# data.attributes.resourceMetadata.description[].@value
Children learn effectively despite the inherent uncertainty and noisy variability of their environments, leveraging both passive exposure and active, goal-directed information-seeking strategies. Their learning unfolds across physical, digital, and increasingly, interactive robotic contexts. Ecological active learning frameworks emphasize how children exploit environmental affordances—objects, social partners, and routines—to construct knowledge efficiently. However, the motivational reward structures influencing learning, specifically collaborative versus competitive contexts, yield mixed evidence regarding which better supports engagement and learning. Social robots offer a uniquely controlled yet naturalistic platform to systematically investigate how these reward contingencies affect children's information-seeking and learning. This study aims to fill a critical gap by comparing collaborative and competitive framing in a robot-mediated learning task, holding task and partner behavior constant, to understand how children adapt their learning strategies to different social motivations across development.

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Learning strategies in collaboration vs. competition in cHRI

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bepress Digital Commons Three-Tiered Taxonomy

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bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].broader[].broader[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].broader[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].broader[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].broader[].broader[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].broader[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.subject[].inScheme[].title[].@value
bepress Digital Commons Three-Tiered Taxonomy

# data.attributes.resourceMetadata.title[].@value
Learning strategies in collaboration vs. competition in cHRI