From Programming Empowerment to AI Empowerment: A Study with Chinese Primary School Students in Information Technology Courses

This study aims to investigate and assess Chinese primary school students' knowledge and competence in AI and machine learning through a survey instrument. Building on established constructs of programming empowerment, including meaningfulness, impact, creative self-efficacy, programming self-efficacy, AI empowerment constructs, such as AI self-efficacy and interest in learning AI were added to the survey. A total of 324 sixth-grade students (49.4% female) enrolled in eight information technology courses from a Chinese primary school completed the survey. Collected survey responses were randomly split into half for training dataset and another half for validation purpose. An exploratory factor analysis (EFA) was performed with a sample of 162 students to identify key factors related to programming and AI empowerment. The results show that meaningfulness, impact, creative self-efficacy, programming self-efficacy, AI self-efficacy, and interest in learning AI are all related to programming and AI empowerment. Following this, confirmatory factor analysis (CFA) was employed to test validity of factors identified in the EFA. The findings indicate a good fit for the proposed model with those six factors. The findings not only help teachers, researchers and policy makers to understand primary school students' competence and understanding of AI and programming but also suggest factors for them to consider when creating and implementing AI curriculum and applications in schools.