TeachLab Presents The Homework Machine

We keep saying that most ed tech is invited into schools, but generative AI crashed the party. But the truth in, some teachers have invited AI into schools. Some think it’s been great, and others see opportunities as well as challenges. We visit four classrooms where students and teachers are using AI in ways they say are innovative, fulfilling, and effective: a student in Oregon who worked with her teacher to expand the scope of her assignments with AI; a Southern California instructor using AI to bypass busywork and focus on the creative aspects of filmmaking; a teacher in Illinois deploying AI to provide targeted feedback; and, finally, a former engineer whose students use AI coding tools to make circuitboards…play Rick Astley? And we ask the question: What are the human teachers doing to create conditions in which AI can support learning? This episode was produced by Jesse Dukes. We had editing from Alexandra Salomon and Ruxandra Guidi. Reporting and research from Chris Bagg, and Andrew Parsons. Additional reporting from Andrew Meriwether, Holly McDede, Natasha Esteves, and Marnette Federis. Sound design and music supervision by Steven Jackson. Thanks to Jerry Shaw for digging up some of those Arduino Uno songs. The “Uptown Funk” was a simulation, created in our studios. Production help from Yebu Ji. Data analysis from Manee Ngozi Nnamani and Manasa Kudumu. Administrative support from Jessica Rondon. Special thanks to Josh Sheldon and Eric Klopfer. Original music for this series was created by Steven Jackson, Andrew Meriwether and Jesse Dukes, as part of the music project Cue Shop. Thanks to Will Grueb, Andy Wilds, and the MIT Music Department for letting us use the MIT Harpsichord.The research and reporting you heard in this episode was supported by the Spencer Foundation, the Kapor Foundation, the Jameel World Education Lab, the Social and Ethical Responsibility of Computing initiative at MIT, and the RAISE initiative, Responsible AI for Social Empowerment and Education also at MIT.We had support from Google’s Academic Research Awards program.

Education technology companies have been falling over themselves to provide AI powered tools for schools, and to convince schools to buy their product. The array of AI powered products is dizzying, and while some can likely be put to good use, it can be hard for school leaders to gauge which are worth adopting. One school system in Iowa, Winterset Community School District has gone all in on generative AI, piloting at least three AI powered products and encouraging faculty and students to experiment with AI. They kindly let us visit for a week, and we dive in to see what they’re excited about, and what has been challenging. This episode was produced by Andrew Meriwether and Jesse Dukes. We had editing from Ruxandra Guidi and Alexandra Salomon. Reporting and research for the Homework Machine from Natasha Esteves, Holly McDede, Andrew Parsons, Marnette Federis, and Chris Bagg. Sound design and music supervision by Steven Jackson. Production help from Yebu Ji. Data analysis from Manee Ngozi Nnamani and Manasa Kudumu. Special thanks to Josh Sheldon and Eric Klopfer. Administrative support from Jessica Rondon. Thanks to Chad Sussex and everybody at Winterset who spoke to Andrew Meriwether. We’re happy to share that AI Express: Leading the Future of Learning — written by Chad Sussex and Sandy Groom-Meeks, who guided the AI journey for Winterset — is now available. This book offers school leaders and educators a practical roadmap for safely and effectively implementing AI in schools. Find the book here: https://bit.ly/AIExpress_AmazonOriginal music for this series was created by Steven Jackson, Andrew Meriwether and Jesse Dukes, as part of the music project Cue Shop. Thanks to Will Grueb, Andy Wilds, and the MIT Music Department for letting us use the MIT Harpsichord. The research and reporting you heard in this episode was supported by the Spencer Foundation, the Kapor Foundation, the Jameel World Education Lab, the Social and Ethical Responsibility of Computing initiative at MIT, and the RAISE initiative, Responsible AI for Social Empowerment and Education also at MIT. We had support from Google’s Academic Research Awards program.

We’re halfway through “The Homework Machine” series, and as our production team works to finish the final episodes, we check in with Teaching Systems Lab director Justin Reich, who is returning to the classroom after a full year of sabbatical. Justin has been nervous, since some of the assignments he’s relied on in the past are not “AI-proof”. He tells us how he plans to adapt, We want to share A Guide to AI in Schools: Perspectives for the Perplexed the guidebook authored by TSL, based on the interviews we conducted for “The Homework Machine”. Justin is a fan of these protocols for evaluating student work:

We’re about halfway through The Homework Machine min-series, and we have more episodes coming. We're taking a break this week, which gives us the opportunity to share an episode of one of our favorite education podcasts with you.Mindshift from KQED features in depth interviews and reports from classroom about education and educators. We particularly enjoy this episode about a shift to teach contemporary poets, alongside the classics.Hanif Abduraqqib. Sarah Kay. Elizabeth Acevedo. Clint Smith. Do any of these names sound familiar? How about Amanda Gorman? All of these writers are part of America’s thriving contemporary poetry scene. But you won’t find them in many text books, because high school poetry units tend to focus on dead poets, like Robert Frost, Walt Whitman and Edgar Allen Poe. North Carolina teacher Melissa Smith is working to change that. For the last seven years, she’s been diversifying the canon in her classroom, and encouraging other teachers to do the same with the hashtag #teachlivingpoets. The shift has inspired teachers across the country to get creative with how they teach students things like tone, rhythm and structure in poetry. And it’s inspired students to connect with and see reflections of themselves in the poets they study.We have more episodes of the Homework Machine coming in a little over a week. In the meantime, please take our listener survey. (We'll enter you in a drawing to win a $25 gift card).https://forms.gle/KwPGTeVYZh2mo6gF7

Students today grapple with the allure of AI tools like ChatGPT for schoolwork, often blurring the lines of academic integrity. Amelia's struggle with a new English class leads her to rely on AI, impacting her relationship with her teacher. Meanwhile, high-achieving students face ethical dilemmas as they navigate the complexities of AI usage. As graduation approaches, the phenomenon of senioritis exacerbates cheating tendencies, highlighting the need for open dialogue about trust and support in education.

Teachers have all sorts of opinions about AI. Some are optimistic, some are pessimistic. But the most common topic that came up in our interviews was cheating.While students have always taken shortcuts to complete their work, ChatGPT and other generative AI have a historically unique power to quickly, convincingly and comprehensively do a students’ assignment. This is proving a powerful temptation to students.So how do teachers help their students make good decisions? Teachers know that schools have historically struggled to manage discipline fairly but they also recognize that letting students get away with cheating isn’t doing them a favor. Teachers share how they’re navigating the Scylla and Charybdis of school discipline in the AI age.Listen to a bleeped version of this episode (Coming soon!).Transcript coming soon!This episode was produced by Jesse Dukes with Yebu Ji.Editing: Alexandra Salomon and Ruxandra GuidiReporting and research from Natasha Esteves, Andrew Meriwether, Holly McDede, Andrew Parsons, Marnette Federis, and Chris Bagg.Sound design and music supervision by Steven Jackson.Production assistance from Nathan Ray.Data analysis from Manee Ngozi Nnamani and Manasa Kudumu.Special thanks to Josh Sheldon, Camila Lee, Liz Hutner, and Eric Klopfer.Administrative support from Jessica Rondon.Thanks to the teachers who spoke to us including Joe O'Hara, Alec Jensen, Schuyler Hunt, Anna Rose Pandey, Ray Salazar, and Jessica Petit-Frere. And thanks to all the teachers and students who partipated in our research.Thanks to Greer Murphy and Jessa Kirk, at UC Santa Cruz's Office of Academic Integrity. Check out Greer Murphy's co-authored survey of academic integrity policies.The research and reporting you heard in this episode was supported by the Spencer Foundation, the Kapor Foundation, the Jameel World Education Lab, the Social and Ethical Responsibility of Computing initiative at MIT, and the RAISE initiative, Responsible AI for Social Empowerment and Education also at MIT.We had support from Google’s Academic Research Awards program.The Homework Machine is a program of the MIT Teaching Systems Lab, Justin Reich, director.

ChatGPT is the most well known of the Large Language Models (LLMs) but what is an LLM? We go deep into how this remarkable new technology is built, and why their performance is inconsistent — or jagged — across similar tasks. We dive into the techniques AI engineers use to align these tools’ behavior with our values, and explain why they don’t always work, and sometimes we get hallucinations or biased output.  This episode was produced by Steven Jackson and Jesse DukesEditing:  Alexandra Salomon and Ruxandra Guidi  Reporting and research from Holly McDede, Natasha Esteves, Andrew Parsons, Andrew Meriwether, Marnette Federis, and Chris Bagg.Sound design and music supervision by Steven Jackson. Production assistance from Yebu Ji and Nathan Ray. Data analysis from Manee Ngozi Nnamani and Manasa Kudumu. Special thanks to Josh Sheldon, Camila Lee, Liz Hutner, and Eric Klopfer. Administrative support from Jessica Rondon. The research and reporting you heard in this episode was supported by the Spencer Foundation, the Kapor Foundation, the Jameel World Education Lab, the Social and Ethical Responsibility of Computing initiative at MIT, and the RAISE initiative, Responsible AI for Social Empowerment and Education also at MIT. We had support from Google’s  Academic Research Awards program. The Homework Machine is a program of the MIT Teaching Systems Lab, Justin Reich, director. 

Educators and students are grappling with the arrival of AI tools like ChatGPT in classrooms. High school teachers reflect on their changing environments and student writing qualities after a long hiatus. The mixed reactions to AI integration highlight both challenges and opportunities in academic integrity and student support. Personal anecdotes reveal schools navigating this new tech landscape, addressing resistance while recognizing the potential benefits for learning in a rapidly evolving educational sphere.

Generative AI is not like other education technologies, which schools often invite into the classroom. This one crashed the party. And then, it started re-arranging the furniture. We wanted to learn more, so in a little over a year, the Teaching Systems Lab has talked to over 90 teachers and 30 students about the impact of Generative AI. Some are excited about AI's potential to transform education for the better. Others are troubled by the temptations of a machine that can quickly and convincingly do many homework assignments. And some think AI is just a shiny object – a distraction from the much larger problems facing education.Over the next seven episodes, we'll try to answer the question: Is AI a game-changing tool, a threat to critical thinking, another ed tech fad? … or something else? Media requests can go to jpd009@mit.edu.  

School leaders, education researchers, and others often point to a study conducted by Stanford researchers that suggested the arrival of generative AI in K-12 school has not meaningfully increased the percentage of students who acknowledge some kind of academic dishonesty. Sometimes, school leaders or experts suggest it means there’s “nothing to see here” when it comes to tools like ChatGPT and worries about students bypassing learning. Researcher + Journalist Jesse Dukes joins Justin to dive into the specifics of that study, and compare it with anecdotes from interviews with students and teachers.  This episode was produced by Andrew Meriwether and Jesse Dukes. We had additional reporting from Holly McDede  and research help from Natasha Esteves and Manassa Kudumu. Thanks to the Spencer Foundation and the Social and Ethical Responsibilities of Computing Initiative at MIT for funding our ongoing  research into the arrival of generative AI in schools. And thanks to the Kapor Foundation for funding Jesse’s work in California with KALW public radio. Thanks to all of the teachers and administrators who have talked with us.  If you want to take our survey, or learn more about our research into Generative AI and K12 education, head over to tsl.mit.edu/ai and if you want to volunteer for the sister study, in California, visit Jesse’s Linktree.