Michael Eason

Date of Award

Spring 2022

Document Type

Open Access Thesis



First Advisor

Scott L. Decker


While some children’s reading difficulties are a consequence of socio-economic factors and inadequate instruction, other children have extreme difficulties learning to read despite having adequate educational opportunity and adequate levels of intelligence. These children are classified under the Individuals with Disabilities Education Act (IDEA) as having a learning disability specific to reading (SLD-R). The identification of children with SLD-R is costly on time, personnel, and other school resources, and due to an insufficient number of resources generally available to schools, the methods implemented for identifying children are alarmingly inconsistent. The aim of the current study is to investigate the task demands of a recently developed computerized test of isolated word reading that was developed to address the resource barriers seen in schools. The task demands were explored by using both person and item characteristics to predict response-likelihood across items. An initial multiple logistic regression analyses revealed that a person’s phonological awareness and oral vocabulary abilities directly predicted the likelihood of success across items. Item characteristic variables and interactions terms between item characteristics were added in subsequent models. Overall, the analyses suggest that the word reading test most demands phonological ability and phonetics knowledge, particularly feedbackward phonetics. Results also show that task demands are significantly moderated by the linguistic parameters required as part of the test design. Limitations of the study are discussed and suggestions for test optimization are given.


© 2022, Michael Eason