Date of Award
Fall 2023
Document Type
Open Access Dissertation
Department
Computer Science and Engineering
First Advisor
Jijun Tang
Abstract
In this work we discuss the design and development of the Carolina Automated Reading Evaluation (CARE), created to facilitate the finding of deficits in the reading ability of children from four to nine years of age. Designed to automate the process of screening for reading deficits, the CARE is an interactive computer-based tool that helps eliminate the need for one-on-one evaluations of pupils to detect dyslexia and other reading deficits and facilitates the creation of new reading tests within the platform. While other tests collect specific data points in order to determine whether a pupil has dyslexia, they typically focus on only a few metrics for diagnosis, such as handwriting analysis or eye tracking. The CARE collects data across up to 16 different subtests, each built to test proficiency in various reading skills. These skills include reading fluency, phoneme manipulation, sound blending, and many other essential skills for reading. This wide variety of measurements allows for a more focused intervention to be created for the pupil. The first chapter of this work recounts the design and development process for the CARE platform, describing the creation of the test development tools and the individual subtests. The second chapter focuses on using eye tracking to optimize the teacher facing user interface. Chapter three discusses the usage of reinforcement learning to create a Computerized Adaptive Test for the CARE.
Rights
© 2024, William Henry Hoskins
Recommended Citation
Hoskins, W. H.(2023). Computerized Psychological Testing: Designing and Developing an Efficient Test Suite Using HCI and Reinforcement Learning Techniques. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/7645