Abstract

Developmental science has experienced a vivid debate on whether young children prioritize goals over means in their prediction of others' actions. Influential developmental theories highlight the role of goal objects for action understanding. Yet, recent infant studies report evidence for the opposite. The empirical evidence is therefore inconclusive. The current study advanced this debate by assessing preschool children's verbal predictions of others' actions. In five experiments (N=302), we investigated whether preschool children and adults predict agents to move towards their previous goal (that is, show goal-related predictions) or predict agents to move along the same movement path that they pursued before. While Experiments 1a, 1b and 1c presented young children and adults with animated agents, Experiments 2a and 2b presented participants with human grasping action. An integrative analysis across experiments revealed that children were more likely to predict the agent to move along the same movement path, Z=-4.574, p ≤ 0.0001 (r=0.304). That is, preschool children were more likely to predict that agents would move along the same trajectory even though this action would lead to a new goal object. Thus, our findings suggest that young children's action prediction relies on the detection of spatial and movement information. Overall, we discuss our findings in terms of theoretical frameworks that conceive of action understanding as an umbrella term that comprises different forms and facets in which humans understand others' actions. RESEARCH HIGHLIGHTS: We investigated whether preschool children predict agents to move towards their previous goal or to move along the same movement path that they pursued before. Unlike adults, preschool children predicted that agents would move along the same trajectory even though this action would lead to a new goal. Adults' goal-based predictions were affected from contextual details, whereas children systematically made path-based predictions. Young children's action prediction relies on the detection of spatial and movement information.

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