When AI Is—and Is Not—Needed: AI Literacy and Computational Thinking in Primary STEM

Artificial intelligence (AI) is increasingly present in children’s lives, yet exposure does not necessarily lead to an accurate understanding of how AI works. This study examined whether a LEGO-based integrated STEM intervention could improve third-grade students’ AI literacy and computational thinking, particularly their ability to distinguish machine learning from rule-based automation and reason about training data, model error, and technology choice. An embedded mixed-methods, quasi-experimental pretest–posttest control-group design was conducted with 93 students from four intact classrooms. The experimental group (n = 46) completed eight weeks of authentic design problems, while the control group (n = 47) continued regular Life Studies instruction. After controlling for pretest scores, the experimental group significantly outperformed the control group in AI literacy, F(1, 90) = 152.51, p < .001, partial η2 = 0.629, and computational thinking, F(1, 90) = 22.18, p < .001, partial η2 = 0.198. Qualitative evidence showed a shift from viewing AI through robots and automatic actions toward reasoning about learning from examples, data diversity, limitations, human oversight, accessibility, and problem–technology fit. Integrated STEM instruction can foster critical AI literacy by making AI mechanisms visible and inviting students to judge whether AI is needed at all.