A university team is analyzing how data from voice and facial recognition technology could help instructors incorporate active learning.

A Carnegie Mellon University (CMU) assistant professor is using voice recognition technology that analyzes talk patterns to better inform instructors about what's happening in their classrooms.

The voice recognition technology used in the classrooms will help teachers gain insights about what students are learning and if they are collaborating and analyzing concepts, said Amy Ogan, assistant professor of human-computer interaction in CMU's School of Computer Science.

Right now, the technology is focused on the sounds that occur in a classroom....

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