Research Personalized Learning Report Generation--An Example from a Course on Integration of Information Technology and Physics Curriculum

The rapid development of artificial intelligence technology represented by AIGC has pushed the generation of learning reports from traditional manual writing to automated generation. In order to efficiently, objectively diagnose the effective learning behaviors of students in the learning process and automatically generate learning situation reports, this paper starts from a multimodal perspective, collects data related to students’ learning behaviors by using smart classrooms and online learning platforms and carries out feature extraction and metrics, and builds datasets, and constructs a text generation model for learning situation diagnosis based on the Generative Adversarial Network to automatically generate diagnostic texts for learning behaviors. Finally, Freemaker templating is used to generate the learning diagnosis report. Empirical studies have shown that the automatic generation of learning situation report based on multimodal data can accurately reflect the students’ learning situation, make classroom teaching intelligent, whole process, and accurate, and provide the basis for teachers to make targeted and accurate policy, and improve the quality of teachers’ teaching.