Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Tamar Kushnir is active.

Publication


Featured researches published by Tamar Kushnir.


Psychological Science | 2010

Young Children Use Statistical Sampling to Infer the Preferences of Other People

Tamar Kushnir; Fei Xu; Henry M. Wellman

Psychological scientists use statistical information to determine the workings of human behavior. We argue that young children do so as well. Over the course of a few years, children progress from viewing human actions as intentional and goal directed to reasoning about the psychological causes underlying such actions. Here, we show that preschoolers and 20-month-old infants can use statistical information—namely, a violation of random sampling—to infer that an agent is expressing a preference for one type of toy instead of another type of toy. Children saw a person remove five toys of one type from a container of toys. Preschoolers and infants inferred that the person had a preference for that type of toy when there was a mismatch between the sampled toys and the population of toys in the box. Mere outcome consistency, time spent with the toys, and positive attention toward the toys did not lead children to infer a preference. These findings provide an important demonstration of how statistical learning could underpin the rapid acquisition of early psychological knowledge.


Psychological Science | 2005

Young Children Infer Causal Strength From Probabilities and Interventions

Tamar Kushnir; Alison Gopnik

We examine the interaction of two cues that children use to make judgments about cause-effect relations: probabilities and interventions. Children were shown a “detector” that lit up and played music when a block was placed on its surface. We varied the probabilistic effectiveness of the block, as well as whether the experimenter or the child was performing the interventions. In Experiment 1, we found that children can use probabilistic evidence to make inferences about causal strength. However, when the results of their own interventions are in conflict with the overall frequencies, preschoolers favor the results of their own interventions. In Experiment 2, children used probabilistic evidence to infer a hidden causal mechanism. Though they again gave preference to their own interventions, they did not do so when their interventions were explicitly confounded by an alternative cause.


Current Directions in Psychological Science | 2013

Infants Are Rational Constructivist Learners

Fei Xu; Tamar Kushnir

What is the nature of human learning, and what insights can be gained from understanding early learning in infants and young children? This is an important question for understanding the human mind, the origins of knowledge, scientific reasoning, and how to best structure our educational environment. In this article, we argue for a new approach to cognitive development: rational constructivism. This view characterizes the child as a rational constructive learner, and it sees early learning as rational, statistical, and inferential. Empirical evidence for this approach has been accumulating rapidly, and a set of domain-general statistical and inferential mechanisms have been uncovered to explain why infants and young children learn so fast and so well.


Memory & Cognition | 2006

The importance of decision making in causal learning from interventions

David M. Sobel; Tamar Kushnir

Recent research has focused on how interventions benefit causal learning. This research suggests that the main benefit of interventions is in the temporal and conditional probability information that interventions provide a learner. But when one generates interventions, one must also decide what interventions to generate. In three experiments, we investigated the importance of these decision demands to causal learning. Experiment 1 demonstrated that learners were better at learning causal models when they observed intervention data that they had generated, as opposed to observing data generated by another learner. Experiment 2 demonstrated the same effect between self-generated interventions and interventions learners were forced to make. Experiment 3 demonstrated that when learners observed a sequence of interventions such that the decision-making process that generated those interventions was more readily available, learning was less impaired. These data suggest that decision making may be an important part of causal learning from interventions.


Cognitive Science | 2013

A Comparison of American and Nepalese Children's Concepts of Freedom of Choice and Social Constraint

Nadia Chernyak; Tamar Kushnir; Katherine M. Sullivan; Qi Wang

Recent work has shown that preschool-aged children and adults understand freedom of choice regardless of culture, but that adults across cultures differ in perceiving social obligations as constraints on action. To investigate the development of these cultural differences and universalities, we interviewed school-aged children (4-11) in Nepal and the United States regarding beliefs about peoples freedom of choice and constraint to follow preferences, perform impossible acts, and break social obligations. Children across cultures and ages universally endorsed the choice to follow preferences but not to perform impossible acts. Age and culture effects also emerged: Young children in both cultures viewed social obligations as constraints on action, but American children did so less as they aged. These findings suggest that while basic notions of free choice are universal, recognitions of social obligations as constraints on action may be culturally learned.


Psychological Science | 2013

Giving Preschoolers Choice Increases Sharing Behavior

Nadia Chernyak; Tamar Kushnir

Young children are remarkably prosocial, but the mechanisms driving their prosociality are not well understood. Here, we propose that the experience of choice is critically tied to the expression of young children’s altruistic behavior. Three- and 4-year-olds were asked to allocate resources to an individual in need by making a costly choice (allocating a resource they could have kept for themselves), a noncostly choice (allocating a resource that would otherwise be thrown away), or no choice (following instructions to allocate the resource). We measured subsequent prosociality by allowing children to then allocate new resources to a new individual. Although the majority of children shared with the first individual, children who were given costly alternatives shared more with the new individual. Results are discussed in terms of a prosocial-construal hypothesis, which suggests that children rationally infer their prosociality through the process of making difficult, autonomous choices.


PLOS ONE | 2014

The Child as Econometrician: A Rational Model of Preference Understanding in Children

Christopher G. Lucas; Thomas L. Griffiths; Fei Xu; Christine Fawcett; Alison Gopnik; Tamar Kushnir; Lori Markson; Jane Hu

Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain childrens ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding.


Cognitive Science | 2009

Inferring Hidden Causal Structure

Tamar Kushnir; Alison Gopnik; Christopher G. Lucas; Laura Schulz

We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system. Given minimal training and no feedback, participants in Experiment 1 used causal graph notation to spontaneously draw structures containing one observed cause, one unobserved common cause, and two unobserved independent causes, depending on the pattern of associations and interventions they saw. We replicated these findings with less-informative training (Experiments 2 and 3) and a new apparatus (Experiment 3) to show that the pattern of data leads to hidden causal inferences across a range of prior constraints on causal knowledge.


Journal of Cognition and Development | 2014

The Self as a Moral Agent: Preschoolers Behave Morally but Believe in the Freedom to Do Otherwise

Nadia Chernyak; Tamar Kushnir

Recent work suggests a strong connection between intuitions regarding our own free will and our moral behavior. We investigate the origins of this link by asking whether preschool-aged children construe their own moral actions as freely chosen. We gave children the option to make three moral/social choices (avoiding harm to another, following a rule, and following peer behavior) and then asked them to retrospect as to whether they were free to have done otherwise. When given the choice to act (either morally or immorally), children avoided harm and abided by rules, but they endorsed their freedom to have done otherwise. When choice was restricted by adult instruction, children did not endorse their free choice and indicated feeling constrained by moral obligation in their explanatory responses. These results suggest that children believe that their moral actions afford free will, but this belief is dependent on their experience of choice.


Developmental Psychology | 2017

What I don’t know won’t hurt you: The relation between professed ignorance and later knowledge claims.

Tamar Kushnir; Melissa A. Koenig

Testimony is a valuable source of information for young learners, in particular if children maintain vigilance against errors while still being open to learning from imperfectly knowledgeable sources. We find support for this idea by examining how children evaluate individual speakers who present very different epistemic risks by being previously ignorant or inaccurate. Results across 2 experiments show that children attribute knowledge to (Experiment 1) and endorse new claims made by speakers (Experiment 2) who previously professed ignorance about familiar object labels, but not to speakers whose labels were previously inaccurate. Study 2 further clarifies that children are not simply relying on links between informational access and knowledge; children rejected testimony from a previously inaccurate speaker even when she had perceptual access to support her claim. These results show that children actively monitor the reliability of a speaker’s knowledge claims, distinguish unreliable speakers from those who sometimes admit ignorance, raising new questions about how such admissions factor in to children’s appraisal of the scope and limits of a person’s knowledge.

Collaboration


Dive into the Tamar Kushnir's collaboration.

Top Co-Authors

Avatar

Alison Gopnik

University of California

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Fei Xu

University of California

View shared research outputs
Top Co-Authors

Avatar

Laura Schulz

Massachusetts Institute of Technology

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge