Development and Validation of Phonological Processing Assessment Tool in Kannada Language

The research evidence in orthographically transparent language Kannada indicates that phonological processing significantly influences reading acquisition, and deficits increase the risk of dyslexia. A comprehensive assessment of phonological processing that includes phonological awareness, phonological memory, and phonological naming is crucial for implementing effective intervention strategies, thereby reducing the risk of dyslexia. However, there is a notable absence of phonological processing assessment tools specifically designed and validated for children learning to read alphasyllabary Kannada. The present study addresses this gap by developing and validating a phonological processing assessment tool for children between Grade I and Grade III learning to read alphasyllabary languages such as Kannada. The study was conducted in two distinct phases. The first phase consisted of developing and piloting a phonological processing assessment tool. It included the stages of task selection, item generation, content validation, pilot testing, and reliability analysis. In the second phase, the developed tool was validated by administering it to both typically developing children and children at-risk for dyslexia from Grade I through Grade III. Subsequently, the developmental appropriateness of the tool was tested by comparing the performance of typically developing children between the grades. Additionally, diagnostic validity, including sensitivity, specificity, and area under the curve, was established by comparing the performance of typically developing and at-risk children. The study makes a substantial contribution to research on reading in Akshara orthographies, offering a valuable clinical tool for identifying children at-risk for dyslexia

Kannada · Linguistics · Natural language processing · Phonological development · Phonological rule · Phonology · Advanced Data Processing Techniques · Computer Science · Educational Methods and Technology · Employee Welfare and Language Studies · Artificial Intelligence

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