Study: Adaptive learning programs may soon read emotions
While adaptive learning programs have long been heralded for their ability to give students personalized learning experiences, they may soon be able to further their effectiveness by reading facial expressions and deducing students' emotional states as they learn.
Adaptive learning systems currently use technology to tailor instruction based upon which questions students are answering correctly and incorrectly, adjusting to meet each student's individual skill level.
The revolutionary technology is being used in classrooms throughout the United States as teachers look for ways to give students the individualized attention that they need to be successful and prepare for college and their careers.
Researchers at the Tilburg Center for Cognition and Communication set out to determine if intelligent tutoring systems could be further improved by reading students' non-verbal behavior and using that information to more closely mimic the abilities of teachers.
To test the theory, researchers asked adult participants in the study to view videos of 2nd and 5th graders attempting to solve solve math problems and then rate their perceived difficulty of the problems based upon the facial expressions of the students.
After the researchers were able to determine that facial expressions can, in fact, indicate the level of difficulty, they set out to prove that adaptive learning technologies could be adjusted to do the same, predicting whether the problem was easy or difficult for student within the first second of their response.
"This 'thin-slice analysis' could correctly predict the difficulty level in 71 percent of all cases," the study said. "When trained on sufficiently many recordings, Adaptive Tutoring Systems should be able to detect children's state and adapt the difficulty level of their learning materials accordingly."
This discovery may prove to have a substantial effect on the way education is approached in the future, and demonstrates how adaptive learning technologies can be used to assist teachers through blended learning practices.
"Identifying motivational or emotional issues through facial recognition is most helpful when it leads to a teacher being alerted to the situation and given the responsibility to put the student back on track," Eric Hororwitz, an education researcher, explained in EdSurge.
Although more research needs to be done in the area of facial recognition before the technology can take hold, what is clear is that adaptive learning technologies will likely continue to be integral to the way education is approached in America, particularly as more schools move towards a blended learning model of instruction.