The purpose of this study is to analyze the difficulties experienced by parents of children with disabilities by using semantic network analysis, one of analytic methods using a big data, to enhance understanding of families of children with disabilit...
The purpose of this study is to analyze the difficulties experienced by parents of children with disabilities by using semantic network analysis, one of analytic methods using a big data, to enhance understanding of families of children with disabilities and to find implications for better educating disabled children. To this end, data was searched on the TEXTOM program, using search terms of parents of disabled infants & difficulty of parents of disabled infants, and setting two years for the search period, which was from November 27, 2020 to November 2022. Then, through two rounds of refinement, the TF-IDF and frequency of the refined final data were identified, and the top 50 words based on TF-IDF were selected as final keywords. Semantic network analysis was conducted with these 50 final keywords. As a result, first, among 50 keywords, 'development', 'kid', 'child', 'education', 'infant', and 'disability' were ranked high. Second, as a result of centrality analysis of 50 keywords, the six keywords of 'disability', 'parent', 'difficulty', 'infant', 'child', and 'development' are all consistently ranked high across the connection centrality, proximity centrality, and betweenness centrality analyses. Third, as a result of the CONCOR analysis, a total of four clusters were formed. This study identified the difficulties of families of children with disabilities, suggesting that it can be used as a source to set up effective policy measures for the education of children with disabilities.