Developing Computational Thinking Questions for Upper Elementary Students with Mild Autism Spectrum Disorder

Abstract

This research developed questions to measure the improvement in computational thinking (CT) abilities of children with mild autism spectrum disorder (ASD). A quantitative approach was used in this research, with data collection through filling out expert judgment questionnaires by material experts and questions related to CT. The study results showed that the questions created were considered good for use in improving the CT abilities of children with ASD. The results of material expert validation showed an average value of 78.32%, which falls into the good category. In contrast, the question expert validation gives a perfect score, which confirms the validity of the questions created for the material and learning objectives used. The question instrument developed includes three main components of CT, namely decomposition, pattern recognition, and algorithm design, with a design that uses images and visual elements as well as simple instructions to facilitate understanding and involvement in children with ASD. This study bring a positive contribution to the development of more inclusive and effective CT learning for children with ASD.