토픽모델링과 의미연결망 분석을 통한 자폐성 장애아 연구동향 분석

초록

This study explores research trends related to children with autism spectrum disorder (ASD) through topic modeling and semantic network analysis. A total of 881 articles published in the Korean Citation Index (KCI) between January 2000 and January 2025 were selected for analysis. The first phase (2000-2007) focused on learning-centered studies that categorize Autism Spectrum Disorder as an emotional disorder. The second phase (2008-2017) marked the implementation of the Special Education Act for Persons with Disabilities, which led to the expansion of behavioral intervention research. The third phase (2017-2025) highlighted diversified instructional strategies and the emergence of digital technology-based interventions. Topic modeling revealed four major themes: language ability (15.2%), behavioral intervention (37.6%), social skills enhancement (24.5%), and educational support (22.7%). Semantic network analysis further demonstrated the centrality of keywords such as “use,” “ability,” and “group” in the language ability topic; “intervention,” “design,” and “behavior” in the behavioral intervention category; “behavior,” “society,” and “development” in the social skills enhancement theme; and “education,” “society,” and “materials” in the educational support domain. Educational Impact and Implications: This study confirms that ASD research in Korea has evolved across distinct phases, focusing sequentially on language ability, behavioral interventions, social skills enhancement, and educational support. These findings provide a foundation for setting stepwise goals in ASD curricula. The increasing use of digital and AI-based interventions highlights the need for a technology-integrated approach to program development. Furthermore, strengthening collaboration between teachers and parents is essential for building a coherent home-school support system and aligning educational practices with policy frameworks.

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