Convolutional neural network modelling for autistic individualized education chatbot

• Published in: IAES International Journal of Artificial Intelligence
• Main Author: Hamzah R.; Jamil N.; Ahmad N.D.; Syed Zainal Ariffin S.M.Z.
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2025
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211140993&doi=10.11591%2fijai.v14.i1.pp109-118&partnerID=40&md5=abadb004ea2d057645ac699d298d9393

The traditional education system for autistic kids needs integration with computer technology that embraces artificial intelligence to help school instructors and management. An application that enables the teacher to retrieve information from a trusted source is essential since the information is only sometimes available on time. Thus, developing a chatbot application that utilizes natural language processing can enhance the management of autistic schools and will help individualized education for autistic students. This research uses a deep learning model that utilizes a convolutional neural network to develop a chatbot as a teaching assist tool for teachers. The results show that the chatbot has achieved ˜0.03% loss when trained with different epoch numbers. In terms of usability, the chatbot achieves mean system usability scores of 80.48 ± 13.03. This may open opportunities for more effective individualized education for students with special needs and increase the potential to improve inclusive education for disabled students. It is useful to include future actions that enable the simplification of the use of this chatbot tool in a wide range of contexts. To close the education gap for children with disabilities, chatbots could help people with communication disabilities and could also significantly enhance the rate of communication. © 2025, Institute of Advanced Engineering and Science. All rights reserved.