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Mark L. Davison; David J. Weiss; Joseph N. DeWeese; Ozge Ersan; Gina Biancarosa; Patrick C. Kennedy – Journal of Educational and Behavioral Statistics, 2023
A tree model for diagnostic educational testing is described along with Monte Carlo simulations designed to evaluate measurement accuracy based on the model. The model is implemented in an assessment of inferential reading comprehension, the Multiple-Choice Online Causal Comprehension Assessment (MOCCA), through a sequential, multidimensional,…
Descriptors: Cognitive Processes, Diagnostic Tests, Measurement, Accuracy
Ben Seipel; Patrick C. Kennedy; Sarah E. Carlson; Virginia Clinton-Lisell; Mark L. Davison – Journal of Learning Disabilities, 2023
As access to higher education increases, it is important to monitor students with special needs to facilitate the provision of appropriate resources and support. Although metrics such as the "reading readiness" ACT (formerly American College Testing) of provide insight into how many students may need such resources, they do not specify…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Reading Tests, Reading Comprehension
Ben Seipel; Patrick C. Kennedy; Sarah E. Carlson; Virginia Clinton-Lisell; Mark L. Davison – Grantee Submission, 2022
As access to higher education increases, it is important to monitor students with special needs to facilitate the provision of appropriate resources and support. Although metrics such as ACT's (formerly American College Testing) "reading readiness" provide insight into how many students may need such resources, they do not specify…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Reading Tests, Reading Comprehension
Virginia Clinton-Lisell; Terrill Taylor; Sarah E. Carlson; Mark L. Davison; Ben Seipel – Grantee Submission, 2022
Standardized reading assessments are often used as an admissions criterion for college admittance, however, the relationship and predictive validity of reading assessments to academic achievement remains in question. Through a quantitative review of the literature, we conducted a meta-analysis to examine how well performance on college reading…
Descriptors: Reading Achievement, Reading Comprehension, Reading Tests, Academic Achievement
Virginia Clinton-Lisell; Terrill Taylor; Sarah E. Carlson; Mark L. Davison; Ben Seipel – Journal of College Reading and Learning, 2022
Reading comprehension assessments are used for postsecondary course placement and advising, and they are components of college entrance exams. Therefore, a quantitative understanding of the relationship between reading comprehension assessments and postsecondary academic achievement is needed. To address this need, we conducted a meta-analysis to…
Descriptors: Reading Achievement, Reading Comprehension, Reading Tests, Academic Achievement
Ben Seipel; Sarah E. Carlson; Virginia Clinton-Lisell; Mark L. Davison; Patrick C. Kennedy – Grantee Submission, 2022
Originally designed for students in Grades 3 through 5, MOCCA (formerly the Multiple-choice Online Causal Comprehension Assessment), identifies students who struggle with comprehension, and helps uncover why they struggle. There are many reasons why students might not comprehend what they read. They may struggle with decoding, or reading words…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Diagnostic Tests, Reading Tests
Mark L. Davison; David J. Weiss; Ozge Ersan; Joseph N. DeWeese; Gina Biancarosa; Patrick C. Kennedy – Grantee Submission, 2021
MOCCA is an online assessment of inferential reading comprehension for students in 3rd through 6th grades. It can be used to identify good readers and, for struggling readers, identify those who overly rely on either a Paraphrasing process or an Elaborating process when their comprehension is incorrect. Here a propensity to over-rely on…
Descriptors: Reading Tests, Computer Assisted Testing, Reading Comprehension, Elementary School Students