A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches

When confronted with novel problems, problem-solvers must decide whether to copy a modeled solution or to explore their own unique solutions. While past work has established that infants can learn to solve problems both through their own exploration and through imitation, little work has explored th...

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Autores principales:	Hannah Solby, Mia Radovanovic, Jessica A. Sommerville
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	cognitive development exploration infant development motion capture technology automated behavioral analysis problem solving Psychology BF1-990
Acceso en línea:	https://doaj.org/article/93142bb84137469e9eea68c578d191ec
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spelling	oai:doaj.org-article:93142bb84137469e9eea68c578d191ec2021-11-08T04:45:59ZA New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches1664-107810.3389/fpsyg.2021.705108https://doaj.org/article/93142bb84137469e9eea68c578d191ec2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fpsyg.2021.705108/fullhttps://doaj.org/toc/1664-1078When confronted with novel problems, problem-solvers must decide whether to copy a modeled solution or to explore their own unique solutions. While past work has established that infants can learn to solve problems both through their own exploration and through imitation, little work has explored the factors that influence which of these approaches infants select to solve a given problem. Moreover, past work has treated imitation and exploration as qualitatively distinct, although these two possibilities may exist along a continuum. Here, we apply a program novel to developmental psychology (DeepLabCut) to archival data (Lucca et al., 2020) to investigate the influence of the effort and success of an adult’s modeled solution, and infants’ firsthand experience with failure, on infants’ imitative versus exploratory problem-solving approaches. Our results reveal that tendencies toward exploration are relatively immune to the information from the adult model, but that exploration generally increased in response to firsthand experience with failure. In addition, we found that increases in maximum force and decreases in trying time were associated with greater exploration, and that exploration subsequently predicted problem-solving success on a new iteration of the task. Thus, our results demonstrate that infants increase exploration in response to failure and that exploration may operate in a larger motivational framework with force, trying time, and expectations of task success.Hannah SolbyMia RadovanovicJessica A. SommervilleFrontiers Media S.A.articlecognitive developmentexplorationinfant developmentmotion capture technologyautomated behavioral analysisproblem solvingPsychologyBF1-990ENFrontiers in Psychology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	cognitive development exploration infant development motion capture technology automated behavioral analysis problem solving Psychology BF1-990
spellingShingle	cognitive development exploration infant development motion capture technology automated behavioral analysis problem solving Psychology BF1-990 Hannah Solby Mia Radovanovic Jessica A. Sommerville A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
description	When confronted with novel problems, problem-solvers must decide whether to copy a modeled solution or to explore their own unique solutions. While past work has established that infants can learn to solve problems both through their own exploration and through imitation, little work has explored the factors that influence which of these approaches infants select to solve a given problem. Moreover, past work has treated imitation and exploration as qualitatively distinct, although these two possibilities may exist along a continuum. Here, we apply a program novel to developmental psychology (DeepLabCut) to archival data (Lucca et al., 2020) to investigate the influence of the effort and success of an adult’s modeled solution, and infants’ firsthand experience with failure, on infants’ imitative versus exploratory problem-solving approaches. Our results reveal that tendencies toward exploration are relatively immune to the information from the adult model, but that exploration generally increased in response to firsthand experience with failure. In addition, we found that increases in maximum force and decreases in trying time were associated with greater exploration, and that exploration subsequently predicted problem-solving success on a new iteration of the task. Thus, our results demonstrate that infants increase exploration in response to failure and that exploration may operate in a larger motivational framework with force, trying time, and expectations of task success.
format	article
author	Hannah Solby Mia Radovanovic Jessica A. Sommerville
author_facet	Hannah Solby Mia Radovanovic Jessica A. Sommerville
author_sort	Hannah Solby
title	A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
title_short	A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
title_full	A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
title_fullStr	A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
title_full_unstemmed	A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches
title_sort	new look at infant problem-solving: using deeplabcut to investigate exploratory problem-solving approaches
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/93142bb84137469e9eea68c578d191ec
work_keys_str_mv	AT hannahsolby anewlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches AT miaradovanovic anewlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches AT jessicaasommerville anewlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches AT hannahsolby newlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches AT miaradovanovic newlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches AT jessicaasommerville newlookatinfantproblemsolvingusingdeeplabcuttoinvestigateexploratoryproblemsolvingapproaches
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A New Look at Infant Problem-Solving: Using DeepLabCut to Investigate Exploratory Problem-Solving Approaches

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