Faculty of Computing

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    ItemOpen Access
    Enhancing Cognitive and Metacognitive Domains of Autistic Children Using Machine Learning
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-08-21) Tharaki, D; Rupasinghe, Y; Ruhunage, P; Pehesarani, A; Rathnayake, S.C
    ASD poses special difficulty in both cognitive and metacognitive development, necessitating specialized educational strategies. This research proposes LearnMate, a web-based application powered by machine learning techniques that aims to improve the abilities of children with autism. Utilizing classification models learned from medical data, LearnMate forecasts skill acquisition and suggests personalized learning activities according to the strengths and developmental requirements of the child. The system permits instructors to monitor progress through real-time feedback, enabling adaptive learning approaches. Pilot application to more than 100 children showed significant gains in their skills. The results demonstrate the immense potential for change through machine learning in special education to facilitate data-driven, personalized learning opportunities that enhance the capabilities of both autistic students and teachers.
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    PublicationEmbargo
    A technological intervention for improving cognitive abilities based on the preferences of Autistic children
    (IEEE, 2021-10-27) Gunathilake, Y. A. G. U. T; Fasliya, R. F; Premarathne, R. D. A. R; Kalhara, D. P; Karunasena, A; Bandara, P. S
    autism spectrum disorder (ASD) is a multiplex developmental condition which limits the performance of communication and social interaction of young children while hin- dering development of their cognitive capabilities. To educate the Autistic children, this application caters the needs with number of aspects as selection of activities, that develop the cognitive capabilities and user-friendliness. To address the limitations which pays considerations to aspects as above, this research proposes an interactive web application to enhance the educational needs of Autistic children aged 5–8 years with a novel pack of technologies including Augmented Reality (AR), image processing, eye tracking and machine learning. The application has implemented activities to enhance the vocabulary of children using AR while also presenting a number of other activities as drawing activities to improve the motor skills. To analyze how comfortable the children are with the technology, the children are monitored using processing of their drawings, eye-tracking, and emotion identification with voice assisted support are extended.