Using Response Time of a Computer-Administered MOCCA to Predict Reading Proficiency

Abstract

Reading involves several stages of information processing. Individuals without reading comprehension difficulties had shorter information processing times because they had achieved automatic information processing in reading. This suggests that response times can provide information about reading automaticity, a necessary characteristic for reading-to-learn. This study examined whether reading response times provided additional information, over and above item responses, in predicting 3rd through 5th grade students’ end-of-year statewide test performance. Specifically, the study examined whether the response time on correctly answered test items can be used to improve the prediction of proficiency on the statewide test. Results showed that students from all three grades who have a higher number of fast and correct responses have a lower expected probability of being at-risk than students whose responses are slow and correct. Although slow and correct responses helped predict proficiency status in all three grades, it added less value to the model. Lastly, the AUC showed that the predicted probabilities of all three grades are relatively accurate in predicting proficiency. Considering the detrimental effects of misidentifying at-risk or not-at-risk students, it is important to correctly identify at-risk students and provide instructions at an early stage, as reading comprehension is crucial for children’s future success.