What is she best known for?
The fields of study she is best known for:
- Epistemology
- Artificial intelligence
- Cognitive science
Her primary scientific interests are in Cognitive development, Developmental psychology, Social psychology, Cognitive psychology and Causal inference.
Her research in Cognitive development intersects with topics in Concept learning, Epistemology, Inference and Bayes' theorem.
Her study in the field of Child development also crosses realms of Causal relations.
Her Social psychology study combines topics in areas such as Folk psychology, Preschool child, Consciousness, Age differences and Theory of mind.
Her work carried out in the field of Cognitive psychology brings together such families of science as Perception, Categorization and Early childhood education.
Her study in Causal inference is interdisciplinary in nature, drawing from both Isolation, Imitation, Causal reasoning and Bayesian inference.
Her most cited work include:
- Words, thoughts, and theories (1066 citations)
- Children's understanding of representational change and its relation to the understanding of false belief and the appearance-reality distinction. (1004 citations)
- Cultural learning. Author's reply (753 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Cognitive development, Cognitive psychology, Developmental psychology, Social psychology and Cognitive science.
Her Cognitive development study incorporates themes from Language development, Epistemology, Categorization, Gopnik and Concept learning.
Alison Gopnik has included themes like Perception, Causal reasoning, Causal inference, Theory of mind and Object in her Cognitive psychology study.
In her study, which falls under the umbrella issue of Causal reasoning, Probabilistic logic is strongly linked to Causal model.
Her Causal inference research includes elements of Set and Bayesian inference.
The Developmental psychology study combines topics in areas such as Visual perception, Inference, Causality and Action.
She most often published in these fields:
- Cognitive development (33.80%)
- Cognitive psychology (32.87%)
- Developmental psychology (31.48%)
What were the highlights of her more recent work (between 2016-2021)?
- Cognitive psychology (32.87%)
- Developmental psychology (31.48%)
- Cognitive development (33.80%)
In recent papers she was focusing on the following fields of study:
The scientist’s investigation covers issues in Cognitive psychology, Developmental psychology, Cognitive development, Theory of mind and Perception.
Her Cognitive psychology study integrates concerns from other disciplines, such as Space, Active learning, Object and Inference.
The various areas that Alison Gopnik examines in her Developmental psychology study include Probabilistic logic and Comprehension.
In her study, she carries out multidisciplinary Cognitive development and Intuition research.
Alison Gopnik interconnects Question answering, Test, Selection and Need to know in the investigation of issues within Theory of mind.
Her Perception research is multidisciplinary, incorporating elements of Framing, Analogy, Analogical reasoning and Relational reasoning.
Between 2016 and 2021, her most popular works were:
- Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood (82 citations)
- Explaining Constrains Causal Learning in Childhood. (28 citations)
- Childhood as a solution to explore-exploit tensions. (16 citations)
In her most recent research, the most cited papers focused on:
- Epistemology
- Artificial intelligence
- Cognitive science
Alison Gopnik focuses on Cognitive psychology, Developmental psychology, Cognitive development, Generalization and Causal learning.
Her Cognitive psychology research includes themes of Test, Question answering, Property, Theory of mind and Object.
Her studies in Developmental psychology integrate themes in fields like Task analysis and Cross-cultural studies.
Her multidisciplinary approach integrates Cognitive development and Cultural learning in her work.
The concepts of her Generalization study are interwoven with issues in Prior learning, Human–computer interaction, Set and Child development.
Her Causal learning study integrates concerns from other disciplines, such as Mathematical model and Bayesian probability, Bayesian inference.
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