An artificial intelligence approach for selecting effective teacher communication strategies in autism education

Vasileios Lampos*, Joseph Mintz*, Xiao Qu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
12 Downloads (Pure)

Abstract

Effective inclusive education is key in promoting the long-term outcomes of children with autism spectrum conditions (ASC). However, no concrete consensus exists to guide teacher-student interactions in the classroom. In this work, we explore the potential of artificial intelligence as an approach in autism education to assist teachers in effective practice in developing social and educational outcomes for children with ASC. We form a protocol to systematically capture such interactions, and conduct a statistical analysis to uncover basic patterns in the collected observations, including the longer-term effect of specific teacher communication strategies on student response. In addition, we deploy machine learning techniques to predict student response given the form of communication used by teachers under specific classroom conditions and in relation to specified student attributes. Our analysis, drawn on a sample of 5460 coded interactions between teachers and seven students, sheds light on the varying effectiveness of different communication strategies and demonstrates the potential of this approach in making a contribution to autism education.
Original languageEnglish
Article number25
Number of pages10
Journalnpj Science of Learning
Volume6
Issue number1
DOIs
Publication statusPublished - 1 Sept 2021
Externally publishedYes

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