1. How Do Hong Kong Bilingual Children with Chinese Dyslexia Perceive Dyslexia and Academic Learning? An Interview Study of Metaphor Analysis
- Author
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Brian W. L. Wong, Hau Ching Lam, Julia Wing Ka Lo, Urs Maurer, and Shuting Huo
- Abstract
While extensive quantitative research has shed light on the cognitive mechanisms of dyslexia, few mixed-methods studies have been conducted to examine the perceptions of and attitudes towards learning in children with dyslexia, especially in Hong Kong, a bilingual context. In addition, the validity of the metaphor elicitation technique, which was adopted in previous interview studies, has not yet been examined in children. Therefore, 30 children with dyslexia (age range: 8-13; 10 females) in Hong Kong were interviewed for metaphors regarding six domains: Chinese reading, Chinese writing, having Chinese lessons, English reading, solving maths problems, and dyslexia. Word reading fluency and parent-rated learning interest and confidence were measured to validate the use of the metaphor elicitation method in assessing children's reading attitudes in both Chinese and English using correlation analyses. Perceptions were examined by way of qualitative analyses based on the metaphor entailments. Results showed that children who expressed more positive attitudes towards English reading performed better in English reading. Moreover, the attitudes also positively correlated with the corresponding parents' ratings. These findings suggested that the metaphor elicitation technique is a valid method for assessing attitudes towards English reading in children with dyslexia. Furthermore, their perceptions of dyslexia and learning generally corresponded to those from previous interview studies despite differences in languages and contexts. Importantly, descriptions related to multiple themes, including metalinguistic awareness, cognitive skills, coping strategies, and dyslexia, were well-aligned with scientific findings, demonstrating that children already have a good understanding of dyslexia and various learning domains.
- Published
- 2024
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