Classifier systems constitute one of the most prominent features of East and South-East Asian languages (Li, 2013). Classifiers categorize referent nouns based on salient semantic features such as humanness, animacy, shape, or others (Aikhenvald and Mihas, 2019). The work described in this dissertation constitutes a thorough quantitative…

The meaning of positive polar questions (PPQs) is relatively straightforward, so the truth conditions of PPQs can be decided easily. In contrast, the meaning of negative polar questions (NPQs) may vary, and simple yes-no answers to NPQs have seemingly unpredictable interpretations. For example, a simple yes answer to a PPQ like 'Did you have lunch…

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…

This dissertation examines the effectiveness of machine learning algorithms and feature engineering techniques for analyzing process data and predicting test performance. The study compares three classification approaches and identifies item-specific process features that are highly predictive of student performance. The findings suggest that…

This non-experimental causal-comparative study aims to explore the possible effect of expertise on learning experience design (LXD) deviation identification and the classification of these deviations in alignment with provided learning experience design constructs within a learning technology. Additionally, this study challenges Nielsen's (1993)…

This study was conducted to further research into the impact of student-group item parameter drift (SIPD) --referred to as subpopulation item parameter drift in previous research-- on ability estimates and proficiency classification accuracy when occurring in the discrimination parameter of a 2-PL item response theory (IRT) model. Using Monte…

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…

Vision classification tasks, a fundamental and transformative aspect of deep learning and computer vision, play a pivotal role in our ability to understand the visual world. Deep learning techniques have revolutionized the field, enabling unprecedented accuracy and efficiency in vision classification. However, deep learning models, especially…

The research in this dissertation consists of two parts: An active learning algorithm for hierarchical labels and an embedding-based retrieval algorithm. In the first part, we present a new approach for learning hierarchically decomposable concepts. The approach learns a high-level classifier (e.g., location vs. non-location) by separately…

This two-part dissertation centers on a re-examination of the role of book indexes in information retrieval research on full-text digital book collections in digital libraries. Early research focused on information retrieval and book indexes (in addition to other parts of books) in the 2000s when the Google Books corpus was first released to the…

The aim of this study was to examine the impact of academic digital archives on scholarship and university status. Digital archives have played roles in strengthening scholarly research and developing innovative fields of study. This is especially prevalent in the rise of digital humanities and making work available through digital libraries and…

This qualitative case study examined the complicated process that School Building Learning Communities (SBLCs) navigated in regard to the pre-referral process due to the pandemic. Rooted in the theories of John Dewey (2018) and Howard Gardner (1996), this research was conducted by way of interviews and a reflective journal of 12 educational…

Research on video activity detection has primarily focused on identifying well-defined human activities in short video segments. The majority of the research on video activity recognition is focused on the development of large parameter systems that require training on large video datasets. This dissertation develops a low-parameter, modular…

Since 2010, gamification, a concept and practice, gained attention in academic research. Results of its effectiveness were mixed and often lacked the use of grounded models or frameworks. Dichev et al. (2019b) proposed the existence of demotivational factors and highlighted two distinct sets of motivational drivers--one linked to game elements and…