AI Resilience Report forEducation Teachers, Postsecondary

Right now, AI is mostly augmenting the work of postsecondary education teachers — meaning it helps them do their jobs better rather than replacing them. Teacher educators are actually some of the people teaching their students how to use AI well. At The College of Wooster, for example, professors are running a "Build-A-Bot" project where future teachers design AI chatbots that simulate real classroom decisions, and they've found that AI significantly reduces the time investment for lesson planning and curriculum development, while still emphasizing that the teacher is still the driver.

New platforms like BranchED use large language models so that simulation platforms are emerging as a modality for teacher training, using avatars and large language models to replicate student behavior and give teachers practice dealing with classroom situations. AI is also showing up in research tasks: a Nature news report ^[1] found that scientists who use chatbots to draft grant proposals win more NIH funding, though the proposals tend to look more similar to past work. The professional society AACTE recognized this shift ^[2] by giving its top Journal of Teacher Education article award to "Uncovering the Hidden Curriculum in Generative AI: A Reflective Technology Audit for Teacher Educators." Some tools push further into automation — Inside Higher Ed reported ^[3] that Arizona State University soft launched a web app earlier this month that allows anyone, for $5 per month, to create an apparently unlimited number of customized "learning modules" using artificial intelligence built from professor content, raising big questions about who owns teaching.

Adoption is happening fast in some areas and slowly in others. On the "fast" side, the tools are cheap, easy, and save real time — nearly 60 percent of teachers used AI in the past school year, according to a Gallup survey cited by the National Education Association ^[4]. Education professors feel pressure to model these tools because their students will need them on day one of teaching.

On the "slow" side, there are real ethical concerns: faculty at ASU described the course-builder as "Frankensteinian" because it remixes their work without clear consent, and Nature notes AI-assisted grant proposals can crowd out original ideas. Grading, mentoring student teachers in real classrooms, and building human relationships still need a person — those are exactly the high-touch tasks ONET flags as least automatable. The takeaway for you: if you're drawn to teaching teachers, the human skills (judgment, empathy, ethics, coaching) are getting more* valuable, not less.

Learning to use AI thoughtfully now is the smart move.