Research on the Transformation Limitations and Optimization Paths of AI-Assisted Teaching Plan Design for Preschool Normal Students

Jiaqi He; Ling Ma; Jianying He

doi:10.70088/1mkb9b31

Authors

Jiaqi He Normal College of Jishou University, Jishou, China Author
Ling Ma Normal College of Jishou University, Jishou, China; School of Education, Minzu University of China, Beijing, China Author
Jianying He Jishou No. 11 Kindergarten, Jishou, China Author

DOI:

https://doi.org/10.70088/1mkb9b31

Keywords:

digital-intelligent lesson plan design, preschool normal university students, general education, digital literacy

Abstract

Generative artificial intelligence has now become deeply embedded in educational pedagogy, exerting multifaceted facilitative effects on curriculum resources, instructional formats, and teacher development. This study takes AI-assisted lesson plan texts produced by preschool normal university students as its research basis and compares them with curriculum cases from frontline kindergarten teachers. It finds that AI-assisted lesson plan design for preschool normal university students plays an optimizing and facilitating role in textual structures such as activity objectives, activity preparation, and activity processes, yet lacks the embodied nature of the teaching field in terms of selecting local materials, designing individualized instruction, and exercising pedagogical tact. Accordingly, optimization pathways for human-machine collaborative lesson plan design for preschool normal university students are proposed, with the aim of cultivating new normal university talent possessing both professional competence and digital literacy.

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