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Persistence is “expensive” in real life, as it involves opportunity costs. Thus, decisions concerning persisting vs. modifying goals should be prudent. Current research suggests that young children become more persistent through modeling. However, little is known regarding when and how young children develop the ability to monitor and control their performance over time and effectively decide to persist or to seek alternatives to maximize gains (i.e., “smart persistence”). Clarifying the developmental processes underlying smart persistence is needed to support children’s learning.
Our primary aim was to create a developmentally sensitive task to tap young children’s smart persistence by downwardly extending Newman et al.’s (1987) adult measure of learning efficiency. Typically developing 3- to 7-year-old children participated in a 60-minute laboratory session (N = 114). Children were given a smart persistence game, a metacognition interview, three executive function (EF) tasks, and a verbal intelligence assessment. In our smart persistence game, children were invited to pretend to go fishing in several spots, and the goal was to catch as many fish as possible to reach a goal line displayed on a score board. Unbeknownst to the child, the seven ordered spots were designed to increase in difficulty (all fish were catchable in Spot 1; none in Spot 7). After each trial, the child decided whether to stay at the current level, move back to prior (easier) levels, or move forward to the next (more challenging but more fish) level and were informed about how many chances remained. Smart persistence was scored on a 0-2 scale by giving 0 to children who never went back and 1 to those who stayed/went back but could not reach the goal and 2 to those who reached the goal. Most measures were significantly intercorrelated (Table 1).
First, we hypothesized that smart persistence would increase as a function of age. There was a significant age effect, β=.67, p<.001. Children ages 3-4 years persistently attempted overly challenging levels, whereas beginning at age 5, children improved in smart persistence.
Second, we hypothesized that metacognition and EF would be uniquely associated with smarter persistence while adjusting for age and verbal intelligence. However, there were no main effects of metacognition or EF.
Third, we hypothesized that the effect of children’s metacognition would be conditional on their EF. We found a significant interaction between metacognition and cool EF but not hot EF, while controlling for age and verbal intelligence, β=.5, p=.002. The relation between metacognition and smart persistence was stronger among children with high EF than those with low EF (Figure 1).
Our results indicate that smart persistence emerges as early as age 5 and depends on an interaction between metacognition and cool EF. It would be interesting to test if a reflection intervention during the game—helping children track their behaviors—would enable younger and lower-EF children to persist more prudently like older children. This research has implications for children’s motivation and performance in school, sports, and personal pursuits.