AI for Personalized Learning Experiences

Over the past several years, education software has advanced greatly. Students receive tailored courses depending on their learning styles using such technologies. Next, this approach is applied to e-learning systems and a framework for designing and using a knowledge and learner adaptive system is presented. There are great potential to employ AI to give students with individualized learning experiences. This study expect tutoring methods to supplement and even replace expert human instruction for more topics by integrating adaptive material and intelligent tutoring technologies. Therefore, the purpose of adaptive content and intelligent tutoring systems research is to deliver high-quality tailored education to students globally and make it not only interesting for instructors but also useful for students in reaching their specific learning goals. In addition, this study recommend new avenues for fundamental AI research, notably in cognitive architectures and natural language processing, once the proposed systems are applied to new contracts and knowledge-driven peer review systems.