The present study investigates the influence of multidimensionality on linking and equating in a unidimensional IRT. Two hypothetical multidimensional scenarios are explored under a nonequivalent group common-item equating design. The first scenario examines test forms designed to measure multiple constructs, while the second scenario examines a…

In many large-scale testing programs, examinees are frequently categorized into different performance levels. These classifications are then used to make high-stakes decisions about examinees in contexts such as in licensure, certification, and educational assessments. Numerous approaches to estimating the consistency and accuracy of this…

This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…

This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…

Student growth percentiles (SGPs) have become a common means to measure and report on student academic growth for state education accountability, and some states have adopted SGP cutscores as a means of classifying student growth into categories like "high/medium/low" growth. It has therefore become important to understand properties of…

The processes used in identifying/diagnosing specific learning disabilities (SLDs) vary across settings and classification systems. Moreover, the theoretically and mathematically derived identification models (i.e., discrepancy model) have thus far not demonstrated adequate reliability and validity. The present study explores the utility of…

The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…

Despite the increasing demand for diagnostic information, observed subscores have been often reported to lack adequate psychometric qualities such as reliability, distinctiveness, and validity. Therefore, several statistical techniques based on CTT and IRT frameworks have been proposed to improve the quality of subscores. More recently, DCM has…

The purpose of the present study was to compare the classification accuracy of a previous year's end-of-year state assessment, a computer-adaptive diagnostic assessment (i-Ready), and the combination of the previous year's end-of-year state assessment with the following year's "i-Ready" performance to predict the rate of students passing…

When we read, errors in oculomotor programming can cause the eyes to land and fixate on different words from what the mind intended. Previous work suggests that these "mislocated fixations" form 10-30% of first-pass fixations in reading eye movement data, which presents theoretical and analytic issues for eyetracking-while-reading…

This dissertation investigates how parametric variation of linguistic properties leads to similarities and differences in language processing across the levels of words, grammatical features, and sentences. For a truly generalizable theory of psycholinguistics, the languages surveyed should not be constrained to English (Garnham, 1994; Norcliffe…

Early childhood traumatic experiences place children at-risk for social, emotional, and behavioral impairments that contribute to poor educational outcomes. There is an increasing awareness that children with early traumatic exposure may need supplemental supports for academic success. These supports may be presented in the form of…

Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

Reading comprehension can be analyzed from three points of view: Semantics, Assessment, and Cognition. Here, Semantics refers to the task of identifying discourse relations in text. Assessment involves utilizing these relations to obtain meaningful question-answer pairs. Cognition means categorizing questions according to their difficulty or…

Items in the mental lexicon have three storage and processing strata, the concept, lemma, and lexeme, which equate to semantic, syntactic and phonological information. Lexical items relate to each other at each stratum. Bilingual lexicons, which contain items from all languages, may contain cognates, items sharing concepts and with overlapping…