Vocabulary development in autistic children: a network growth analysis

Area of Science:

• Developmental Psychology
• Computational Linguistics
• Neurodevelopmental Disorders

Background:

• Autistic children often exhibit delayed expressive vocabulary development.
• Early word learning processes in autism are not well understood.
• This study investigates vocabulary acquisition in autistic and non-autistic children.

Purpose of the Study:

• To compare network growth models in explaining vocabulary acquisition trajectories.
• To analyze early word learning in autistic and non-autistic children.
• To identify similarities and differences in vocabulary development.

Main Methods:

• Utilized item-level data from child vocabulary checklists for 721 autistic children and 2,166 non-autistic toddlers.
• Estimated vocabulary growth trajectories and assessed model fit using network growth models.
• Computed word-level acquisition norms and evaluated model performance based on semantic structure and word associations.

Main Results:

• Word-level acquisition norms proved useful, especially when age-based norms are unavailable for neurodivergent populations.
• Network growth models explained comparable variance in vocabulary acquisition for both autistic and non-autistic children.
• Both groups showed a bias towards learning words connected to previously acquired vocabulary, with an additional boost from environmental word connections.

Conclusions:

• Autistic and non-autistic children preferentially acquire words by utilizing the semantic structure of their learning environment.
• Theoretical models of vocabulary growth show significant overlap between autistic and non-autistic developmental trajectories.
• Findings suggest a shared underlying mechanism in leveraging semantic networks for word learning.