, and student-friendly AI tools that enable anyone, even those with no programming background, to create original applications for desktop and mobile computing. “ Scratch and App Inventor are already in the hands of millions of learners worldwide,” explains Abelson. “RAISE is enhancing these platforms and making powerful AI accessible to all people for increased creativity and personal expression.”

Ethics and AI will be a central component to the initiative’s curricula and teaching tools. “Our philosophy is, have kids learn about the technical concepts right alongside the ethical design practices,” says Breazeal. “Thinking through the societal implications can’t be an afterthought.”

“AI is changing the way we interact with computers as consumers as well as designers and developers of technology,” Klopfer says. “It is creating a new paradigm for innovation and change. We want to make sure that all people are empowered to use this technology in constructive, creative, and beneficial ways.”

“Connecting this initiative not only to [MIT’s schools of] engineering and computing, but also to the School of Humanities, Arts and Social Sciences recognizes the multidimensional nature of this effort,” Klopfer adds.

Sarma says RAISE also aims to boost AI literacy in the workforce, in part by adapting some of their K-12 techniques. “Many of these tools — when made somewhat more sophisticated and more germane to the adult learner — will make a tremendous difference,” says Sarma. For example, he envisions a program to train radiology technicians in how AI programs interpret diagnostic imagery and, vitally, how they can err.

“AI is having a truly transformative effect across broad swaths of society,” says Breazeal. “Children today are not only digital natives, they’re AI natives. And adults need to understand AI to be able to engage in a democratic dialogue around how we want these systems deployed.”

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Prof. Eric Klopfer, co-director of the RAISE initiative (Responsible AI for Social Empowerment in Education), speaks with GBH reporter Diane Adame about the importance of providing students guidance on navigating artificial intelligence systems. “I think it's really important for kids to be aware that these things exist now, because whether it's in school or out of school, they are part of systems where AI is present,” says Klopfer. “Many humans are biased. And so the [AI] systems express those same biases that they've seen online and the data that they've collected from humans.”

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New York Times reporter Natasha Singer spotlights the Day of AI, an MIT RAISE program aimed at teaching K-12 students about AI. “Because AI is such a powerful new technology, in order for it to work well in society, it really needs some rules,” said MIT President Sally Kornbluth. Prof. Cynthia Breazeal, MIT’s dean of digital learning, added: “We want students to be informed, responsible users and informed, responsible designers of these technologies.”

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How K–12 Schools Can Use Artificial Intelligence in Education

Alexandra Frost is a Cincinnati-based freelance journalist, content marketing writer, copywriter and editor published in The Washington Post , Glamour , Shape , Today’s Parent , Reader’s Digest , Parents , Women’s Health and Insider. Alex has a Master of Arts in Teaching degree and a bachelor’s degree in mass communications/journalism, both from Miami University near Cincinnati. She also taught high school for 10 years, specializing in media education.

What role will artificial intelligence play in the future of education? For educators, AI can feel like an exciting development — or a terrifying unknown.

AI technology is advancing quickly and creating solutions once thought impossible. It’s widely available in various technologies and, in many places, already being integrated into the classroom . The pandemic spurred the development of educational technology out of necessity, including the development of AI. Suddenly, educators needed ways to obtain more information virtually.

“We were starting to work on AI during the pandemic, but it sped up because there was a huge demand for it,” says Mike Tholfsen, principal group product manager at Microsoft Education . “All these things were happening online, and teachers were saying. ‘I don’t know what’s happening in my classroom anymore.’”

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With educators busier than ever, Tholfsen says, the greatest benefit AI can offer them is time. AI programs can gather data teachers would traditionally have to gather themselves manually.

What Is Artificial Intelligence?

Trying to define artificial intelligence is a bit like asking about the meaning of life: You will get a slightly different answer from everyone. At its core, AI is an area of computer science addressing the simulation of intelligent behavior in computers.

Michelle Zimmerman , a classroom teacher, researcher and school leader at Renton Prep Christian School in Washington state and author of the book Teaching AI: Exploring New Frontiers for Learning , notes that psychologists and neurologists in the field don’t even agree on what counts as human intelligence.

The definition also changes over time. Not too long ago, simple calculators were considered AI, while the term now is associated with a variety of innovative technologies, such as those that power content filtering and endpoint security .

EXPLORE THE TREND: Here are three ways classroom use of artificial intelligence will grow in 2022.

Artificial Intelligence vs. Machine Learning: What’s the Difference?

Though not all AI involves machine learning, it is a popular subcategory of the technology. Machine learning refers to machines that process vast amounts of data and also have the capacity to get better at it the more they “learn,” Zimmerman says.

“You can train models with machine learning to improve things. An example is speech-to-text technology,” Tholfsen says.

“Machine learning needs a lot of data to train it to look for patterns and understand what it is looking for. The more data, the more refined or accurate the results. The results, though, are only as good as the data included,” Zimmerman says.

READ THE WHITE PAPER: Achieve effective data analytics.

How Can AI Be Used in K–12 Education?

AI is already playing a role in many classrooms and has promising benefits that can be integrated now and in the future.

Intelligent tutors: What if an AI program could play the role of a teacher or coach, leading students through lessons and even motivating them? Nancye Black , founder of the Block Uncarved and project lead for ISTE ’s AI Explorations program, says AI can support learners in a variety of ways. As a Columbia University researcher, she’s exploring how avatar interactions impact students. “There is some really promising research around the use of AI agents supporting girls and students of color, who are able to — in a lower-risk situation — ask for help and have social learning, even when they are learning independently,” Black says.

Reading workshops: If educators could host reading workshops around the classroom with each individual student, they would. Instead, AI-powered products such as Microsoft’s Immersive Reader can help educators focus on improving education for the 1 in 7 learners who have a disability, Tholfsen says. The product uses text decoding solutions to individualize instruction.

Michelle Zimmerman Classroom Teacher, Researcher and School Leader, Renton Prep Christian School

Translation capabilities: Translation technology is improving quickly, and these tools include more dialects and language nuances every day. A teacher in New York, for example, used AI technology to host a virtual parent night for families who speak multiple different languages, Tholfsen says. Microsoft Translate allows the teacher to generate a code, which broadcasts to everyone connecting to the stream. It translates the speaker’s language into listeners’ languages without the necessity of a human interpreter. “Listeners can type or speak back in their languages, and it cross-translates, so when you type back in Spanish, it goes to me in English, translates to Mike in Italian, and to the person speaking Arabic or Chinese,” Tholfsen says. “It’s like the Star Trek universal translator.”

Low-vision accessibility: Accessibility checkers are helping educators increase access for low-vision students . “We use AI and computer vision to identify what is in an image and generate a caption,” Tholfsen says. “It’s a massive timesaver to do auto-captioning on images, so people are much more likely to make their content accessible.”

The implementation of AI tools won’t replace educators but will instead help them save time. The tech can be customized to fit any classroom, putting educators in control of the AI tools — not the other way around.

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How chatgpt and similar ai will disrupt education.

Teachers are concerned about cheating and inaccurate information

Students are turning to ChatGPT for homework help. Educators have mixed feeling about the tool and other generative AI.

Glenn Harvey

Who said what?

When prompted, ChatGPT can craft answers that sound surprisingly like those from a student. We asked middle school and high school students from across the country, all participants in our Science News Learning education program , to answer some basic science questions in two sentences or less. The examples throughout the story compare how students responded with how ChatGPT responded when asked to answer the question at the same grade level.

What effect do greenhouse gases have on the Earth?

Agnes b. | grade 11, harbor city international school, minn..

Greenhouse gases effectively trap heat from dissipating out of the atmosphere, increasing the amount of heat that remains near Earth in the troposphere.

Greenhouse gases trap heat in the Earth’s atmosphere, causing the planet to warm up and leading to climate change and its associated impacts like sea level rise, more frequent extreme weather events and shifts in ecosystems.

The good, bad and weird of ChatGPT

ChatGPT has wowed its users. “It’s so much more realistic than I thought a robot could be,” says Avani Rao, a sophomore in high school in California. She hasn’t used the bot to do homework. But for fun, she’s prompted it to say creative or silly things. She asked it to explain addition, for instance, in the voice of an evil villain.

Given how well it performs, there are plenty of ways that ChatGPT could level the playing field for students and others working in a second language or struggling with composing sentences. Since ChatGPT generates new, original material, its text is not technically plagiarism.

Students could use ChatGPT like a coach to help improve their writing and grammar, or even to explain subjects they find challenging. “It really will tutor you,” says Vogelsinger, who had one student come to him excited that ChatGPT had clearly outlined a concept from science class.

Educators could use ChatGPT to help generate lesson plans, activities or assessments — perhaps even personalized to address the needs or goals of specific students.

Xiaoming Zhai, an expert in science education at the University of Georgia in Athens, tested ChatGPT to see if it could write an academic paper . He was impressed with how easy it was to summarize knowledge and generate good writing using the tool. “It’s really amazing,” he says.

All of this sounds wonderful, but really big problems exist. Most worrying, ChatGPT and other similar tools can often get things very wrong. They don’t pull facts from databases. Rather, they are trained to generate new text that sounds natural. They remix language without understanding it, which can lead to glaring mistakes.

The news website CNET came under fire earlier this year for using AI to churn out dozens of articles, many of them packed with errors. In an early advertisement for the Bard chatbot, it made a factual error about the James Webb Space Telescope, incorrectly claiming that it had taken the very first picture of an exoplanet. And ChatGPT said in a conversation posted on Twitter that the fastest marine mammal was the peregrine falcon. A falcon, of course, is a bird and doesn’t live in the ocean.

ChatGPT is “confidently wrong,” says Casey Fiesler, an expert in the ethics of technology at the University of Colorado Boulder. “There are mistakes and bad information.” She has made multiple TikTok videos about the pitfalls of ChatGPT .

Most of ChatGPT’s training data come from before September 2021, and it does not provide sources for its information. If asked for sources, it makes them up, Fiesler revealed in one video . Zhai, who sees the tool as an assistant, discovered the exact same thing. When he asked ChatGPT for citations, it gave him sources that looked correct. But they didn’t actually exist.

Define the term biodiversity.

Dante a. | grade 10, clark magnet high school, calif..

Biodiversity refers to the variety of living species and ecosystems that exist in a particular region or on the planet as a whole. It encompasses the different genes, species and ecosystems that make up the natural world and the relationships between them.

Biodiversity refers to the variety of living organisms that inhabit the Earth and the ecosystems they form. It includes the diversity of species, genes and ecosystems, and is important for maintaining the balance of nature and sustaining life on our planet.

How ChatGPT works

ChatGPT’s mistakes make sense if you know how it works. “It doesn’t reason. It doesn’t have ideas. It doesn’t have thoughts,” explains Emily M. Bender, a computational linguist at the University of Washington in Seattle.

ChatGPT was developed using at least two types of machine learning. The primary type is a large language model based on an artificial neural network. Loosely inspired by how neurons in the brain interact, this computing architecture finds statistical patterns in vast amounts of data.

A language model learns to predict what words will come next in a sentence or phrase by churning through vast amounts of text. It places words and phrases into a multidimensional map that represents their relationships to one another. Words that tend to come together, like peanut butter and jelly, end up closer together in this map.

The size of an artificial neural network is measured in parameters. These internal values get tweaked as the model learns. In 2020, OpenAI released GPT-3. At the time, it was the biggest language model ever, containing 175 billion parameters. It had trained on text from the internet as well as digitized books and academic journals. Training text also included transcripts of dialog, essays, exams and more, says Sasha Luccioni, a Montreal-based researcher at Hugging Face, a company that builds AI tools.

OpenAI improved upon GPT-3 to create GPT-3.5. In early 2022, the company released a fine-tuned version of GPT-3.5 called InstructGPT. This time, OpenAI added a new type of machine learning. Called reinforcement learning with human feedback, it puts people into the training process. These workers check the AI’s output. Responses that people like get rewarded. Human feedback can also help reduce hurtful, biased or inappropriate responses. This fine-tuned language model powers freely available ChatGPT. As of March, paying users receive answers powered by GPT-4, a bigger language model.

During ChatGPT’s development, OpenAI added extra safety rules to the model. It will refuse to answer certain sensitive prompts or provide harmful information. But this step raises another issue: Whose values are programmed into the bot, including what it is — or is not — allowed to talk about?

OpenAI is not offering exact details about how it developed and trained ChatGPT. The company has not released its code or training data. This disappoints Luccioni because it means the tool can’t benefit from the perspectives of the larger AI community. “I’d like to know how it works so I can understand how to make it better,” she says.

When asked to comment on this story, OpenAI provided a statement from an unnamed spokesperson. “We made ChatGPT available as a research preview to learn from real-world use, which we believe is a critical part of developing and deploying capable, safe AI systems,” the statement said. “We are constantly incorporating feedback and lessons learned.” Indeed, some experimenters have gotten the bot to say biased or inappropriate things despite the safety rules. OpenAI has been patching the tool as these problems come up.

ChatGPT is not a finished product. OpenAI needs data from the real world. The people who are using it are the guinea pigs. Notes Bender: “You are working for OpenAI for free.”

What are black holes and where are they found?

Althea c. | grade 11, waimea high school, hawaii.

A black hole is a place in space where gravity is so strong that nothing, not even light, may come out.

Black holes are extremely dense regions in space where the gravity is so strong that not even light can escape, and they are found throughout the universe.

ChatGPT’s academic performance

How good is ChatGPT in an academic setting? Catherine Gao, a doctor and medical researcher at Northwestern University’s Feinberg School of Medicine in Chicago, is part of one team of researchers that is putting the tool to the test.

Gao and her colleagues gathered 50 real abstracts from research papers in medical journals and then, after providing the titles of the papers and the journal names, asked ChatGPT to generate 50 fake abstracts. The team asked people familiar with reading and writing these types of research papers to identify which were which .

“I was surprised by how realistic and convincing the generated abstracts were,” Gao says. The reviewers mistook roughly one-third of the AI-generated abstracts as human-generated.

In another study, Will Yeadon and colleagues tested whether AI tools could pass a college exam . Yeadon, a physics instructor at Durham University in England, picked an exam from a course that he teaches. The test asks students to write five short essays about physics and its history. Students have an average score of 71 percent, which he says is equivalent to an A in the United States.

Yeadon used the tool davinci-003, a close cousin of ChatGPT. It generated 10 sets of exam answers. Then Yeadon and four other teachers graded the answers using their typical standards. The AI also scored an average of 71 percent. Unlike the human students, though, it had no very low or very high marks. It consistently wrote well, but not excellently. For students who regularly get bad grades in writing, Yeadon says, it “will write a better essay than you.”

These graders knew they were looking at AI work. In a follow-up study, Yeadon plans to use work from the AI and students and not tell the graders whose is whose.

What is heat?

Precious a. | grade 6, canyon day junior high school, ariz..

Heat is the transfer of kinetic energy from one medium or object to another, or from an energy source to a medium or object through radiation, conduction and convection.

Heat is a type of energy that makes things warmer. It can be produced by burning something or through electricity.

Tools to check for cheating

When it’s unclear whether ChatGPT wrote something or not, other AI tools may help. These tools typically train on AI-generated text and sometimes human-generated text as well. They can tell you how likely it is that text was composed by an AI. Many of the existing tools were trained on older language models, but developers are working quickly to put out new, improved tools.

A company called Originality.ai sells access to a tool that trained on GPT-3. Founder Jon Gillham says that in a test of 10,000 samples of texts composed by models based on GPT-3, the tool tagged 94 percent of them correctly as AI-generated. When ChatGPT came out, his team tested a smaller set of 20 samples. Each only 500 words in length, these had been created by ChatGPT and other models based on GPT-3 and GPT-3.5. Here, Gillham says, the tool “tagged all of them as AI-generated. And it was 99 percent confident, on average.”

In late January 2023, OpenAI released its own free tool for spotting AI writing, cautioning that the tool was “not fully reliable.” The company is working to add watermarks to its AI text, which would tag the output as machine-generated, but doesn’t give details on how. Gillham describes one possible approach: Whenever it generates text, the AI ranks many different possible words for each position. If its developers told it to always choose the word ranked in third place rather than first place at specific points in its output, those words could act as a fingerprint, he says.

As AI writing tools improve, the tools to sniff them out will need to improve as well. Eventually, some sort of watermark might be the only way to sort out true authorship.

What is DNA and how is it organized?

Luke m. | grade 8, eastern york middle school, pa..

DNA, or deoxyribonucleic acid, is kept inside the cells of living things, where it holds instructions for the genetics of the organism it is inhabiting.

DNA is like a set of instructions that tells our cells what to do. It’s organized into structures called chromosomes, which contain all of the DNA in a cell.

ChatGPT and the future of writing

There’s no doubt we will soon have to adjust to a world in which computers can write for us. But educators have made these sorts of adjustments before. As high school student Rao points out, Google was once seen as a threat to education because it made it possible to look up facts instantly. Teachers adapted by coming up with teaching and testing materials that don’t depend as heavily on memorization.

Now that AI can generate essays and stories, teachers may once again have to rethink how they teach and test. Rao says: “We might have to shift our point of view about what’s cheating and what isn’t.”

Some teachers will prevent students from using AI by limiting access to technology. Right now, Vogelsinger says, teachers regularly ask students to write out answers or essays at home. “I think those assignments will have to change,” he says. But he hopes that doesn’t mean kids do less writing.

Teaching students to write without AI’s help will remain essential, agrees Zhai. That’s because “we really care about a student’s thinking,” he stresses. And writing is a great way to demonstrate thinking. Though ChatGPT can help a student organize their thoughts, it can’t think for them, he says.

Kids still learn to do basic math even though they have calculators (which are often on the phones they never leave home without), Zhai acknowledges. Once students have learned basic math, they can lean on a calculator for help with more complex problems.

In the same way, once students have learned to compose their thoughts, they could turn to a tool like ChatGPT for assistance with crafting an essay or story. Vogelsinger doesn’t expect writing classes to become editing classes, where students brush up AI content. He instead imagines students doing prewriting or brainstorming, then using AI to generate parts of a draft, and working back and forth to revise and refine from there.

Though he’s overwhelmed about the prospect of having to adapt his teaching to another new technology, he says he is “having fun” figuring out how to navigate the new tech with his students.

Rao doesn’t see AI ever replacing stories and other texts generated by humans. Why? “The reason those things exist is not only because we want to read it but because we want to write it,” she says. People will always want to make their voices heard.

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June 24, 2024

Indiana gave teachers a chance to try out artificial intelligence. here's what comes next, rachel fradette.

Students at Stonewall Elementary in Lexington, Ky. each summarized a text about boxing champion and Kentucky icon Muhammad Ali then tried to figure out which summaries were penned by classmates and which was written by the chatbot in February 2023.

Thousands of Indiana students and classroom educators took on an assignment to explore artificial intelligence, or AI, this last school year.

State education leaders hoped what they and their teachers learned could lead to future use of AI in classrooms although specific funding for the venture has dried up.

The Department of Education tasked school districts to apply for grant money to try out AI concepts. Department leaders presented some findings from the classroom to the State Board of Education this month.

“If AI is here, how might we leverage AI for the good,” Secretary of Education Katie Jenner said. “How could it help us solve some of the problems?”

Jenner said educators in local school districts inspired the pilot after many approached the department seeking ways to incorporate it ethically.

The program focused on ways to decrease teacher workloads and increase 1-on-1 tutoring for students, Jenner said.

Surveys from the program revealed somewhat positive feedback from educators who put AI to the test for classroom tasks.

But what happens after the pilot could be up to school districts.

Digital learning grants

The state targeted around $2 million in pandemic relief funds to conduct the pilot.

Molly Williams, a spokeswoman for the education department, said there’s no plans to continue the pilot program.

However, some school districts and educators will be able to utilize a Digital Learning Grant through IDOE to continue AI programming and other digital learning opportunities.

They can request up to $50,000 to fund projects tied to AI, game based learning and virtual reality, among other things. The 2024 applications have closed. About 45 school districts and charter schools participated in 2023.

There are also grants to support professional development in artificial intelligence, virtual instruction and integrating technology for educators who spend more than half of their time focused on digital learning.

What did educators in the pilot think of AI?

About 2,500 teachers participated in the AI pilot while only 625 educators responded to a state survey about its successes and failures. Of those, more than half said artificial intelligence had a positive influence on student learning.

Educators put AI to work for classroom tasks, like lesson plans, rubric and assessment creation and to further knowledge of subjects. Schools appeared to have facilitated some feedback from students although there was no formal survey shared by IDOE.

Nearly forty traditional public school districts and charter schools received grants last year to explore AI platforms. They picked the program as long as they met some state requirements.

Schools chose various AI education-focused companies and startups including Amira Learning, SchoolJoy, Edia and Chat for Schools.

All have varied features but differ from generative AI platforms, like ChatGPT. That was an important distinction, Jenner said.

Despite a mostly positive start, educators reported some shortcomings from the platforms.

Heather Herring, a course access specialist for the education department, said educators found bugs in navigating the platforms, microphone usage and speech recognition.

That feedback will be shared with artificial intelligence providers directly, Herring said.

What comes next?

Kyungbin Kwon, an Indiana University associate professor, said teachers need continued support and professional development to move forward and try out AI concepts, which could enhance their teaching methods, he said.

“Teachers should understand what's going on and the work functionalities available for them,” Kwon said. “At the time, they may have some kind of sense of judgment about AI integration.”

Kwon studies AI and its impact on students in the classroom. In 2023, Kwon published a study about middle school age students’ conceptions of AI and how they change those impressions during an AI-focused summer camp.

Some educators may be reluctant to introduce AI in the classroom, Kwon said academic integrity is why. But there are ways to use AI for learning, not cheating, he said.

“We cannot block generative AI or other AI tools from students because there are many potentials and benefits,” Kwon said.

Last year, Hamilton Southeastern Schools added the misuse of artificial intelligence to student handbooks. If a student turns in AI-generated work once, like if they create an essay through ChatGPT, they could lose credit for the assignment and have their parents notified.

Students who are dishonest again will be sent to school leaders and may be withdrawn from the class with a failing grade, according to high school handbooks. And HSE is not alone as school districts discover how to manage AI.

“There is a time and effort required for this process.” Kwon said. “Once teachers and administrators see the potential then they may change their mind and then they will have a more positive attitude towards this.”

Rachel Fradette is the WFYI Statehouse education reporter. Contact Rachel at [email protected] .

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Watch CBS News

Schools, universities turning to artificial intelligence to transform education

By Paul Gessler

August 30, 2023 / 7:59 PM EDT / CBS Baltimore

BALTIMORE - As computers did a generation before, advancements in technology are changing how students learn and how teachers teach.

The rise of artificial intelligence presents a mixed bag of opportunities to learn and get around learning.

A.I. is not going away, and some institutions and districts are embracing it.

It's a free teacher's aide for educators who choose to use it.

Artificial intelligence tools can write up a syllabus or create lesson plans in seconds.

"A.I. will transform, not just education, but business and society," said Dr. Dr. Dobin Yim, from Loyola University Maryland.

Dr. Yim researches A.I. and integrates it into his curriculum.

"So, this won't replace teachers?" WJZ Paul Gessler asked.

"I don't think so, although, I think if you decide to embrace it, it will democratize learning," Dr. Yim said.

Democratizing learning, Dr. Yim says, because A.I. is well-versed across many subjects.

"Whether you have a learning disability or want to accelerate your learning journey, A.I., to me, is a personal tutor," Dr. Yim said.

A.I. is a personal tutor which is why Dr. Yim urges teachers to get acquainted with it.

"I think everyone should at least try it out to see if this is the right tool for you or not," Dr. Yim said.

"I think the balance always is how is technology aiding education," added Cheryl Bost, Maryland State Teacher's Union President.

Bost says teachers need guidance and training for evolving challenges.

"We're just scratching the surface of what it can do, what it can provide benefits, and what challenges it presents," Bost said.

Some of the challenges include plagiarism.

Instead of writing a history paper, you can ask ChatGPT, and within seconds, an essay appears.

But, Dr. Yim said there are patterns teachers can detect.

"If a teacher is well-versed in it, this seems like it was generated by ChatGPT, they can ask the student, 'Did you do this on your own?'"

Then, there's A.I. out of the classroom.

Some school districts are leaning on it to enhance safety.

Baltimore City Public Schools are joining dozens of other districts across the country, using a weapons detection system meant to distinguish whether a student has a gun on campus.

"The goal of the Evolv system is to let kids come to focus on learning and teachers focus on teaching," said Anil Chitkara, the company's co-founder.

Some universities are creating A.I. courses.

"We don't know where it will go and I think we are all learning together," said Alyssa Moon, from Western Michigan University.

Dr. Yim says A.I. can be misused by anyone who uses it, students or teachers, which is why school leaders should get out in front of it.

"Should you use it? I think that really relies on the comfort level of the instructor and also the institution," Dr. Yim said.

Why are patients turning to artificial intelligence chatbots for medical advice?
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Paul Gessler is a general assignment reporter at WJZ with a decade of experience reporting in Baltimore.

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The challenges and opportunities of Artificial Intelligence in education

Artificial Intelligence (AI) is producing new teaching and learning solutions that are currently being tested globally. These solutions require advanced infrastructures and an ecosystem of thriving innovators. How does that affect countries around the world, and especially developing nations? Should AI be a priority to tackle in order to reduce the digital and social divide?

These are some of the questions explored in a Working Paper entitled ‘ Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development ’ presented by UNESCO and ProFuturo at Mobile Learning Week 2019 . It features cases studies on how AI technology is helping education systems use data to improve educational equity and quality.

Concrete examples from countries such as China, Brazil and South Africa are examined on AI’s contribution to learning outcomes, access to education and teacher support. Case studies from countries including the United Arab Emirates, Bhutan and Chile are presented on how AI is helping with data analytics in education management.

The Paper also explores the curriculum and standards dimension of AI, with examples from the European Union, Singapore and the Republic of Korea on how learners and teachers are preparing for an AI-saturated world.

Beyond the opportunities, the Paper also addresses the challenges and policy implications of introducing AI in education and preparing students for an AI-powered future. The challenges presented revolve around:

Developing a comprehensive view of public policy on AI for sustainable development : The complexity of the technological conditions needed to advance in this field require the alignment of multiple factors and institutions. Public policies have to work in partnership at international and national levels to create an ecosystem of AI that serves sustainable development.
Ensuring inclusion and equity for AI in education : The least developed countries are at risk of suffering new technological, economic and social divides with the development of AI. Some main obstacles such as basic technological infrastructure must be faced to establish the basic conditions for implementing new strategies that take advantage of AI to improve learning.
Preparing teachers for an AI-powered education : Teachers must learn new digital skills to use AI in a pedagogical and meaningful way and AI developers must learn how teachers work and create solutions that are sustainable in real-life environments.
Developing quality and inclusive data systems : If the world is headed towards the datafication of education, the quality of data should be the main chief concern. It´s essential to develop state capabilities to improve data collection and systematization. AI developments should be an opportunity to increase the importance of data in educational system management.
Enhancing research on AI in education : While it can be reasonably expected that research on AI in education will increase in the coming years, it is nevertheless worth recalling the difficulties that the education sector has had in taking stock of educational research in a significant way both for practice and policy-making.
Dealing with ethics and transparency in data collection, use and dissemination : AI opens many ethical concerns regarding access to education system, recommendations to individual students, personal data concentration, liability, impact on work, data privacy and ownership of data feeding algorithms. AI regulation will require public discussion on ethics, accountability, transparency and security.

The key discussions taking place at Mobile Learning Week 2019 address these challenges, offering the international educational community, governments and other stakeholders a unique opportunity to explore together the opportunities and threats of AI in all areas of education.

Download the working paper

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EDITORIAL article

Editorial: artificial intelligence for education.

$\r\nManuel Gentile$

1 Institute for Educational Technology, National Research Council of Italy, Palermo, Italy
2 EA4023 Laboratoire d'Informatique de l'Université du Mans (LIUM), Le Mans, France
3 Department of Computing Science, Umeå University, Umeå, Sweden

Editorial on the Research Topic Artificial intelligence for education

When the Research Topic “ Artificial intelligence for education ” was launched in June 2021, the impact that advances in artificial intelligence would have on the education sector was not entirely predictable.

However, the long and close relationship between research in the two fields of AI and Education was common knowledge. Indeed, since understanding how people learn is closely related to the idea of intelligence, or given that knowledge representation has been one of the most prominent Research Topics in AI, a natural connection between the areas of knowledge concerning Artificial Intelligence and Education emerged even before the term “Artificial Intelligence” was coined ( Turing, 1950 ).

Scholars in the field of artificial intelligence have always looked to the field of education as one of their favorite application areas. From the realization of the logic theorist ( Newell and Simon, 1956 ) to the emergence in the 1990s of cognitive architectures ( Laird et al., 1987 ; Newell, 1990 ), many of the innovations in the field of AI have found a direct application in the field of education, in the realization of tools such as expert systems to support learning processes and intelligent tutor systems ( Anderson et al., 1985 ; Bidarra et al., 2020 ).

The new renaissance of AI, marked by recent innovations in the field of deep learning, has in recent years outlined a landscape in which a strong impact could also be expected in education. However, the disruption caused by the market introduction of ChatGPT in November 2022 coincided with the final part of the call for papers for this Research Topic. This timing has therefore cut off, from many of the studies presented in this Research Topic, all the latest research, especially that related to generative AI and large language models (LLM).

Nevertheless, the topic we have been supervising for the past 2 years has allowed us to closely monitor this rapid change, collecting contributions that have proposed and analyzed various topics related to AI in Education. Two recent contributions to the topic by Mallik and Gangopadhyay and Gentile et al. provide an overview of the trend.

Mallik and Gangopadhyay examine how AI, machine learning and deep learning methods are currently used to support the educational process. They conduct this examination by analyzing the involvement of AI-driven methods in the educational process considered as a whole. Based on the analysis of a large set of papers, the authors outline the main trends of future research concerning the use of AI in Education with particular reference to some paradigmatic shifts in the approaches analyzed.

Gentile et al. analyze one of the most exciting topics about AI and Education: the impact of AI on teachers' roles through a systematic literature review. Teachers have always been called upon to change their practices by attempting to integrate new technologies rather than rejecting them. However, even at first glance, the potential changes introduced by AI signal a radical change, what can be called a genuine paradigm shift in teachers' role in Education. According to the authors, the literature analysis reveals that full awareness of the urgency with which the challenges imposed by AI in Education must be addressed has yet to be achieved. Moreover, the study proposes a manifesto to guide the evolution of teachers' roles according to the paradigm shift proposed by Kuhn in the scientific field.

To be managed adequately and avoid causing discomfort in education systems, the assumed changes in the teacher's role should be accompanied by appropriate professional development programmes. In this regard, Sáiz-Manzanares et al. address the topic of designing teacher training programmes that combine the use of technology and instructional design to promote the development of Self-Regulated Learning and automatic feedback systems. Through a study involving 23 secondary school teachers in a training programme delivered with Moodle, the authors investigated the differences in the behavior of experienced and inexperienced teachers, the consistency of the behavior patterns extracted during the study, with the respective type of teacher being modeled, and the teachers' level of satisfaction with the training activity on digital didactics.

The development of assessment tools is one of the preferred areas of application of AI in Education, and, in this respect, AI-based learning analytics will play a key role.

Student-generated texts represent an essential but often unexplored source of information for gaining deeper insights into learners' cognition and ensuring better compliance with students' real needs. To this regard, Berding et al. present a new approach based on applying item response theory concepts to content analysis for the analysis of the textual data generated by the student. They present the results of three studies conducted to make textual information usable in the context of learning analytics. By producing a new content analysis measure, simulating a content analysis process and analyzing the performance of different AI approaches for interpreting textual data, they show that AI can reliably interpret textual information for learning purposes and also provide recommendations for an optimal configuration of AI.

Fleckenstein et al. present a systematic review to explore the effectiveness of AI-based Automated writing evaluation (AWE) tools in realizing systems capable of assessing students' writing skills and providing them with timely feedback with a view to formative assessment. The results confirm a medium-size effect and highlight how it is necessary to continue the exploration by identifying groups of interventions that are more homogeneous among themselves, trying to identify those factors that distinguish these interventions.

Cloude et al. propose an analysis and interpretation framework of real-time multimodal data to support students' Self Regulated Learning (SRL) processes. Specifically, their paper thematises the issues researchers and instructors face when using the data collected through innovative technologies. By recalling a specific procedure through which a researcher/instructor can standardize, process, analyze, recognize and conceptualize multimodal data, they discuss various implications for constructing valid and effective AI algorithms to foster students' SRL.

Cheng et al. address the topic of personalisation of learning using dynamic learning data to track the state of students' knowledge over time. Specifically, the authors propose a context-aware attentive knowledge query network model that can combine flexible neural network models with interpretable model components inspired by psychometric theory to analyze the exercise data.

Chichekian and Benteux propose an exploratory review to describe how the effectiveness of AI-based technologies is measured, the roles attributed to teachers and both theoretical and practical contributions. From the research conducted, it emerges, according to the authors, that the role of teachers is underestimated and that the optimisation of AI systems is still nested exclusively in a strictly IT perspective.

The conscious and informed use of AI and tools that make use of AI is a critical indicator of the maturity of the community that benefits from these instruments. On the contrary, conscious use allows all the potential that can be found in AI to be turned into concrete gains. In this regard, Zammit et al. emphasize the importance of the diffusion and understanding of AI and Machine Learning and the associated ethical implications. To this end, the authors exploit a digital game designed and developed to teach AI and ML core concepts and to promote critical thinking about their functionalities and shortcomings in everyday life.

The paper by Ninaus and Sailer also fits into the groove of critical and aware use of AI in Education. The authors explore humans' role in decision-making in designing and implementing artificial intelligence in Education. Considering the essential role of users in decision-making in educational contexts and emphasizing the need to balance human- and AI-driven decision-making and mutual monitoring, they address both cases in which some AI implementations might make decisions autonomously and cases in which students and teachers, having received information from an AI, are enabled to make reasoned decisions.

Much remains to be done to understand how AI is changing educational practices and how the key stakeholders in the educational community (i.e., students, teachers, faculty, and families) perceive this ongoing change. Nevertheless, the Research Topic provides a broad picture of ongoing changes and a starting point in a research path that will develop over the coming years involving many experts in AI and Education fields.

We believe it is important to renew this Research Topic so that the most recent findings can be shared and systematically analyzed in order to support the progress of this field.

Author contributions

MG: Writing—original draft, Writing—review & editing, Conceptualization, Validation. GC: Writing—original draft, Writing—review & editing, Validation. IM-S: Validation, Writing—review & editing. FD: Validation, Writing—review & editing. MA: Validation, Writing—review & editing.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Anderson, J. R., Boyle, C. F., and Reiser, B. J. (1985). Intelligent tutoring systems. Science 228, 456–462. doi: 10.1126/science.228.4698.456

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Bidarra, J., Simonsen, H. K., and Holmes, W. (2020). “Artificial Intelligence in Teaching (AIT): A road map for future developments,” in Empower EADTU, Webinar week: Artificial Intelligence in Online Education. doi: 10.13140/RG.2.2.25824.51207

Laird, J. E., Newell, A., and Rosenbloom, P. S. (1987). SOAR: an architecture for general intelligence. Artif. Intell . 33, 1–64. doi: 10.1016/0004-3702(87)90050-6

Newell, A. (1990). Unified Theories of Cognition . Cambridge, MA: Harvard University Press.

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Keywords: Artificial Intelligence and Education (AIED), education, generative AI, learning processes, intelligent tutor systems

Citation: Gentile M, Città G, Marfisi-Schottman I, Dignum F and Allegra M (2023) Editorial: Artificial intelligence for education. Front. Educ. 8:1276546. doi: 10.3389/feduc.2023.1276546

Received: 12 August 2023; Accepted: 25 October 2023; Published: 07 November 2023.

Reviewed by:

Copyright © 2023 Gentile, Città, Marfisi-Schottman, Dignum and Allegra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Giuseppe Città, giuseppe.citta@itd.cnr.it

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Impact of Artificial Intelligence in Education

Ai's potential benefits are immense, but there are also ethical considerations and concerns about data privacy.

Key points:

AI is a powerful catalyst for enhancing teaching effectiveness in many ways
AI augments teaching by offering real-time insights, and fostering PD
Discover more about why AI in education is essential for learning

Artificial intelligence is reshaping the landscape of education, ushering in a new era of innovation and transformation. AI technologies are reshaping traditional educational models, offering innovative tools that adapt to individual student needs, streamline administrative tasks, and provide valuable insights through data analytics. From intelligent tutoring systems to immersive virtual reality experiences, AI is transforming how knowledge is imparted and acquired. While the potential benefits are immense, there are also ethical considerations, concerns about data privacy, and challenges associated with equitable access.

This dynamic interplay between technological advancement and educational evolution underscores the significance of understanding and harnessing the impact of AI to create a more adaptive, inclusive, and effective learning environment.

How artificial intelligence in education influences teaching effectiveness

To analyze the benefits of artificial intelligence in education, we must acknowledge that AI is a powerful catalyst for enhancing teaching effectiveness in numerous ways. Firstly, AI enables personalized learning experiences by analyzing individual student data, allowing educators to tailor instruction to diverse learning styles and pace. This adaptability fosters a deeper understanding of subjects among students.

AI supports teachers in administrative tasks, such as grading and assessment, freeing up valuable time. Automated grading systems powered by AI streamline routine tasks, enabling educators to focus on interactive teaching methods, mentorship, and targeted interventions for struggling students.

Intelligent tutoring systems, driven by AI, provide real-time feedback and insights into student performance. This allows teachers to identify learning gaps promptly and address them proactively. AI also offers data-driven analytics, empowering educators with valuable insights into student progress and areas that require attention.

AI contributes to professional development by providing teachers with innovative tools and resources. It facilitates continuous learning and updates on best practices, ensuring educators stay informed about evolving educational methodologies.

In essence, AI augments teaching effectiveness by providing personalized support, automating routine tasks, offering real-time insights, and fostering ongoing professional development. As a collaborative partner, AI empowers educators to create dynamic and engaging learning environments, ultimately benefiting both teachers and students in the educational journey.

How will artificial intelligence impact the way we teach?

AI is poised to revolutionize the way we teach by introducing innovative approaches that enhance educational outcomes. One significant aspect of the impact of artificial intelligence on education is the personalization of learning experiences. AI algorithms analyze individual student data, allowing for tailored content delivery based on students’ unique needs and learning styles. This adaptability ensures a more engaging and effective learning environment.

AI facilitates a shift from a one-size-fits-all approach to personalized learning plans. Intelligent tutoring systems provide real-time feedback, identifying areas where students may struggle and offering targeted assistance. This not only addresses individual learning gaps but also promotes a self-paced and mastery-based approach to education.

Moreover, AI introduces data-driven insights into teaching practices. Educators can leverage analytics to assess student progress, identify effective teaching strategies, and make informed decisions to optimize learning outcomes.

As AI becomes more integrated into education, teachers will transition into roles that emphasize mentorship, creativity, and personalized guidance. The human touch in teaching, coupled with the capabilities of AI, will create a symbiotic relationship, ensuring that education remains a collaborative and enriching experience. Embracing these advancements, educators will become facilitators of personalized learning journeys, preparing students for success in an ever-evolving, technology-driven world.

Does AI benefit or hurt the field of education?

The pros and cons of AI in education are nuanced, with many factors influencing the educational landscape.

Positive aspects:

Personalized learning: AI enables personalized learning experiences, tailoring educational content to individual student needs and learning styles. This adaptability can enhance comprehension and engagement.
Efficiency and time saving: Automated grading systems powered by AI streamline administrative tasks, allowing educators to allocate more time to interactive teaching methods, mentorship, and targeted interventions for students.
Global accessibility: AI facilitates online education, providing access to quality learning resources and courses globally. This inclusivity is particularly beneficial for students in remote or underserved areas.

Negative aspects:

Bias and inequity: If AI algorithms are trained on biased data, they may perpetuate existing inequities in education. This raises concerns about fairness and equitable access to educational opportunities.
Loss of human connection: Critics argue that an overreliance on AI might lead to a diminished human element in education. The emotional and social aspects of learning, crucial for holistic development, may be compromised.
Privacy concerns: The collection and analysis of extensive student data raise privacy issues. Ensuring robust safeguards for the ethical and secure handling of sensitive information is crucial.

The impact of AI on education depends on how it is implemented and integrated. When used responsibly, AI has the potential to enhance personalized learning, streamline administrative tasks, and increase educational accessibility. However, addressing concerns related to bias, privacy, and the potential loss of human connection is essential for ensuring that AI contributes positively to the educational experience.

How AI is shaping the future of education

The impact of artificial intelligence in education is far-reaching, shaping the future of K-12 education by introducing transformative changes that enhance learning experiences, improve efficiency, and foster personalized education:

Personalized learning: AI-powered adaptive learning platforms analyze individual student data to customize educational content, catering to diverse learning styles and paces. This personalization ensures that students receive tailored instruction, promoting a deeper understanding of subjects.
Data-driven insights: AI provides educators with valuable data-driven insights into student performance and learning patterns. This information helps in making informed decisions, refining teaching strategies, and identifying areas that may require additional attention.
Global accessibility: AI facilitates online education, enabling students to access educational resources and courses from anywhere in the world. This inclusivity expands educational opportunities, especially for students in remote or underserved areas.
Preparation for future skills: AI-driven educational tools, including virtual tutors and gamified learning platforms, foster the development of critical thinking, problem-solving, and digital literacy skills, preparing students for the evolving demands of the future workforce.

AI is shaping the future of K-12 education by creating a more personalized, efficient, and globally accessible learning environment. As technology continues to advance, the thoughtful integration of AI holds the potential to optimize educational outcomes, equip students with essential skills, and prepare them for success in an increasingly digital and interconnected world.

How can AI disrupt education?

AI has the potential to disrupt education significantly, challenging traditional paradigms and reshaping the learning landscape. Let’s look at what might accompany the future of AI in education:

Personalized learning revolution: AI can tailor educational content to individual student needs, preferences, and learning styles, challenging the one-size-fits-all model. This disruption fosters a more personalized and adaptive learning environment, addressing diverse learning needs.
Shift in pedagogical approaches: AI-driven intelligent tutoring systems can challenge traditional pedagogical approaches. These systems offer real-time feedback and insights, influencing a move towards student-centric, data-driven teaching methodologies.
Global accessibility and inclusivity: AI facilitates online education, disrupting geographical barriers and expanding access to learning resources globally. This inclusivity challenges traditional notions of education delivery, making quality education accessible beyond traditional classrooms.
Emergence of new educational models: AI’s influence extends to the emergence of new educational models, such as virtual classrooms, adaptive learning platforms, and gamified learning experiences. These innovations disrupt traditional classroom structures and methodologies.
Evolving teacher roles: AI’s introduction may lead to a redefinition of the teacher’s role. Educators may transition from traditional lecturers to facilitators of personalized learning journeys, emphasizing mentorship, creativity, and emotional support.

While these disruptions offer immense potential for positive transformation, they also raise concerns about equity, privacy, and the ethical use of data. Managing these challenges responsibly is crucial to harness the full benefits of AI in education and ensure a positive and inclusive learning future.

How does AI help teachers?

AI serves as a valuable ally for educators, offering a range of tools and capabilities that enhance teaching effectiveness and streamline various aspects of the educational process. Here’s a sample of how AI for teachers can improve instructional approaches:

Personalized learning: AI analyzes individual student data to tailor educational content, addressing diverse learning styles. This personalized approach allows teachers to cater to the unique needs of each student, fostering a deeper understanding of subjects.
Real-time feedback and interventions: Intelligent tutoring systems powered by AI offer real-time feedback on student performance. Teachers can use this data to identify learning gaps promptly, allowing for timely interventions and targeted support.
Professional development: AI provides educators with continuous professional development opportunities. Access to innovative teaching resources, data-driven insights, and collaborative platforms empowers teachers to stay informed about evolving educational methodologies and refine their teaching practices.
Enhanced teaching strategies: AI-driven analytics offer insights into teaching strategies that are most effective for individual students or entire classrooms. This data-driven approach enables teachers to refine their methods, adapting to the evolving needs of their students.
Inclusive education: AI supports inclusive education by providing tools for early identification of learning challenges and offering targeted interventions. This proactive approach ensures that all students, including those with diverse learning needs, receive the support they require.

AI assists teachers by providing personalized learning experiences, automating administrative tasks, offering real-time feedback, facilitating professional development, enhancing teaching strategies, and promoting inclusivity in education. As a collaborative partner, AI contributes to a more dynamic and effective teaching environment, empowering educators to create impactful and personalized learning journeys for their students.

What are the disadvantages of artificial intelligence for children?

AI use in education for children presents potential disadvantages that warrant careful consideration. Among the negative effects of artificial intelligence in education is the risk of reinforcing biases inherent in training data, leading to discriminatory outcomes. Additionally, excessive reliance on AI could compromise the development of critical thinking and creativity by promoting a standardized approach to learning. Privacy issues emerge as AI systems collect and analyze extensive data, raising concerns about the security of children’s information.

Furthermore, the digital divide may exacerbate inequalities, as not all children have equal access to AI-driven educational tools. Striking a balance between the benefits and potential drawbacks of AI in education for children is essential to ensure responsible and equitable implementation.

What is the role of artificial intelligence in teaching and learning?

The role of AI in teaching and learning and of AI tools for education is transformative, reshaping traditional educational paradigms. In teaching, AI acts as a supportive tool, automating administrative tasks like grading, allowing educators to focus on interactive and personalized instruction. AI-driven tutoring systems offer tailored feedback and adapt to individual student needs, enhancing the learning experience. Moreover, AI facilitates the creation of dynamic and engaging educational content, catering to diverse learning styles.

In learning, AI provides personalized pathways, adapting to each student’s pace and preferences. Intelligent content delivery systems utilize data analytics to identify areas of strength and weakness, enabling a targeted approach to skill development. Virtual reality and simulations powered by AI offer immersive learning environments, making complex subjects more accessible and practical.

While AI streamlines educational processes, challenges include ethical concerns, potential biases in algorithms, and the need for responsible AI use. The evolving role of educators involves collaboration with AI tools, emphasizing the human touch in fostering critical thinking and creativity. Overall, AI in teaching and learning holds the promise of a more adaptive, personalized, and inclusive educational experience, preparing students for the complexities of the modern world.

Educators can embrace the transformative power of AI in education by taking collective action to shape a future-ready learning environment.

Educators, policymakers, parents, and stakeholders can unite in fostering responsible AI integration: Prioritize ongoing professional development for educators to harness AI’s potential. Advocate for equitable access to AI-driven resources, ensuring that all students benefit from this technological evolution. Industry leaders can invest in collaborative initiatives to develop innovative AI tools aligned with educational goals. Together, educators and stakeholders can unlock the full potential of AI, creating personalized, inclusive, and impactful learning experiences. A collaborative commitment will shape an education landscape where AI empowers learners, nurtures creativity, and prepares students for the challenges of an evolving world.

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Artificial Intelligence

California Bill Would Prevent AI Replacement of Community College Faculty

The new bill comes after concerns from several faculty members about AI’s classroom role.

By Lauren Coffey

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The California legislature approved a bill that would prevent AI bots from replacing community college faculty members.

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The California legislature voted unanimously for a bill to stop artificial intelligence (AI) bots from replacing community college faculty in the state.

The short, two-page bill passed on Friday and was sent to the desk of California governor Gavin Newsom, who can sign or veto the bill, or allow it to become law in September by taking no action. Newsom’s office declined to comment.

The bill states that the “instructor of record” for a community college course “shall be a person who meets the minimum qualifications to serve as a faculty member.” The process to meet those minimum qualifications is extensive, involving approval from the Academic Senate and Board of Governors, and would exclude AI bots from being instructors.

“AI is definitely encroaching upon the area of where I think a human should be involved in the learning,” said Wendy Brill-Wynkoop, president of the Faculty Association of California Community Colleges. She pointed toward some AI tools in California that are starting to replace counselors, while tools like those from Khan Academy are moving deeper into the tutoring space.

An association governance committee hatched the idea for the bill last September. While, at face value, the bill seems focused on the labor concern of keeping faculty, Brill-Wynkoop said she believes it is less of an AI-focused bill and more about mitigating the potential long-term effects on students.

“Our thought was that the tool is powerful but we have to be cautious; because it is brand new, we have no idea where this is going to go,” she said. “The thought of the bill was making sure students have the right to humans as a faculty member to help them through wherever this [AI path] ends up going.”

Other faculty members across the nation have cited concerns about AI technology potentially coming for their jobs. Boston University faculty expressed alarm in April after the university’s dean of arts and sciences, Stan Sclaroff, emailed faculty suggesting they use AI during a strike by graduate students to help manage course discussions, labs and student feedback.

The National Education Association is expected to release faculty union guidance next month for use as a bargaining framework in discussions about potential AI replacements.

But other higher education–facing organizations have no plans to pursue similar legislation.

Larry Galizio, president and CEO of the Community College League of California, said the bill “almost essentially reaffirms the status quo.”

“I haven’t heard that concern about being replaced, but what I’ve heard are concerns that we need to have those discussions, hear from those experts and discuss a multiplicity of issues,” he said, pointing toward privacy concerns. “The bigger concerns are how are we approaching this as educational professionals so our students, in our communities, are as well placed as they can be in this changing and changed environment.”

Similarly, Martha Parham at the American Association of Community Colleges, said she was unaware of similar legislation pushes from community colleges across the nation, although she said this topic is at the forefront of most educators’ minds.

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“I can say AI is something we’re hearing a lot about from many of our members; it’s definitely a top-of-mind subject for presidents and all administration, really,” she said, adding that the AACC’s next commission meeting will focus solely on AI and best ways to streamline processes for students. “I have not heard of anyone interested in replacing human beings with AI but certainly heard about how we can all benefit from the services it can provide to help students.”

Brill-Wynkoop agreed, saying the Faculty Association of California Community Colleges is not anti-AI. They just want to set limitations now before things evolve, especially in light of a tightened state budget that could have legislators turning toward cheaper teaching options.

“I don’t think there’s some evil being out there saying, ‘Let’s get rid of everyone,’ but when you have a budget that’s tightened, because of AI’s efficiency, it can be one of those tools [to help],” she said. “So we have to be thoughtful and careful in how and where we use it, to supplement education rather than a tool for eliminating positions.”

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The Use of Artificial Intelligence in English Learner Education

Disclaimer: The NCELA Blog is intended to share information that can be of use to educators, parents, learners, leaders, and other stakeholders in their efforts to ensure that every student, including ELs, is provided with the highest quality education and expanded opportunities to succeed. This blog post represents the view of the authors only and does not constitute or imply endorsement, recommendation, or favoring by NCELA, the Office of English Language Acquisition (OELA), or the U.S. Department of Education.

There is a lot of intrigue surrounding Artificial Intelligence (AI) in education. For educators, especially those working with English learners (ELs), leveraging AI has the potential of allowing them to enhance their instruction and better engage with multilingual families and caregivers. However, with AI's rapid evolution, understanding the potential benefits and challenges of AI for ELs is crucial to ensure that schools and districts adapt this technology appropriately. The Office of Educational Technology's (EdTech’s) publication AI and the Future of Teaching and Learning: Defining Artificial Intelligence outlines the evolving role of AI in society and addresses its risks and opportunities when used in K–12 schools.

In May 2024, an Impact Research survey found that 46% of K-12 teachers reported using ChatGPT at least weekly for work while 59% percent viewed AI chatbots favorably overall (Walton Family Foundation, 2024). ChatGPT and other AI chatbots are platforms that fall under the category of GenAI, a subset of AI that can recognize patterns in data to generate content.

As an educator, you may be contemplating how to integrate GenAI into your instruction to better support your ELs and multilingual students. GenAI can serve these students in various ways, such as through helping them learn new content via AI-powered research tools, through generating mentor texts, and through creating accessible materials—including materials in the ELs’ home languages. Teachers can use GenAI platforms to support with planning lessons, differentiation, creating assessments, and adapting content to the academic and linguistic needs of diverse students.

When incorporating technology into teaching or connecting with EL families, educators and support staff can begin with small-scale experimentation. This initial exploration can introduce AI tools into the classroom while providing time to get a sense of their strengths and weaknesses. With this knowledge, teachers can then gradually introduce these technologies into their lesson plans and communication strategies to ensure seamless integration (Najarro, 2023). AI and the Future of Teaching and Learning: Engaging Educators shares that “as schools and districts make decisions about AI systems, they need to share information and provide professional learning opportunities for educators, families, and communities” (EdTech, 2022).

However, a lingering question remains: What impact will the adoption of AI have on education as a whole, both positively and negatively? It is crucial to remain cognizant of the challenges that may arise with the introduction of new technologies and to implement internet safety measures when utilizing digital platforms. As an educator, being involved in every stage of the process—from design and development to evaluation and policymaking—can serve as an effective initial step in addressing concerns.

Sources:

Walton Family Foundation. (2024, June 11). The value of AI in today’s classrooms. https://www.waltonfamilyfoundation.org/learning/the-value-of-ai-in-todays-classrooms
Office of Educational Technology. (2022a, April 4). AI and the future of teaching and learning: Defining artificial intelligence. Medium . https://medium.com/ai-and-the-future-of-teaching-and-learning/ai-and-the-future-of-teaching-and-learning-defining-artificial-intelligence-f31d20628280
Office of Educational Technology. (2022b, April 22). AI and the future of teaching and learning: Engaging educators. Medium . https://medium.com/ai-and-the-future-of-teaching-and-learning/ai-and-the-future-of-teaching-and-learning-engaging-educators-141e90c5e29f
Najarro, I. (2023, October 6). What teachers should know before using AI with English learners . Education Week . https://www.edweek.org/teaching- learning/what-teachers-should-know-before-using-ai-with-english-learners/2023/10

June 24, 2024

Aba task force on law and artificial intelligence releases survey on ai and legal education.

CHICAGO, June 24, 2024 – The American Bar Association and the ABA Task Force on Law and Artificial Intelligence released the results of its AI and Legal Education Survey , a compilation of insights gathered from law school administrators and faculty regarding the integration of artificial intelligence into legal education.

The survey was completed by 29 law school deans or faculty members between late December 2023 and mid-February 2024 and found that law schools are increasingly incorporating AI into their curricula. More than half of the law schools that responded to the survey (55%) reported that they offer classes dedicated to teaching students about AI. An overwhelming majority (83%) reported the availability of curricular opportunities, including clinics, where students can learn how to use AI tools effectively.

The survey suggests that AI is already having a significant impact on legal education and is likely to result in additional changes in the years ahead. With a majority of responding law schools offering dedicated AI courses and providing opportunities for students to engage with AI tools, it is evident that legal education is evolving to meet the demands of a profession increasingly shaped by technological advancements.

Other findings:

A substantial percentage of institutions (69%) have adapted their academic integrity policies in response to generative AI.
The survey revealed differing views on applicants’ use of generative AI in the admissions process. While none of the respondents explicitly permit applicants to use generative AI, a majority of law schools (62%) have not yet decided how to approach the issue.
A substantial majority of responding law schools (85%) contemplate changes to their curricula in response to the increasing prevalence of AI tools.

The survey indicates a trend towards integrating AI literacy across various legal disciplines, from legal writing to clinical practice, suggesting a broader acknowledgment that familiarity with AI tools and concepts is becoming essential for future legal professionals. The proactive measures taken by many law schools to update academic integrity policies and consider curriculum changes demonstrate a commitment to preparing students for the challenges and opportunities presented by AI in the legal landscape.

The ABA Task Force on Law and Artificial Intelligence was formed in August 2023 to address the impact of AI on the legal profession and the practice of law, including the ethical implications; identify the potential risks of AI; and develop insights into using AI in a responsible and trustworthy manner.The task force concentrates on several distinct areas involving AI including legal education, access to justice, the courts, governance, risk management and challenges the technology may impose on the legal profession.

The ABA is the largest voluntary association of lawyers in the world. As the national voice of the legal profession, the ABA works to improve the administration of justice, promotes programs that assist lawyers and judges in their work, accredits law schools, provides continuing legal education, and works to build public understanding around the world of the importance of the rule of law. View our privacy statement online. Follow the latest ABA news at www.americanbar.org/news and on X (formerly Twitter) @ABANews .

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Nabeel Gillani, Rebecca Eynon, Catherine Chiabaut, and Kelsey Finkel, “ Unpacking the ‘Black Box’ of AI in Education ,” Educational Technology & Society 26, no. 1 (2023): 99–111.

Jürgen Rudolph, Samson Tan, and Shannon Tan, “ ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education? ” The Journal of Applied Learning and Teaching 6, no. 1 (January 24, 2023).

Emily M. Bender, Timnit Gebru, Angela McMillan-Major, and Shmargaret Shmitchell, “ On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 ,” FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (March 2021): 610–623.

Erik Brynjolfsson, “ The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence ,” Daedalus 151, no. 2 (2022): 272–87.

Kevin Scott, “ I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale ,” Daedalus 151, no. 2 (2022): 75–84.

Laura D. Tyson and John Zysman, “ Automation, AI & Work ,” Daedalus 151, no. 2 (2022): 256–71.

Todd C. Helmus, Artificial Intelligence, Deepfakes, and Disinformation: A Primer (RAND Corporation, 2022).

William Hasselberger, “ Can Machines Have Common Sense? ” The New Atlantis 65 (2021): 94–109.

Gwo-Jen Hwang and Nian-Shing Chen, “ Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions ,” Educational Technology & Society 26, no. 2 (2023).

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Lauren Goodlad and Samuel Baker, “ Now the Humanities Can Disrupt ‘AI’ ,” Public Books (February 20, 2023).

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