In view of the management problems of early childhood education major in universities in the era of artificial intelligence, as well as the mismatch between the artificial intelligence internship platform and the actual demand, this study combined with literature research and design of the evaluation indicators of intelligent enabling early childhood education internship software, including 3 first-level indicators, 5 second-level indicators and 12 third-level indicators. The weights of each index are determined by Delphi method and analytic hierarchy process. After the consistency test is passed, the weight of indicators at each level is determined scientifically. This paper provides a certain reference basis for finding a suitable artificial intelligence practice management platform for early childhood education in universities, and then discusses the development direction of the future practice management platform software. INTRODUCTION: This is the introductory text. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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