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The education sector has long treated all students the same way. However, each student is unique and has different learning abilities. But what is artificial intelligence in education? Through computer vision, AI can help maximize students' academic output by providing a personalized learning experience based on their strengths and weaknesses, tailored to the student's personal pace. The main advantage of artificial intelligence in education is the ease and non-abstract nature of the assessment process compared to traditional classroom education. Teachers can observe whether a student is motivated or disinterested in class without interrupting their activities. Affective computing techniques, the availability of low-cost cameras, and their widespread use in electronic devices like cell phones, computers, and tablets allow educators to measure student engagement levels using computer vision. Thus, continuously monitoring a student's behavior in an analog way is not possible, so artificial intelligence using computer vision eliminates the need for a teacher to continuously monitor each student's behavior, which is highly beneficial. READ ALSO: • What is process optimization?
• What is computer vision?
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How can artificial intelligence contribute to education?
See how the use of artificial intelligence will help transform teaching as we know it:
Improvement of digital teaching methods
The world is becoming increasingly closer due to the propagation of the internet. People can easily search for any topic they might be interested in and find relevant information at their fingertips in seconds. Expanding on this, users can opt for any skill-oriented course or program from a variety of courses available online. People are not restricted when it comes to learning about something that interests them. Leveraging the demand for online learning, many massive open online course (MOOC) platforms are on the rise. Many reputable institutes now offer online certification courses in addition to standard university courses. These online training courses provide audio and video lectures for students, along with digital materials such as e-books for learning. These courses almost provide a near-real classroom experience for students. Students can learn from these courses according to their schedule and do not fear missing important lectures. Such courses are usually chosen by students who cannot commit full-time due to full-time employment or enrollment in a different course. Online learning offers an excellent opportunity for those students who want to learn an additional skill set. The only major disadvantage of these courses is that there is no direct real-time interaction and feedback between the teacher and the student. Low student engagement remains a significant concern faced by educators in online learning contexts. Research shows that students who opt for digital courses suffer from low levels of engagement and end up dropping out of the course without completing it. Completion rates for online courses or MOOCs are as low as 7%. This is a major concern for educators as well as students. Self-reporting of doubts and unclear study materials is poorly exercised by students in these courses. It is a tedious process and does not yield the desired results. The use of artificial intelligence in education can help overcome this problem. With computer vision, educators can analyze user behavior, eye movement, and posture to assess engagement levels. This helps educators study their students' behavior as to which sections were engaging and which left the student uninterested. Thus, they can provide engaging courses, which require consistent interaction to grab the user's attention. As new technologies allow us to record and collect data on everything from posture, eye movement, and even facial expression, self-reporting is no longer the only or even the best way to measure engagement.
What are the advantages of using artificial intelligence in education?
Just like in online courses, computer vision can be useful for tracking student engagement in traditional classrooms. Analyzing student postures and behaviors, along with eye tracking, can help monitor their level of interest and attention. By studying this data, teachers can analyze the behavior of each student individually and measure the peaks and valleys in their level of interest at any given moment. Educators can modify their teaching methods to capture the attention of as many students as possible and maximize their interest. This helps develop an open interaction between teachers and students. In other words, teachers can assess and understand students' reactions to their teaching methods and ask students to provide genuine feedback that can be compared with the data collected through computer vision.
Artificial intelligence in the classroom
Artificial intelligence through computer vision can also be useful for improving cooperation among students. Teachers can place students in groups where they feel most comfortable interacting and sharing their ideas and opinions. Introverted students can benefit significantly, as they may feel uncomfortable among large crowds and loud, extroverted people. Organizing students according to their personalities helps in student growth, as they are at their comfort level. Students can share their ideas and suggestions and discuss their doubts, if they have any, freely with other students who are close to their own personality and can easily interact with one another. Computer vision analysis helps to understand behavior and interaction during various group tasks, how students teach others, and how comfortable they feel with their peers. This optimizes student interaction when teachers group students according to their comfort levels. Computer vision can offer valuable insights into students' posture, facial orientation, or gesturing during team activities, recording all student interactions.
Concerns regarding the use of computer vision in education
The use of computer vision in education has been controversial and debatable. The ethics of placing students under continuous surveillance have long been debated. There is also the argument that the technology itself may not yet be ready for widespread implementation. Facial recognition tools currently used for computer vision are highly susceptible to errors and report higher error rates for women and people of color. Regarding online courses, there is the issue of user data privacy being used without consent. The amount of data and the length of time a website can monitor user movements is highly debatable. Facial recognition data being used for other illegal purposes and the possibility of it being sold or hacked by third parties are also major concerns. Therefore, strict security measures need to be adopted by institutions implementing computer vision technology to protect user data from misuse. Not all institutions can implement such strong security measures, as they require capital investment. The use of artificial intelligence in education is not without its limitations. However, these issues can be resolved with further improvements in technology. Edtech companies can leverage the benefits of computer vision to create an engaging and intuitive atmosphere in educational institutions. Artificial intelligence through computer vision can mutually benefit the parties involved, making learning more satisfying, productive, and most importantly, fun.
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
