Artificial intelligence technology empowers visualization and teaching of digital news communication

Abstract

The development of artificial intelligence and the rise of online education have accelerated the process of intelligent education, and knowledge tracking is one of the most basic and important tasks. The study introduces the knowledge tracking model into journalism and communication teaching to innovate journalism and communication teaching. A personalized, in-depth knowledge tracking model PKT integrating students’ differences is established, which fully considers the continuous change of students’ abilities in the process of learning and the variability among different individuals and uses the K-means clustering algorithm for dynamic grouping. Based on this model, a smart-adaptive journalism and communication auxiliary teaching system is designed to visualize and analyze students’ learning status of journalism and communication knowledge. The results of the model application show the effectiveness of explicit modeling of students’ abilities in the proposed PKT model, which can better ensure the rationality and interpretability of personalized news communication teaching. In addition, the mean values of students’ satisfaction with the three dimensions of the effectiveness of smart digital news communication teaching, the efficiency of remedial teaching, and satisfaction with the teaching effect are all above 4 points, which can realize the diversity of news communication teaching methods.