Analysis of Automated Content Generation and Adaptive Teaching Pathways of AIGC in Informational Teaching of Preschool Education Majors

Abstract

Generative artificial intelligence, as the latest breakthrough in artificial intelligence, has attracted widespread attention in the field of education since its release. With the background of intelligent transformation of education, this study compiles and analyzes AIGC technology and its application in teaching preschool education majors, establishes a model of influencing factors on the effectiveness of AIGC application, and explores the adaptive teaching path of AIGC application in informatization teaching of preschool education majors. The core factor scores of the sample preschool education majors are all greater than 3.65, and the effectiveness of AIGC application is in the middle to upper level. Meanwhile, the positive contribution of teacher traits, teacher support, equipment use, learning motivation, learning attitude, self-efficacy, technical support, and learning atmosphere to the effectiveness of AIGC application was verified at the 5% level. The study proposes that AIGC technology be utilized to develop teachers' nurturing and students' creativity, to enhance the relevance of teaching evaluation and the utilization of resource recommendations, and to promote the high quality of teaching and learning in preschool education.