NYC's AI ban through grade 8 sets stage for rest of US, experts say Share NYC's AI ban through grade 8 sets stage for rest of US, experts say on social media New York City's ban on use of artificial intelligence in the classroom for elementary and middle school students in the city's public school system - the largest in the country - could set the stage for how other school systems in the United States tailor their approach to the use of AI, experts say. The moratorium, which was announced on Wednesday, will last for one year and will end the use of 40 different educational tools impacting 600,000 students. The ban will not bar teachers from using the technology to create lesson plans. They need to develop skills alongside their peers, build relationships with educators and wrestle with tough problems on their own," Mayor Zohran Mamdani said in a news conference on Wednesday. "The tech industry wants us to believe that AI-powered early education is not only inevitable, but necessary.

Kids "need to wrestle with tough problems on their own," New York's mayor said Wednesday. Mayor Zohran Mamdani holds a press conference to announce a one-year moratorium on student AI usage in NYC public schools. Get your news from a source that's not owned and controlled by oligarchs. New York City Mayor Zohran Mamdani announced a one-year moratorium on AI use for elementary and middle school students on Wednesday. The decision, which comes a week before New York City public schools begin the year, "includes all software that uses student-facing generative AI." Elementary and middle school students--about 600,000 students in total--will Companion chatbots will also be prohibited for all grade levels. The city is also introducing biannual AI critical thinking training for high schoolers that cover determining what is and is not AI, impacts on careers and future skills, and AI-related biases, among others, along with limited pilot programs for a few classes per high school that incorporate AI tools into students' learning "under the direct supervision of a trained educator."

New York City mayor Zohran Mamdani just announced a one-year ban of generative AI tools in public schools for students up to eighth grade. The legislation takes effect during the 2026-2027 school year and will impact around 600,000 students. "This moratorium is a commitment to getting the future right," Mayor Mamdani said. "We will embrace new technology, but only when it serves our students." New York Governor Kathy Hochul added that the state "has been leading the way in our efforts to keep kids focused on learning and growing -- not clicking and scrolling."

Teachers and parents have warned against AI use in schools over concerns of'cognitive surrender' New York City will ban students' use of artificial intelligence in public schools through eighth grade, typically age 13 or 14. The prohibition is scheduled to be announced on Wednesday and will go into effect next week. The change is part of a sweeping overhaul of the use of technology in the US's largest school district, which enrolls roughly 900,000 students a year. In another policy shift, classrooms will keep students off laptops or tablets through the third grade, age nine or 10. The city's public school technology policies are closely watched by the rest of the United States.

UC Berkeley professor admits to using AI to edit op-ed on students' math skills Zvezdelina Stankova says she used AI to'help edit' an article about some of her students being'five to eight years' behind A math professor at the University of California, Berkeley, criticizing a "severe" math deficiency among students in an op-ed for the San Francisco Standard, admitted to using artificial intelligence to help edit the piece. The Standard published a 2,000-word piece by Zvezdelina Stankova last week, in which the professor said some of her math students were "five to eight years" behind and lacked a "middle school" education on fractions and basic algebra. Stankova said the UC system's test-blind admissions were to blame, suggesting that students who weren't sufficiently prepared for the rigor of Berkeley's mathematics program were admitted because a longstanding benchmark like the SAT had disappeared. Over the weekend, journalists at Berkeley's student newspaper, the Daily Californian, noticed the op-ed's language sounded like AI . According to Berkeley sophomore Francis Luo, they ran it through AI-detection software Pangram, which claimed 33% of the op-ed had been generated or assisted by AI.

'There is this overwhelming sense that ed tech companies are deciding what kids learn, and teachers are just being put into this position of tech support instead of driving the decisions about what is best for kids in terms of learning.' 'There is this overwhelming sense that ed tech companies are deciding what kids learn, and teachers are just being put into this position of tech support instead of driving the decisions about what is best for kids in terms of learning.' In October, Kelly Clancy's son received an assignment in sixth grade at a middle school in Brooklyn, New York, to create a science experiment and then ask Google Gemini, an artificial intelligence chatbot, for feedback, she said. Clancy, who has three children in New York City public schools, told the teacher that the bot "is something that just teaches kids that they can have machines do the thinking for them", instead of suggesting: "Let's talk to your partners. What about the science experiment could you improve?" Clancy also founded Parents for AI Caution in Educational Spaces, a group pushing the city to institute a two-year moratorium on using AI in its public schools.

'You can't replace human connection, human judgment,' warns Sarah Caliboso-Soto, a licensed clinical social worker. 'You can't replace human connection, human judgment,' warns Sarah Caliboso-Soto, a licensed clinical social worker. Schools are using AI counselors to track students' mental health. As hundreds of schools implement an automated monitoring tool, educators say that students can find talking to a chatbot'more natural' than confiding in a human The alert came around 7pm. Brittani Phillips checked her phone. A middle school counselor in Putnam county, Florida, Phillips receives messages from an artificial intelligence-enabled therapy platform that students use during nonschool hours.

Things to Do in L.A. Tap to enable a layout that focuses on the article. Homework faces an existential crisis. Has AI made it pointless? Students wait for a celebration of high test scores to begin at La Tijera Academy of Excellence in Inglewood on Wednesday. This is read by an automated voice.

Recent advances in multimodal large language models (MLLMs) raise the question of their potential for grading, analyzing, and offering feedback on handwritten student classwork. This capability would be particularly beneficial in elementary and middle-school mathematics education, where most work remains handwritten, because seeing students' full working of a problem provides valuable insights into their learning processes, but is extremely time-consuming to grade. We present two experiments investigating MLLM performance on handwritten student mathematics classwork. Experiment A examines 288 handwritten responses from Ghanaian middle school students solving arithmetic problems with objective answers. In this context, models achieved near-human accuracy (95%, k = 0.90) but exhibited occasional errors that human educators would be unlikely to make. Experiment B evaluates 150 mathematical illustrations from American elementary students, where the drawings are the answer to the question. These tasks lack single objective answers and require sophisticated visual interpretation as well as pedagogical judgment in order to analyze and evaluate them. We attempted to separate MLLMs' visual capabilities from their pedagogical abilities by first asking them to grade the student illustrations directly, and then by augmenting the image with a detailed human description of the illustration. We found that when the models had to analyze the student illustrations directly, they struggled, achieving only k = 0.20 with ground truth scores, but when given human descriptions, their agreement levels improved dramatically to k = 0.47, which was in line with human-to-human agreement levels. This gap suggests MLLMs can "see" and interpret arithmetic work relatively well, but still struggle to "see" student mathematical illustrations.

As personalized learning gains increasing attention in mathematics education, there is a growing demand for intelligent systems that can assess complex student responses and provide individualized feedback in real time. In this study, we present a personalized auto-grading and feedback system for constructive geometry tasks, developed using large language models (LLMs) and deployed on the Algeomath platform, a Korean online tool designed for interactive geometric constructions. The proposed system evaluates student-submitted geometric constructions by analyzing their procedural accuracy and conceptual understanding. It employs a prompt-based grading mechanism using GPT-4, where student answers and model solutions are compared through a few-shot learning approach. Feedback is generated based on teacher-authored examples built from anticipated student responses, and it dynamically adapts to the student's problem-solving history, allowing up to four iterative attempts per question. The system was piloted with 79 middle-school students, where LLM-generated grades and feedback were benchmarked against teacher judgments. Grading closely aligned with teachers, and feedback helped many students revise errors and complete multi-step geometry tasks. While short-term corrections were frequent, longer-term transfer effects were less clear. Overall, the study highlights the potential of LLMs to support scalable, teacher-aligned formative assessment in mathematics, while pointing to improvements needed in terminology handling and feedback design.