Integrating computer vision in education can enhance students' learning experience.

Over the decades, the education sector has made incredible strides using smart technologies to deliver an enhanced learning experience to students. The evolution of new age, education technologies, from smart classes to digital learning, has further transformed the industry. As each student has a unique way of understanding things, the use of technology helps them to learn in an effective way. Already, digital classrooms are giving students an enhanced way of a learning experience, but research shows students opting for digital courses have low levels of engagement and eventually give up the course without completion. In this way, using Computer Vision can give a boost in enhancing students' learning patterns and provide educators the ability to understand students learning behavior.

The technology can also help teachers to take requisite measures to improve students' interest levels by enabling them to identify disengaged students in the class. Leveraging computer vision in education can assist in surging students' academic output by delivering a customized learning experience based on their strengths and weaknesses. With its effective computing techniques, availability of cameras at a lower cost, and pervasive use in electronic devices like computers, tablets and others, allow teachers to assess learners' engagement levels.

Unlike in a physical classroom where teachers can easily identify when a student is bored, stressed, or distracted, in the digital classroom or online learning it is impossible to keep monitoring every individual student. The use of computer vision here can reduce the need for a teacher to relentlessly monitor each and every student's behavior, which is a very complex task. It can also be used to analyze students' body posture, eye movement, and behavior in order to improve learning experience. By making use of computer vision tools, teachers will be able to conduct online examinations. Using such tools like a webcam can help recognize students.

Computer vision in education can also assist in creating an open interaction between teachers and students, where teachers can easily scale and understand each student's reaction. This can help reinforce teaching methods by asking students to provide feedback that can be then compared with the data gathered using computer vision.

As distance learning or online classrooms require good quality of both image and streaming video, recent advances in computer vision and algorithms have made potential considerable improvements for these with accuracy. In the last few years, there is an increasing number of products and companies specialized in emotion detection, facial analysis, and identity recognition, among others, has evolved significantly. Many researches show facial recognition is the most promising technology in engagement detection in an online learning environment. Emotuit, a California-based e-learning analytics startup, for instance, use facial recognition as analytics to improve student e-learning engagement.

Moreover, apart from advancing both teaching and learning practices, computer vision in education helps improving cooperation between students. This gives growth in students' comfort level so that they can learn things in an interesting and exciting way.