Influence of school characteristics on computational thinking: A supervised machine learning approach

被引:1
作者
Ezeamuzie, Ndudi O. [1 ,2 ]
机构
[1] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China
[2] Hong Kong Metropolitan Univ, Sch Sci & Technol, Dept Elect Engn & Comp Sci, Kowloon, Hong Kong, Peoples R China
关键词
Computational thinking; Data mining; ICT; Machine learning; School; Technology; METAANALYSIS; PERFORMANCE; SCIENCE; ONLINE;
D O I
10.1007/s10639-024-12644-9
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
This study explores the influence of schools' general characteristics, and their information and communication technology (ICT) capabilities on students' computational thinking. The computational thinking achievements of 31,823 students who participated in a large-scale comparative study in 1412 schools and across nine countries/regions were analyzed using supervised machine learning. Five classification rules were triangulated to determine how 22 schools' general characteristics and their ICT capabilities predicted students' computational thinking achievements. Data analysis showed no predictive relationship between schools' ICT capabilities and computational thinking. However, some classification rules predicted higher computational thinking achievement for students from affluent schools. The discussion amplifies the need for proper incorporation of ICT in schools with recommendations for more research on the nuanced relationship between schools' characteristics and computational thinking development.
引用
收藏
页码:20077 / 20101
页数:25
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