Teachers’ Perceptions and Challenges in Implementing Digital Learning for Autism Spectrum Disorder (ASD) Students in Inclusive Classrooms
Year: 2025
Type: article
Abstract: The aim of the study is to explore the perceptions and challenges encountered by teachers in implementing digital learning for ASD students within inclusive classroom settings. The research niche emphasises how crucial it is to take into account the viewpoint of teachers in order to implement digital learning for ASD students in inclusive classroom environments. The research addresses gaps in understanding teachers' perspectives and challenges in using digital learning for ASD students in inclusive classrooms and to provide insights into teacher needs and solutions for digital learning in ASD-inclusive settings. Therefore, this qualitative study was conducted by interviewing 12 teachers (N=12) from schools in Kuala Lumpur, Malaysia. The results show that digital learning could help teachers in the teaching and learning process of ASD students in the inclusive classroom. The findings emphasise that teachers view the use of digital tools in inclusive classrooms as facilitating their preparation and lesson planning for ASD students. They also consider digital technology as providing personalised instructions to ASD students and enabling data tracking and progress monitoring. Furthermore, teachers believe that digital tools can help engage ASD students in lessons. However, teachers stated challenges that related to attention difficulties and technological issues. Teachers also faced challenges in transitioning between activities or devices for ASD students and the issue regarding sensory sensitivities, which hinders the learning process. As a conclusion, teachers have provided positive perceptions towards the use of digital learning for ASD students in inclusive classrooms, yet still face some challenges that definitely have solutions.
Source: Journal Of ICT In Education
Authors: Nor Amalina Rusli, Meyly Kheng
Institution: University of Debrecen
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4411938557