A smart learning environment is equipped with personal digital devices, wireless communication, learning platforms, and sensors that associate to provide input into Artificial intelligence systems. Artificial intelligence makes decisions about regulating the physical aspects of the environment or learning systems. These requirements may be identified by analyzing learning performance, behaviors, and the real-world and online settings in which students are situated. There are several challenges in implementing smart learning environments that are highly cost-effective, connectivity issues (internet), impair the problem-solving capacity of students, technical challenges, e.g., malfunctioning of electronic gadgets. Hence, in this paper, Artificial Intelligence based Efficient Smart Learning Framework (AI-ESLF) has been proposed to overcome the challenges faced by a smart learning environment. This study aims to designate the current concept of the smart learning environment based on AI application and to examine the fundamental criteria of it and to demonstrate how tests can be performed in this smart learning environment by case studies. The experimental results show that the suggested system enhances the prediction ratio in terms of students learning behavior when compared to other existing approaches.
展开▼
