Biometrics technology in education is rapidly expanding, as schools around the world seek new ways to integrate technology into their classrooms. In fact, the global biometrics market in the education sector is projected to grow at a CAGR of 26% during the 2017-2021 forecast period.
Schools in China and the U.S. have already begun implementing facial recognition systems to track attentiveness and improve school security, and it is undeniable that this technology is a growing trend in education. However, facial recognition technology has applications that extend beyond the traditional classroom: It can also play a significant role in personalizing learning experiences in special education programs and virtual classrooms.
A growing concern in both lower and higher-level education is how to best engage students and individualize their learning, and this lack of personalization is especially prevalent in special education and virtual classrooms. Facial recognition technology offers an innovative solution to this problem.
Special education programs suffer from underfunding and are often overlooked in discussions about improving education, despite the fact that over 6.7 million U.S. students received special education services in the 2015-2016 school year. Facial recognition technology can lend a hand in improving the quality of special education programs by giving each student additional attention and by facilitating student-teacher interactions.
One of the main obstacles in teaching special education is difficulty in communication. Some special needs students have disabilities in verbal and nonverbal communication, but facial recognition can enable instructors to adapt content and teaching methods to meet individual needs. Through emotional analysis, these systems can determine when students are losing interest, when they need help, and when they are distracted.
This technology can also identify children who are affected by emotional disturbances, behavioral disorders, and other conditions that are barriers to education. It can then alert teachers of these issues so that they can respond appropriately. By improving streams of communication between special needs students and instructors, facial recognition technology can assist teachers in addressing students’ individual needs.
Similarly, facial recognition technology can collect data to help personalize virtual learning experiences. As education moves toward different classroom models based on online learning, it is essential to ensure that online education is just as fair and effective as traditional education.
Distance learning and the rise of Massive Open Online Classes creates issues of impersonality and accountability. Facial recognition technology can fill this gap; for instance, existing recognition systems are able to analyze student attentiveness during online lectures and generate quizzes based on content covered during moments of inattentiveness. Facial recognition technology can adapt to individual needs, adjusting the pace of learning and promoting effective study habits on a case-by-case basis.
Additionally, facial recognition systems can monitor online cheating by verifying students’ identities at multiple points throughout exams and by tracking eye movements to ensure they are not looking through other material. The implications of facial recognition technology in online exams are radical; this technology has the potential to completely replace costlier and less accessible in-person exams.
Ultimately, facial recognition technology could be a huge boon to education both inside and outside of traditional classrooms. By personalizing learning experiences and catering to students’ individual needs, facial recognition technology can help bridge the gap between what students need in order to learn best and how teachers can assist them in meeting these needs.
Note: We asked our summer interns to investigate the potential for FRT in education and present us with their findings and conclusions. Katerina Gan is a rising sophomore at the University of Chicago studying Economics. She is passionate about journalism and education policy and has experience teaching English to elementary school students in China. Her article about AI in special education programs and virtual classrooms is the second edition of our FRT in education series: Be sure to check out our first article about how FRT can maximize classroom performance.
