Predicting reading outcomes in school starters using a computer assisted dynamic assessment of decoding

Early and accurate identification of children at risk of reading difficulties is essential for ensuring timely and appropriate educational support. Traditional screening tools are static, measuring only current knowledge. As a result, poor performance may reflect either a specific learning difficulty such as dyslexia or limited prior learning opportunities, making accurate identification challenging. This study examined the potential of a computer-assisted Dynamic Assessment (DA) of decoding, which measures learning potential through responsiveness to training, as an alternative approach. In a longitudinal study, 317 reception-aged children (mean age 5 years 3 months) completed the DA of decoding along with static assessments of reading, related skills, and non-verbal ability. Ten months later, 286 of these children were reassessed on the measures of word reading. The DA of decoding accounted for significant unique variance in later word reading and demonstrated excellent classification accuracy in identifying children at risk of dyslexia. For children with English as an Additional Language (EAL), combining the DA with static measures resulted in perfect classification accuracy. Further analysis of a sub-sample of non-readers suggests that administering the DA earlier in the school year could increase its predictive value for all learners. These findings support the use of DA of decoding as a promising early screening tool, particularly for culturally and linguistically diverse children who may be misidentified by traditional static assessments.