Multiple independent RCTs show efficacy across several dimensions of teaching and learning
The positive impact of automated feedback for teachers has been validated not just in TeachFX’s internal data and analyses, but also in rigorous studies conducted by independent academic researchers.
Four large-scale randomized controlled trials (RCTs) from leading researchers at Harvard University, Stanford University and the University of Maryland found positive impacts on both teacher practice and student outcomes.
Read more about these studies here.
TeachFX helps develop great teachers
A soon-to-be-published study of teacher candidates at a leading educator prep program found that TeachFX users consistently score dramatically better on their teacher evaluations and report overwhelmingly positive experiences using the tool.
Grounded in decades of education research
TeachFX leads the field in turning classroom audio into actionable insights for educators
Three 2025 peer-reviewed papers authored by TeachFX’s Research & Machine Learning teams highlight our most recent breakthroughs:
Multimodal Diarization (AIED 2025): Our first-of-its-kind multimodal diarization system combines both audio and text to determine who’s talking in class with unprecedented accuracy.
Detecting Opportunities to Respond in Noisy Classroom Transcripts (AIED 2025): TeachFX’s fine-tuned models demonstrate high reliability in detecting high-leverage teaching practices in real-world noisy classroom conditions.
Joint Classification and Quote Extraction of Opportunities to Respond (SEGA 2025): Builds on prior work by introducing a new fine-tuned model that is jointly trained to classify the presence of Opportunities to Respond (OTRs) and extract associated teacher quotes.












