With the rapid advancement of generative artificial intelligence, teachers and school leaders are seeking answers to complex questions about how to successfully integrate technology into lessons, while also ensuring that students actually learn what they are trying to teach.
Justin Reich, associate professor in MIT’s Comparative Media Studies/Writing program, hopes that a new guidebook published by the MIT Teaching Systems Lab can support K-12 teachers as they determine what AI policies or guidelines to craft.
“Throughout my career, I have tried to be a person who researches education and technology and translates the findings to people working in the field,” says Reich. “When difficult things come up I try to jump in and be helpful.”
“A Guide to AI in Schools: Perspectives for the Perplexed,” published this fall, was developed in collaboration with an expert advisory panel and other researchers. The project includes input from over 100 students and teachers from across the United States, who are sharing their experiences teaching and learning with new generative AI tools.
“We’re trying to advocate for an ethos of humility when we examine AI in schools,” says Reich. “We’re sharing some examples from teachers of how they are using AI in interesting ways, some of which may prove to be robust and some of which may prove to be flawed. And we won’t know for a long time which is which.”
Finding answers to AI and education questions
The guidebook strives to help K-12 teachers, students, school leaders, policy makers, and others collect and share information, experiences, and resources. The advent of AI has left schools struggling to respond to many challenges, such as how to ensure academic integrity and maintain data privacy.
Reich cautions that the guidebook is not meant to be prescriptive or definitive, but rather something that will help foster thought and discussion.
The guidebook’s author says, “Writing a guidebook on generic AI in schools in 2025 is like writing a guidebook on aviation in 1905.” “No one can say how to best manage AI in schools in 2025.”
Schools are also struggling to measure what student learning loss looks like in the age of AI. “What does bypassing productive thinking with AI look like in practice?”. Reich asks. “If we think that teachers provide content and context to support learning and students no longer do the exercises that provide content and context, that is a serious problem.”
Reach invites people directly affected by AI to help develop solutions to the challenges posed by its ubiquity. “It’s like watching conversations in teacher lounges and inviting students, parents, and others to participate about how teachers think about AI,” he says, “what they’re seeing in their classrooms, and what they’ve tried and how it went.”
In Reich’s view, the guidebook is ultimately a collection of hypotheses expressed in interviews with teachers: well-informed, preliminary guesses about the paths schools might follow in the coming years.
Creating Teacher Resources in Podcast
In addition to the guidebook, Teaching Systems Lab also recently produced “The Homework Machine,” a seven-part series from the TeachLab Podcast that explores how AI is reshaping K-12 education.
Reich co-produced the podcast with journalist Jesse Dukes. Each episode tackles a specific area, asking key questions about challenges related to issues like AI adoption, poetry as a tool for student engagement, learning loss post-Covid, pedagogy and book bans. Podcasts allow Reach to share timely information about education-related updates and collaborate with people interested in furthering the work.
“The academic publishing cycle is not capable of helping those grappling with near-term challenges like AI,” says Reich. “Peer review takes a long time, and the research produced is not always in a form that is helpful to teachers.” Schools and districts are grappling with AI in real time, bypassing time-tested quality control measures.
Podcasts can help reduce the time it takes to share, test, and evaluate AI-related solutions to new challenges, which can prove useful in creating training and resources.
“We hope the podcast will spark thought and discussion, giving people the opportunity to learn from the experiences of others,” says Reich.
The podcast was also produced into a one-hour radio special, which was broadcast by public radio stations across the country.
“We are wandering in the dark”
Reich is direct in his assessment of where we are in terms of understanding AI and its impacts on education. Recalling past efforts to quickly integrate new technology into classrooms, he says, “We’ve been fumbling around in the dark.” Reich suggests that these failures highlight the importance of patience and humility as AI research continues. “AI bypasses normal procurement processes in education; it just shows up on kids’ phones,” he said.
“We’ve been really wrong about technology in the past,” says Reich. For example, despite districts’ spending on devices like SmartBoards, research indicates there is no evidence that they improve learning or outcomes. In a new article for the article ConversationHe argues that early teacher guidance in areas such as web literacy has created bad advice that still exists in our educational system. He recalls, “We taught students and teachers not to trust Wikipedia and to search for website credibility markers, both of which turned out to be wrong.” Reach wants to avoid a similar rush to judgment on AI, recommending that we avoid speculating on AI-enabled instructional strategies.
These challenges, combined with potential and observed student impacts, significantly raise the stakes for schools and students’ families in the AI race. “Education technology always provokes anxiety from teachers,” Reich says, “but the prevalence of AI-related concerns is much higher than in other tech-related areas.”
Reich says the dawn of the AI era is different from the way we’ve previously received technology in our classrooms. AI was not adopted like other technologies. It just arrived. It is now upending educational models and, in some cases, complicating efforts to improve student outcomes.
Reich is quick to point out that there are no clear, definitive answers on effective AI implementation and use in classrooms; Those answers do not currently exist. Each resource Reach helped develop invited engagement from its target audience, gathering valuable responses that others might find useful.
“We can develop long-term solutions to schools’ AI challenges, but it will take time and work,” he says. “AI is not like learning to tie knots; we don’t yet know what AI is, or is going to be.”
Reach also recommends learning more about AI implementation from a variety of sources. “Decentralized parts of learning can help us test ideas, discover topics, and gather evidence on what works,” he says. “We need to know whether learning with AI is really better.”
While teachers do not get to make a choice regarding the existence of AI, Reach believes it is important that we solicit their input and engage students and other stakeholders to help develop solutions that improve learning and outcomes.
“Let’s run toward the answers that are right, not the first,” says Reich.
