Research on the Construction of Adaptive Learning System Based on Knowledge Graph in the Context of Artificial Intelligence

With the rapid development of emerging technologies such as artificial intelligence, big data and blockchain, digital and intelligent reform of higher education has attracted much attention. At present, artificial intelligence technology is in the development period of transformation from “perceptual intelligence” to “cognitive intelligence”, and knowledge graph, as the core driving force to realize “cognitive intelligence”, can study the acquired knowledge or data to realize the understanding, reasoning or explanation of human thinking. Although the current adaptive learning system can provide personalized learning resources, students may encounter problems such as understanding problems and lack of immediate feedback in the process of autonomous learning. How to improve the interactivity and tutoring ability of adaptive learning system to better meet students' personalized learning needs has become an urgent problem to be solved. In order to solve this problem, this study proposes to use knowledge graph and other artificial intelligence technologies to enhance the function of adaptive learning system. By integrating intelligent question-answering and intelligent teaching modules, the system will be able to simulate the role of teachers and provide timely feedback and guidance, thus improving the learning experience and efficiency of students.