With the rapid advancement of generative artificial intelligence, teachers and college leaders are searching for answers to complicated questions on successfully integrating technology into the classroom while ensuring that students are literally learning what they need to teach.
Justin Reich, associate professor at MIT Comparative media studies/writing program, hopes for a brand new guide to be published by the MIT Teaching Systems Lab can assist K-12 educators determine which AI policies or guidelines to develop.
“Throughout my profession, I actually have tried to be someone who researches education and technology and translates findings for people working on this field,” says Reich. “If there are tricky things, I attempt to step in and be helpful.”
“A Guide to AI in Schools: Perspectives for the Perplexed“, released this fall, was developed with the support of an authority advisory board and other researchers. The project includes contributions from greater than 100 students and teachers from across the United States who share their experiences teaching and learning with latest generative AI tools.
“We attempt to advocate for an ethos of humility after we study AI in schools,” says Reich. “We're sharing some examples from educators about how they're using AI in interesting ways, a few of which can prove robust and others flawed. And we won't know which is which for a very long time.”
Find answers to questions on AI and education
The guide is meant to assist K-12 educators, students, school leaders, policymakers, and others gather and share information, experiences, and resources. The introduction of AI has left schools grappling with quite a few challenges, corresponding to ensure academic integrity and maintain data privacy.
Reich points out that the guide is just not intended to be prescriptive or definitive, but quite something to stimulate thought and discussion.
“Writing a guide about generative AI in schools in 2025 is a bit like writing a guide about aviation in 1905,” the guide’s authors note. “No one in 2025 can say how best to administer AI in schools.”
Schools also struggle to measure the impact of student learning loss within the age of AI. “What does AI bypassing productive pondering appear to be in practice?” Reich asks. “If we consider that teachers are providing content and context to support learning and students are not any longer doing the exercises that contain the content and supply the context, that could be a major problem.”
Reich invites people directly affected by AI to assist develop solutions to the challenges posed by its ubiquity. “It's like watching a conversation within the staff room and welcoming students, parents and other people to take part in how teachers take into consideration AI,” he says, “what they see of their classrooms, what they've tried and the way it went.”
Reich says the guide is ultimately a group of hypotheses expressed in interviews with teachers: educated, initial guesses in regards to the paths schools might absorb the approaching years.
Creating resources for educators in a podcast
In addition to the guide, the Teaching Systems Lab also recently published “The homework machine“,” a seven-part series from the Teachlab podcast exploring how AI is transforming K-12 education.
Reich produced the podcast in collaboration with journalist Jesse Dukes. Each episode looks at a particular area and asks essential questions on challenges related to topics corresponding to the adoption of AI, poetry as a tool for student engagement, post-Covid learning loss, pedagogy and book bans. The podcast allows Reich to share timely details about education-related updates and to collaborate with those curious about advancing the work.
“The scientific publication cycle is just not suitable for helping individuals with short-term challenges like those of AI,” says Reich. “Peer reviews take an extended time and the outcomes of the research usually are not all the time in a form that is useful to educators.” Schools and districts are engaging with AI in real time, bypassing proven quality control measures.
The podcast can assist reduce the time spent sharing, testing, and evaluating AI-related solutions to latest challenges, which could prove useful in creating training and resources.
“We hope the podcast stimulates thought and discussion and allows people to attract from the experiences of others,” says Reich.
The podcast was also made right into a one-hour radio special that was broadcast on public radio stations across the country.
“We’re groping at the hours of darkness”
Reich directly assesses where we stand in understanding AI and its impact on education. “We’re at the hours of darkness,” he says, recalling previous attempts to quickly integrate latest technologies into classrooms. These failures, Reich says, underscore the importance of patience and humility as AI research moves forward. “AI bypassed the conventional procurement processes in education; it just showed up on kids’ phones,” he notes.
“We’ve been really improper about technology prior to now,” Reich says. Despite districts spending on tools corresponding to smart boards, research suggests there isn’t any evidence that they improve learning or outcomes. In a brand new article for Article for He argues that early teacher advice in areas corresponding to web literacy led to bad advice that also exists in our education system. “We taught students and teachers to not trust Wikipedia,” he recalls, “and to search for site credibility, each of which turned out to be false.” Reich desires to avoid an identical rush to evaluate AI and recommends not making assumptions about AI-powered teaching strategies.
These challenges, coupled with potential and observed impacts on students, significantly raise the stakes for schools and student families within the AI competition. “Educational technology all the time raises fears amongst teachers,” Reich notes, “however the range of AI-related concerns is far broader than in other technology-related areas.”
The dawn of the AI era is different from the best way we have now previously brought technology into our classrooms, says Reich. AI has not been adopted like other technologies. It just arrived. It is now upending educational models and, in some cases, complicating efforts to enhance student outcomes.
Reich is quick to indicate that there are not any clear, definitive answers on effective AI implementation and use within the classroom; These answers don’t currently exist. Each of the resources Reich has contributed to driving engagement among the many audiences they aim has garnered beneficial answers that others may find useful.
“We can develop long-term solutions to varsities’ AI challenges, but it would take time and work,” he says. “AI is just not like learning to tie knots; we don't yet know what AI is or can be.”
Reich also recommends learning more about AI implementation from various sources. “Decentralized learning units can assist us test ideas, seek for themes and gather evidence of what works,” he says. “We must know whether learning with AI is definitely higher.”
While teachers cannot resolve the existence of AI, Reich believes it is vital that we seek their input and interact students and other stakeholders to assist develop solutions that improve learning and outcomes.
“Let’s run for answers which are right, not first,” Reich says.
