Educational research outcomes frequently rely on an assumption that measurement metrics have interval-level properties. While most investigators know enough to be suspicious of interval-level claims, and in some cases even question their findings given such doubts, there is a lack of understanding regarding the measurement conditions that create…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

This dissertation developed a new learner corpus of Japanese and introduced an error and linguistic annotation scheme specifically designed for Japanese particles. The corpus contains texts written by learners who are in the first year to fourth year university level Japanese courses. The texts in the corpus were tagged with part-of-speech and…

This dissertation is aimed at investigating the impact of missing data and evaluating the performance of five selected methods for handling missing responses in the implementation of Cognitive Diagnostic Models (CDMs). The five methods are: a) treating missing data as incorrect (IN), b) person mean imputation (PM), c) two-way imputation (TW), d)…

The development in information science has enabled an explosive growth of data, which attracts more and more researchers to engage in the field of big data analytics. Noticeably, in many real-world applications, large amounts of data are imbalanced data since the events of interests occur infrequently. Classification of imbalanced data is an…

With the increase in frequency of the use of mixed methods, both in research publications and in externally funded grants there are increasing calls for a set of standards to assess the quality of mixed methods research. The purpose of this mixed methods study was to conduct a multi-phase analysis to create a preliminary rubric to evaluate mixed…

The performance of information retrieval systems varies significantly by test topics. Even for those systems that have performed well on average, the results for some difficult topics are still poor. Previous studies have revealed that different optimization techniques should be used for those difficult topics. However, a prerequisite of the…

Models, created using different modeling techniques, usually serve different purposes and provide unique insights. While each modeling technique might be capable of answering specific questions, complex problems require multiple models interoperating to complement/supplement each other; we call this Multi-Modeling. To address the syntactic and…

Numerous ways to meta-analyze single-case data have been proposed in the literature, however, consensus on the most appropriate method has not been reached. One method that has been proposed involves multilevel modeling. This study used Monte Carlo methods to examine the appropriateness of Van den Noortgate and Onghena's (2008) raw data multilevel…

Wayfinding is a kind of spatial riddle that people encounter almost daily. Although it has been well documented that wayfinding elements--namely, environmental cues, people and time--significantly influence wayfinding, there has been little work done to examine the effectiveness of those influences. In particular, the notion of wayfindingly…

Professional school counselors' leadership capacity may well play a pivotal role in educational reform in the twenty-first century. Crucial to the success of this vision, supported by the American School Counseling Association, is the perspective of system-level supervisors of school counselors. This exploratory qualitative study employed in-depth…