Institutional researchers use skills from their diverse backgrounds to collect, analyze and report data about their institutions to stakeholders representing various interests and levels of data literacy. However, there is little research into how these professionals process data and none into what aspects are important to institutional…

Psycholinguistics is the research of language in the mind: The architecture of storing the different components of language in our memory, and the ways we access that knowledge when processing and producing language. Psycholinguists usually conduct quantitative experimental research in which certain standards of experimental design, data…

This dissertation is composed of projects on three aspects of gathering and learning from data in the social sciences: drawing representative samples, taking valid measurement, and making warranted inductive inferences. Chapter one studies the challenge of drawing representative human samples. It is well documented that most samples used by…

The purpose of this study was to investigate the effectiveness of four different models (bifactor, CTC(M-1), CTCU and unidimensional) as to optimal model selection when the wording effect associated with negatively worded items was present. A Monte Carlo simulation study was conducted to compare model-data fit and accuracy in parameter estimates…

Purpose: The purpose of this dissertation is to investigate the feasibility of using tests of robustness in peer review. This study involved selecting three high-impact papers which featured open data and utilized bioinformatic analyses but provided no source code and refactoring these to allow external survey participants to swap tools,…

There has been extensive research into the underrepresentation of minoritized students in STEM disciplines since the 1990s with limited success in improving the representation of Black women in math-intensive STEM fields. This dissertation aims to address how the guiding tenets of critical quantitative (QuantCrit) methods work when used with…

This research explores the emerging field of data science from the scientometric, curricular, and altmetric perspectives and addresses the following six research questions: 1.What are the scientometric features of the data science field? 2.What are the contributing fields to the establishment of data science? 3.What are the major research areas of…

Scientific results are communicated visually in the literature through diagrams, visualizations, and photographs. In this thesis, we developed a figure processing pipeline to classify more than 8 million figures from PubMed Central into different figure types and study the resulting patterns of visual information as they relate to scholarly…

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)…

This paper is a research dissertation based on a qualitative case study conducted on Teachers' Experiences within a Data-Driven Decision Making (DDDM) process. The study site was a Title I elementary school in a large school district in Central Florida. Background information is given in relation to the need for research that was conducted on the…

Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS scores of 34 companies (clients) dealing with similar businesses in the US and Canada. With the given…

In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge. This dissertation centers on the issue of modeling the dynamics of user communities, trending…

The focus on measuring student growth based on teacher effectiveness has presented new challenges for an urban school in Massachusetts. The purpose of this general interpretive qualitative study was to examine the instructional practices of a group of middle school teachers, the practices they perceived to be effective for ensuring student…

This study considers how advising ePortfolios are uniquely situated to address a current challenge in the application of educational technologies: using the right tool for the right job for the right reason at the right time. The particular problem identified for investigation lies at the intersection of two central issues: first, in the age of…

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…