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Technological developments in the field of education have contributed to the current surge in popularity of online courses. Every day, there is an exponential increase in both the rate of development and the availability of learning information. The trend in education systems across the world is toward putting the student at the center of everything. Education systems throughout the world are shifting toward a model that is more tailored to each individual student. This allows current technology to adapt different qualities of humans. Finding an appropriate learning strategy for a course with a large body of material that may be quite a challenge. The recommendation of a learning route aids students in methodically completing their coursework and reaching their objectives. Smart robots and computers are now able to comprehend individual-specific demands, technology advancements like AI, Machine Learning, and Big Data have made this possible. This paper suggests an AI-based learning-teaching model (AI-L-TM) for recommending learning paths that centers on analyzing learning performance and acquiring new information. Educational analytics improves a plethora of English-language individualized learning experiences by evaluating supplied data to provide valuable learning results. Through the use of Internet of Things (IoT) devices, data mining methods, and classroom data gathering, this project seeks to enhance the English learning experiences of college and university students. Here, AI methods might be helpful for a number of reasons, such as creating a learning–teaching model that mimics human thinking and decision-making and reducing uncertainty to make the process more efficient. Using artificial intelligence techniques for adaptive educational systems within e-learning, this paper presents a range of topics related to the field. It discusses the pros and cons of these techniques, and how important they are for creating smarter and more adaptive environments for online learning.

What kind of people to train, how to train them and for whom to train are the fundamental issues and eternal themes of education. The rapid advancement of artificial intelligence (AI) technology in recent years, as exemplified by deep learning and knowledge graphs, has opened up new avenues for innovation in education and modifications to teaching strategies. One of the most crucial subjects in the world of education nowadays is how to employ intelligent technology to encourage students to study intelligently. In the age of AI, smart learning is the fundamental meaning of education. The construction of smart learning models is the key and foundation for implementing smart learning, and it is also a bottleneck issue in research in this field. For the problem that it is difficult to characterize the intrinsic mechanism of intelligent learning, we propose the E-GPPE-C model of intelligent learning by utilizing AI technology, which can explain the operation mechanism, elements and characteristics of intelligent learning. Learning environment, learning route, learning assessment, learner image, educational knowledge map, as well as learning community make up the model. The base layer, service layer, support layer, application layer and key layer are all included in the model at the same time. We suggested the implementation approach of E-GPPE-C model from four perspectives: learning path suggestion, learner picture construction, learning community construction, and educational knowledge graph construction. These methods are based on algorithms linked to AI. The findings of this study lay the groundwork for the development of smart learning and the use of AI in the field of education, and provide a reference for subsequent research on smart learning models.