Introduction
In recent years, artificial intelligence (AI) has revolutionized various fields, including education. The integration of AI in education has provided new opportunities to improve learning and teaching methods. AI-based education can offer numerous benefits, including personalized and customized learning, outside-the-classroom tutoring and support, virtual learning environments, chatbots and social networking sites, predictive analytics, facial recognition systems, and automated evaluation systems.
AI in Education Scenarios
One of the most significant benefits of AI in education is personalized and customized learning. With AI, it is possible to provide students with individualized feedback and study plans without the need for a human teacher. AI-powered Intelligent Tutoring Systems (ITSs) can offer one-on-one education to students and provide them with personalized study plans. Deep learning methods can also be used to create customized curriculums that cater to the specific needs of individual students. As AI technology advances, it may even be possible for robots to scan a student’s expression when they are struggling with a subject and adjust the teaching accordingly (Yogendra,2022).
Another advantage of AI in education is outside-the-classroom tutoring and support. AI-powered systems can offer students access to study materials and support outside of traditional classroom settings. For example, chatbots can be deployed to assist students with financial aid, registration, and other administrative tasks. AI advisors for learners and intelligent content generation can also provide additional support for students outside of the classroom (Prakash, 2022).
Virtual learning environments are also made possible by AI. With virtual classroom software, instructors can engage with students in a remote setting and provide them with interactive learning experiences. Virtual classrooms offer features such as screen-sharing and virtual whiteboard features, polls and quizzes, and breakout rooms, allowing teachers to engage with students in a variety of ways(Yogendra,2022).
Predictive analytics and facial recognition systems are also being utilized in AI-based education. Facial recognition software can be used to monitor student behavior and engagement during the learning experience, allowing teachers to take action to engage students and create student-centric practices. Predictive analytics can also be used to identify students at risk of failure or inability to complete a program, providing them with the help they need (Gampala,2020).
Finally, automated evaluation systems are another promising use of AI in education. Automated assessment systems can grade students’ essays, tests, and assignments, as well as teacher-assigned duties. These systems can help teachers reduce their burden and increase their productivity by providing course assistance and management tools. Automated scoring engines have been embedded into the learning platforms of largest free online course providers, like EdX, Coursera, to score writings of hundreds of students. This technology can also offer feedback and suggestions on how to enhance and edit student writing (Ganesh,2022).
Conclusion
In conclusion, AI-based education has the potential to revolutionize the way teachers educate students. AI can provide personalized and customized learning, outside-the-classroom tutoring and support, virtual learning environments, chatbots and social networking sites, predictive analytics, facial recognition systems, and automated evaluation systems. Although there are some issues with the use of AI in education, including delivery cost, ethics, transparency, privacy, and security, the benefits of AI in education are immense. The integration of AI in education can provide students with a more personalized and engaging learning experience, improving their educational outcomes and preparing them for success in the future.
References
Yogendra Prasad ,” Implementation of Machine Learning Based Google Teachable Machine in Early Childhood Education”, International Journal of Early Childhood Special Education, Vol 14, Issue 03,PP 4132-4138,2022. 19.
Ganesh, D., Kumar, M.S., Reddy, M.P.V., Kavitha, S. and Murthy, D.S., Implementation of AI Pop Bots and its allied Applications for Designing Efficient Curriculum in Early Childhood Education. International Journal of Early Childhood, 14(03), p.2022. 20.
Gampala V, Kumar MS, Sushama C, Raj EF. Deep learning based image processing approaches for image deblurring. Materials Today: Proceedings. 2020 Dec 26.
Prakash, Mr S. Shiva, ManasaBandlamudi, and Ragitha Radhakrishnan. “Educating and communicating with deaf learner’s using CNN based Sign Language Prediction System.”Vol 14, Issue 02,PP: 2624-2629, 2022. 21.
