Hands-On Exploration of Cubes’ Floating and Sinking Benefits Children’s Subsequent Buoyancy Predictions

Children accrue experiences with buoyancy on a daily basis, yet research paints a mixed picture of children’s buoyancy knowledge. Whereas children’s predictions and explanations of the floating and the sinking of common objects are often based on a single feature (e.g., mass or facts), children’s predictions of novel cubes reveal solution strategies based on mass and volume integrations. Correspondingly, category learning theory suggests that categories (e.g., floaters vs. sinkers) are easier to identify when items mainly vary from one another in the relevant defining features. For example, a set of cubes only varies in mass and volume and hence density, thereby being able to highlight the deterministic role of density when placed in water. Here we asked how item variation during hands-on exploration affects children’s subsequent predictions and explanations of buoyancy. Kindergarteners and first-, second-, and third-grade children individually explored either a set of 10 systematically varied cubes (i.e., systematic condition; n = 95) or a set of 10 common objects (i.e., non-systematic condition; n = 96) in a water basin. Next, the children predicted the buoyancy of five new cubes and five new common objects one at a time. Subsequently, the children explained their predictions one subset at a time. The children in the systematic condition were more accurate in their predictions of the test cubes than the children in the non-systematic condition. Latent class regression analyses identified three cube prediction solution strategies. The children in the systematic condition were more likely to use a strategy in which buoyancy decisions were made based on an accurate integration of mass and volume, while the children in the non-systematic condition were more likely to use a strategy in which mass was given more predictive load than volume. A third strategy was characterized by guessing. Latent class analyses of the children’s explanations revealed different explanation strategies, each appealing to several features, but as hypothesized, no clear condition differences were found. The findings indicate that even 5 min of exploration with systematically varied cubes can already help children use an advanced buoyancy prediction strategy. This provides evidence in favor of using category learning theory to inform early science education design