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Motivational frameworks correlate with academic achievement from elementary through high school (Park, Gunderson, Tsukayama, Levine & Beilock, 2016; Blackwell, Trzesniewski & Dweck, 2007; Paunesku et al., 2015). Research on children’s pursuit of challenging goals based on motivational frameworks take for granted, however, that children can understand the relative difficulty of tasks to select their goals. Although environmental factors, such as parental praise, influence children’s motivational frameworks in early childhood (Gunderson et al., 2013; Stipek & Iver, 1989), the role of parent interactions in shaping children’s concept of difficulty and motivational frameworks remains unknown. In this study, we will experimentally manipulate the kind of “easy” feedback children receive after success and measure the effect this feedback has on children’s motivational responses, such as goal choice, persistence, attributions for failure, and strategy generation. We will also attempt to replicate previous studies showing that different types of praise (process, person) change children’s motivational responses. Finally, we will explore whether parents’ self-reported motivational beliefs relate to their children’s motivational responses.

Spatial skills, specifically the abilities to mentally represent and manipulate spatial information, are a major predictor of success in STEM. Prior research has shown that the frequency of home learning activities (e.g., playing with puzzles and building with blocks) and parents’ support during these activities (e.g., spatial talk and gestures) correlated with young children’s spatial skills. However, causal evidence on the effect of home learning activities on children’s spatial skills is limited. The current project aims at establishing causal relationships between spatial home learning activities and spatial skills through a parent intervention. The intervention involves parents and children playing with spatial activities or control (i.e., verbal) activities for a month and parents receiving messages about the importance and malleability of spatial or verbal skills.

The ability to estimate task difficulty is critical for many real-world decisions such as setting appropriate goals for ourselves or appreciating others' accomplishments. Here we give a computational account of how humans judge the difficulty of a range of physical construction tasks (e.g., moving 10 loose blocks from their initial configuration to their target configuration, such as a vertical tower) by quantifying two key factors that influence construction difficulty: physical effort and physical risk. Physical effort captures the minimal work needed to transport all objects to their final positions, and is computed using a hybrid task-and-motion planner. Physical risk corresponds to stability of the structure, and is computed using noisy physics simulations to capture the costs for precision (e.g., attention, coordination, fine motor movements) required for success. We show that the full effort-risk model captures human estimates of difficulty and construction time better than either component alone.