Intelligent Teaching: An Exploration of Teacher Self-Directed Learning Models Driven by Large Models to Improve Digital Literacy

This paper explores a new model of teacher self-directed learning, analyzing the advantages of large models in adult self-directed learning and discussing their feasibility in professional teacher development. Combining adult learning theories, particularly Zimmerman's self-regulated learning model, it analyzes the potential benefits of large models in teacher self-directed learning across three stages: forethought, performance, and self-reflection. These models can assist teachers in setting learning goals, providing personalized resources, and recommending learning strategies, guiding them through the learning process by answering questions and offering suggestions, and helping teachers evaluate learning outcomes, engage in self-reflection, and plan subsequent learning actions to enhance their digital literacy.