Multilevel modeling is commonly used with clustered data, and much emphasis has been placed specifically on the multilevel linear model (MLM). When modeling clustered ordinal data, a multilevel ordinal model with cumulative logit link assuming proportional odds (i.e., multilevel cumulative logit model) is typically used. Depending on the research…

All chemistry students must develop competency in analyzing and making sense of data. However, there are many difficulties that chemistry students may experience while analyzing data. Many students may not use relevant prior knowledge to aid in making sense of data, or they may not form conclusions using all the data provided. Additionally, prior…

Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American…

Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…

This study explored the core competencies, technological skills, functional proficiencies, and professional experiences of data scientists at higher education institutions. The specific population of interest was higher education administrators and staff professionals identified as data scientists. This study was informed by the following guiding…

The purpose of this research study was to examine the role of the senior student affairs officer (SSAO) in promoting assessment practice within the Division of Student Life at Randal University. A qualitative, single-case study research design was employed to conduct this study. The case for this investigation was the Vice President for Student…

There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of "non"-medication products, as well. However, data systems most…

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

This research explored the knowledge, skills, and strategies early childhood teachers possess related to implementing curriculum and authentic assessment. Research suggests that early educators rate their knowledge of curriculum and authentic assessment and their implementation of both as excellent. Despite these self-reported, high levels of…

As district- and school-level leaders face increasing pressure from federal, state, and local accountability mandates there has been increased dependence on using and analyzing student data to help improve student performance. While the reporting of disaggregated data by student subgroup confirms that achievement gaps exist, it does not provide…

Increasing demands for accountability from both the public and the government have resulted in increasing pressure for higher education professionals to use data to support their choices. There is significant speculation that professionals at all levels of education lack the knowledge to implement data-driven decision making. However, empirical…

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

The purpose of this study is to explore and describe the process of alliance creation and maintenance between U.S. institutions of higher education and enterprises in Hong Kong. The methodology is a qualitative case study in which administrators from U.S. universities offering programs in Hong Kong and administrators from organizations in Hong…

In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…

The study uses qualitative methodology to understand the "nature" of spiritual experiences that resemble self-realization or oneness, and the linguistic structures and representational knowledge used to comprehend and communicate such an experience. It draws upon Habermas' theory of communicative action to explain the nuances of communication as…