What is she best known for?
The fields of study she is best known for:
- Cognition
- Artificial intelligence
- Cognitive science
Susan Goldin-Meadow spends much of her time researching Gesture, Cognitive psychology, Nonverbal communication, Language development and Communication.
Gesture recognition is the focus of her Gesture research.
Her research in Cognitive psychology intersects with topics in Teaching method and Body language.
Her Nonverbal communication study integrates concerns from other disciplines, such as Knowledge level, Sign and Expression.
Her Language development study combines topics in areas such as Language acquisition, Metalanguage, Multilingualism and Lexicon.
Her Communication study combines topics from a wide range of disciplines, such as Modalities, Coding, Hand movements and Meaning.
Her most cited work include:
- Hearing Gesture: How Our Hands Help Us Think (707 citations)
- Gesture Paves the Way for Language Development (656 citations)
- Explaining Math: Gesturing Lightens the Load (505 citations)
What are the main themes of her work throughout her whole career to date?
Her primary areas of investigation include Gesture, Cognitive psychology, Communication, Language acquisition and Sign language.
Her Gesture research incorporates themes from Cognition, Cognitive science, Language development and Nonverbal communication.
Her Cognitive psychology research incorporates elements of Embodied cognition, Spatial cognition, Comprehension and Action.
Her Communication research is multidisciplinary, incorporating elements of Semantics, Motion and Set.
Her Language acquisition research is multidisciplinary, incorporating perspectives in Language model, Syntax, Sentence and Developmental linguistics.
Her study looks at the intersection of Sign language and topics like Spoken language with Cued speech.
She most often published in these fields:
- Gesture (70.43%)
- Cognitive psychology (28.99%)
- Communication (24.06%)
What were the highlights of her more recent work (between 2017-2021)?
- Gesture (70.43%)
- Cognitive psychology (28.99%)
- Sign language (20.29%)
In recent papers she was focusing on the following fields of study:
Her scientific interests lie mostly in Gesture, Cognitive psychology, Sign language, Developmental psychology and Comprehension.
She has researched Gesture in several fields, including Context, Communication, Nonverbal communication, Language acquisition and Sign.
Her research in Language acquisition intersects with topics in Language development, Pragmatics, Vocabulary, Syntax and Syntax.
Her Cognitive psychology study incorporates themes from Naturalistic observation, Cognition, Meaning and Action.
The study incorporates disciplines such as Presentational and representational acting and Spoken language in addition to Sign language.
Her Developmental psychology study deals with Narrative intersecting with Longitudinal study and Early childhood.
Between 2017 and 2021, her most popular works were:
- Children's Early Decontextualized Talk Predicts Academic Language Proficiency in Midadolescence. (45 citations)
- Gesture helps learners learn, but not merely by guiding their visual attention. (21 citations)
- Comparing sign language and gesture: Insights from pointing (15 citations)
In her most recent research, the most cited papers focused on:
- Cognition
- Artificial intelligence
- Cognitive science
Susan Goldin-Meadow mainly focuses on Gesture, Nonverbal communication, Cognitive psychology, Sign language and Vocabulary.
Her study in Gesture is interdisciplinary in nature, drawing from both Context, Contrast, Perception and Affect, Communication.
Her studies deal with areas such as Teaching method, Cognition and Action as well as Nonverbal communication.
Her studies in Cognitive psychology integrate themes in fields like Variety and Affect.
Her Sign language research is multidisciplinary, relying on both Sign and Spoken language.
In her research, Developmental psychology and Language acquisition is intimately related to Syntax, which falls under the overarching field of Vocabulary.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
