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Experts tell House Education Committee AI can boost learning if teachers, data protections and equity are prioritized
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Summary
Researchers and teacher-educators told the House Education Committee that AI-backed "learning engineering" and classroom agents can improve outcomes and personalize instruction, but only with teacher training, strong data protections and explicit equity measures.
Carnegie Mellon University researcher Richard Scheines told the House Education Committee that combining learning science with AI — an approach he called "learning engineering" — has produced measurable gains and can help teachers identify which students need targeted help.
"We've been using AI in education for decades," Scheines said, citing cognitive tutors from the 1990s that produced large learning gains. He described dashboards and intelligent class designs that let teachers see who is struggling and tailor attention accordingly.
Dr. Ingo Vitska, a professor of mathematics education at the University of Siegen, described multi‑school projects in Germany that involved more than 40 schools, about 500 teachers and 30,000 students and stressed that classroom tools should be shaped by teachers. "AI is not neutral. It's an amplifier," he said, arguing that equity depends on universal access and guided use.
Temple University assistant dean Dr. Lori Bailey told lawmakers the technology is already in students' hands — photographing math problems to get step‑by‑step help, using translation tools and drafting essays with AI — and framed those behaviors as "acts of self‑directed learning." Bailey urged investment in faculty AI literacy and cross‑institutional, funded consortia so that well‑resourced programs do not monopolize effective training.
Panelists and members repeatedly returned to three practical constraints: reliable infrastructure, teacher preparation and data privacy. Several members asked about age appropriateness; presenters generally recommended caution for young children and emphasized embedding AI in social, collaborative learning rather than isolating students with more screen time.
National and policy witnesses urged cautious, evidence‑based adoption. Jonathan Butcher of the Heritage Foundation warned against embedding AI broadly before addressing risks to development, critical thinking and parental authority, and recommended prioritizing instruction about AI rather than teaching exclusively through AI. Molly Gold of the National Conference of State Legislatures said a handful of states have proposed teacher‑preparation legislation and urged evaluation and research built into any rollout.
Committee chairs said the hearing reinforced the need for "guide rails" at the state level — shared frameworks that would clarify permitted uses, privacy expectations and when tools should be classroom‑specific rather than broadly mandated. No formal statewide policy was adopted at the hearing; lawmakers said they would use testimony to inform future bills.
The committee is expected to translate these themes — teacher training, equity safeguards, infrastructure investment and clear privacy rules — into draft guidance and possible legislation in upcoming sessions.
