2026-10-14T11:12:10Z https://www.scidb.cn/oai

10.57760/sciencedb.28344 2026-06-01T12:58:42Z

2026-06-01 Raw Data for Two Experiments on Children’s Causal Learning from Correct and Incorrect Demonstrations in the Trap-Tube Paradigm doi:10.57760/sciencedb.28344 en Here we publish the raw datasets from two experiments investigating the effects of correct and incorrect demonstrations, as well as their order, on causal learning in 2- to 4-year-old children. The background, methods, and results of two experiments are described in the accompanying manuscript. Here is the abstract from our manuscript: Observing others’ demonstrations is an important route through which children acquire causal knowledge and develop scientific thinking. Using the trap-tube paradigm, the present study investigated the effects of correct and incorrect demonstrations and their order on causal learning in 2-4-year-olds. Experiment 1 (N = 352) showed that 2-year-olds showed no evidence of causal learning across all demonstration types, and their performance did not differ significantly between conditions. Among 3-year-olds and 4-year-olds, performance was better overall in the mixed-demonstration conditions than in the single-demonstration conditions. Within mixed demonstrations, order affected only 3-year-olds, with better performance in the correct-then-incorrect condition than in the incorrect-then-correct condition. Experiment 2 (N = 365) showed that 2-year-olds did not differ significantly across demonstration types, and their performance was largely near chance, whereas 3-year-olds and 4-year-olds performed better in the mixed-demonstration conditions than in the consistent-demonstration conditions. All children were more likely to change the side of insertion in the mixed-demonstration conditions than in the consistent-demonstration conditions. Overall, the findings suggest that mixed demonstrations support causal learning from age 3 onward, whereas evidence in 2-year-olds was weak and inconsistent. Casual learning; children; demonstration Huang Chenshan Shuiping Chen Yanping Wei PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank