An Artificial Intelligence-based Intelligent Evaluation Method for Automatic Generation of Educational Content

With the continuous advancement of artificial intelligence technology, the automatic generation of educational content has become an important tool to improve teaching efficiency and achieve personalized learning. However, there are still problems in evaluating the quality of generated content: monotonous evaluation dimensions and lack of dynamic adaptability; In this paper, an intelligent assessment method based on AI is proposed. Firstly, a multi-dimensional evaluation framework covering knowledge accuracy, logic correctness, teaching objectives, fitness, and learner adaptability is designed. Then, by combining pre-trained language models and GAN technology, an efficient and accurate assessment model is constructed. A learner feedback mechanism was introduced to optimize dynamic adaptability; The experimental results show that the method proposed in this paper outperforms existing methods on both the public data set and the self-built data set, especially in knowledge accuracy and learner adaptation. The experimental results show that the method proposed in this paper outperforms existing methods on public and self-built data sets, especially in knowledge accuracy and learner adaptation, verifying its wide applicability in real-world situations, providing a good evaluation tool for automatically generating teaching materials, and laying a technical foundation for the deeper application of artificial intelligence in education fields.