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An Empirical Research on the Current State of Pre-service Teachers' Instructional Design Ability of Artificial Intelligence Courses in Primary Schools ( EI收录)
文献类型:期刊文献
英文题名:An Empirical Research on the Current State of Pre-service Teachers' Instructional Design Ability of Artificial Intelligence Courses in Primary Schools
作者:He, Zhenzhen[1]; Zhang, Wei[1]; Zhao, Ying[1]; Lyu, Xiaohong[2]
第一作者:He, Zhenzhen
机构:[1] Beijing Union University, Teacher College, Beijing, China; [2] Guangdong University of Education, Teacher Education College, Guangzhou, China
第一机构:北京联合大学师范学院
年份:2025
起止页码:394-398
外文期刊名:2025 10th International Conference on Distance Education and Learning, ICDEL 2025
收录:EI(收录号:20254719571977)
语种:英文
外文关键词:Curricula - Design - Education computing - Students - Teaching
摘要:The implementation of artificial intelligence (AI) universal education in primary schools is a national intelligent education project, while pre-service teachers' instructional design ability to carry out AI courses is a key factor to advancing the high-quality development of AI universal education. Therefore, this study conducted empirical research on detecting the current state of pre-service teachers' instructional design ability of educational policies-oriented AI courses in primary schools. 121 pre-service teachers were recruited to complete separately AI lesson plans. An assessment rubrics used to analyze the lesson plans was developed from five dimensions of teaching content analysis, student situation analysis, teaching objectives design, teaching method design and teaching process design, and instructional evaluation design. Furthermore, both qualitative and quantitative analysis methods were conducted to evaluate their instructional design ability of AI courses in primary schools. It was found that the pre-service teachers' overall instructional design ability of AI course in primary schools was good, but the sub-ability of instructional evaluation design were badly unqualified. The shortcomings of pre-service teachers' AI instructional design ability were mainly reflected in lacking systematic understanding of the teaching content and teaching objectives for AI universal education in primary schools, and having difficulty in flexibly applying teaching theories to carry out detailed analysis and design. To address these shortcomings, this paper put forward targeted proposals from three aspects of strengthening interpretation and publicity of AI-related policies, providing more teaching practice opportunities, and intensifying awareness of self-directed learning, in order to provide references for promoting the construction of AI pre-service teachers. ? 2025 IEEE.
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