Academic Scientific JournalsThe application of generative models in the education of a child with special educational needs at home: an autoethnographic analysis of parental experiences
DOI:
https://doi.org/10.26881/ndps.2024.53.05Keywords:
home education, special educational needs, generative artificial intelligence, autoethnography, ADHD, motor aphasia, personalizationAbstract
The article presents an autoethnographic reflection on the parental experience of using generative artificial intelligence (AI) to support home-based education of a child with special educational needs (SEN). The author describes his personal journey in supporting his son, who has motor aphasia, ADHD, and mild intellectual disability. Positive outcomes of AI use include personalized educational content, language skill development, emotional regulation support, and enhanced daily organization. However, challenges such as overly complex Al-generated content, overstimulation, and the need for ongoing parental intervention were also identified. Employing both analytical and evocative autoethnographic methods, the author maintained a reflective journal over three weeks. The findings highlight the importance of a conscious and critical approach to Al integration, emphasizing the parent' pivotal role in mediating technology use. This study provides insights into both opportunities and limitations of generative Al in the context of home education for children with special educational needs.
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