Curiosity stimulates learning. We tested whether curiosity itself can be stimulated—not by extrinsic rewards but by an intrinsic desire to know whether a prediction holds true. Participants performed a numerical-facts learning task in which they had to generate either a prediction or an example before rating their curiosity and seeing the correct answer. More facts received high-curiosity ratings in the prediction condition, which indicates that generating predictions stimulated curiosity. In turn, high curiosity, compared with low curiosity, was associated with better memory for the correct answer. Concurrent pupillary data revealed that higher curiosity was associated with larger pupil dilation during anticipation of the correct answer. Pupil dilation was further enhanced when participants generated a prediction rather than an example, both during anticipation of the correct answer and in response to seeing it. These results suggest that generating a prediction stimulates curiosity by increasing the relevance of the knowledge gap.
This study investigated whether prompting children to generate predictions about an outcome facilitates activation of prior knowledge and improves belief revision. 51 children aged 9-12 were tested on two experimental tasks in which generating a prediction was compared to closely matched control conditions, as well as on a test of executive functions (EF). In Experiment 1, we showed that children exhibited a pu-
This study examined age-related differences in the effectiveness of two generative learning strategies (GLSs). Twenty-five children aged 9-11 and 25 university students aged 17-29 performed a facts learning task in which they had to generate either a prediction or an example before seeing the correct result. We found a significant Age 9 Learning Strategy interaction, with children remembering more facts after generating predictions rather than examples, whereas both strategies were similarly effective in adults. Pupillary data indicated that predictions stimulated surprise, whereas the effectiveness of example-based learning correlated with children's analogical reasoning abilities. These findings suggest that there are different cognitive prerequisites for different GLSs, which results in varying degrees of strategy effectiveness by age. Garvin Brod was supported by a Jacobs Foundation Early Career Research Fellowship. This study was preregistered on the Open Science Framework. All data and materials, along with analysis scripts, have been made publicly available and can be accessed at https://osf.io/e4h9n/?view_only=37f9109f122b42 faaec678796b225037. We thank Freya Moßig and Manuel Lieb for their help in collecting the data and Silvia Bunge for valuable discussions. Open access funding enabled and organized by Projekt DEAL.
Planning is an important but difficult self-regulation strategy. The successful implementation of a plan requires that the plan is retrievable in everyday life when it is needed. Children in particular are unlikely to use effective strategies to internalize plans in a way that makes them easy to remember. Therefore, we designed PROMPT, a planning app to help children create and internalize plans effectively. The app included different internalization activities that were hypothesized to promote deeper or shallower processing of plans. School-aged children (N = 106, 9-14 years) used PROMPT for 27 days in their daily lives. Contrary to our hypotheses, the type of internalization activity was not associated with memory success overall. Deeper processing activities were only effective for children who spent more time performing these activities, suggesting that there were differences in how effectively children could make use of the internalization activities. These individual differences were predicted by children’s grade level and their analogical reasoning abilities, and mediated by time on task. Findings suggest that a child-appropriate planning app needs to be personalized to be effective; internalization activities have to be tailored to children’s learning prerequisites.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.