Abstract
Artificial Intelligence (AI) education in primary schools has received a great deal of attention globally, and it is thus important to investigate primary school students’ perceptions and understanding of AI learning. Therefore, in this study, 673 drawings of conceptions of AI learning by third to sixth grade students were collected. Firstly, a drawing analysis approach was used to code the drawings into five categories of 25 elements. Then, the epistemic network analysis approach was used to visualize the structure of the relationships between the elements within the conceptions of AI learning. The study found that (1) primary school students generally held positive attitudes toward AI learning and understood AI learning as programming or robot programming learning; (2) higher grade students showed more constructive learning concepts; and (3) girls had significantly more positive emotions and attitudes toward AI learning than boys, but had less participation in manipulating robotic human activities than boys. The over-reliance on programming and robotics in elementary AI education, as well as gender differences in elementary AI learning need more attention from educators.
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Funding
This study was funded by the National Natural Science Foundation of China (Grant No. 72274076) and Funding for Basic Research Operating Expenses of Central Universities ‘Premium Program’ (NO. 2023CXZZ092).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Hanrui Gao, Sunan Zhao and Ying Wang. Project administration were performed by Yi Zhang and Kang Wang. Methodology and supervision were performed Yi Zhang and Gwo-Jen Hwang. The first draft of the manuscript was written by Hanrui Gao. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Gao, H., Zhang, Y., Hwang, GJ. et al. Delving into primary students’ conceptions of artificial intelligence learning: A drawing-based epistemic network analysis. Educ Inf Technol 29, 25457–25486 (2024). https://doi.org/10.1007/s10639-024-12847-0
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DOI: https://doi.org/10.1007/s10639-024-12847-0