Determining Learning Techniques by Using Artificial Intelligence and Observing the Impacts of Differentiated Education Model

Abstract

It is fundamental for students to be aware of how they acquire knowledge from resources in the constantly evolving and changing world. The three most practical senses in learning environments are sight, hearing and touch. The VAK model categorizes these sensory methods of learning as Visual (V), Auditory (A) and Kinesthetic (K) learning styles. In the 21st century, it is inevitable to avoid the use of technology in education. Using ways and technical methods of technology in the classroom enables teachers and students to find the new conclusion of daily life problems. It helps in education to create a better educational syllabus, learning material, and future products and services. As a conclusion, we have focused on learning techniques by a specific software that we have written in collaboration with a computer programmer. By this software, the learning technique of each student will be analyzed by means of online tests to be performed. At the end of the day, the learning style of each student will be particularly understood.After the development of the software, which will last around 3 months, we will introduce the new system to the students. Having finalized the test period, we will measure the success rate of students in their lessons compared to traditional learning. In this article, the relation between the effects of differentiated education on academic achievement with the learning skills of students classified by artificial intelligence will be studied.