Learning through Feature Prediction: An Initial Investigation into Teaching Categories to Children with Autism through Predicting Missing Features

Individuals with autism have difficulty generalising information from one situation to another, a process that requires the learning of categories and concepts. Category information may be learned through: (1) classifying items into categories, or (2) predicting missing features of category items. Predicting missing features has to this point been little used in special education. Children with autism were taught novel category information through either classification or feature prediction tasks. Both methods resulted in successful category learning. Furthermore, feature prediction learning resulted in better performance when predicting missing features of items at test. These results suggest that while both tasks are valuable tools for teaching categories to children with autism, the feature prediction task provides more successful post-learning use of the information acquired.