How Computer Vision Hypothetically Empowers Individual Students?
The education sector has not treated every student with individual care and attention in the midst to complete syllabuses and portions of the curriculum. Students are unique and do not share any common learning capability with each other. By using computer vision, scientists envision to improve the academic output of a student by accommodating a customized learning experience based on their weakness and strengths. Computer vision engages in an ease and non-obstructive assessment process which is not present in a conventional classroom set up.
Mentors or educators cannot watch or concentrate on every student at the same time, to read whether the student is interested or not. Therefore, the
deployment of a set of machines such as low-cost cameras, cell phones, computer etc. help educators to continuously keep a track over all the students’ performances and identify the inattentive student without interrupting their activities. With the help of computer vision technology, every student can be monitored easily. Computer vision technology can be deployed through various measures. One of the primary ways will be stimulating over the digital technology methods that could cater useful and syllabus oriented information to the pupil’s fingertips within seconds. The MOOCs capitalizes the demand over online learning that deliver an audio visual learning experience for the user. The utilization of computer vision in MOOCs can empower it from certain drawbacks it possesses. It can analyze user behaviour and eye movement to assess the engagement level of the student. Hence, educators can evaluate on what portions the student need special attention and care. Another interesting method is by enhancing the already existing teaching criteria. Educators can make use of the data generated by computer vision after analyzing individual student in the classroom. They can understand the reaction of the student using the teaching methods they proceed with. The genuine feedback given by the students can be used to compare with the data generated by computer vision. This alerts teachers with a heads-up to improve their teaching method and provide customized courses as well as materials for learning.
But there are concerns pertaining to the degree of the use of computer vision inside a classroom. The ethics in accordance with keeping students under surveillance at every time is controversial and debatable. Even though use of computer vision inside classroom has its own drawbacks, improvements in the technology can resolve such issues. Enterprises that are in the domain of edtech can leverage on its basic ways to gain fruitful results from computer vision technology.