In Single-Case Designs (SCD), the outcome variable most commonly involves some form of count data. However, statistical analyses and associated effect size (ES) calculations for count outcomes have only recently been proposed. Three recently proposed ES methods for count data are: Nonlinear Bayesian effect size (Rindskopf, 2014), Log Response…

As social, racial, and environmental justice topics dominate national conversations, STEM teachers must provide learning opportunities that support students to make sense of these problems and co-construct hope for their futures (Calabrese-Barton et al., 2020; Ojala, 2012). Thinking about how teachers can begin to transform their classrooms into…

To analyze educational outcomes or evaluate operations, academic institutions need to produce high-quality data. Unfortunately, many institutions do not have accurate, timely, and useful data and information despite investments to manage technology. Furthermore, data management issues in education, including access, quality, and ownership, inhibit…

Public higher education in the United States (US) is funded through two primary forms: one is through state higher education appropriation funds, and the other is student financial aid that is directly given to students. Increasing postsecondary full-time equivalent (FTE) enrollment and graduation rate are becoming a crucial economic priority in…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

This dissertation discusses the relationship between teacher sensemaking, attributions, and instructional adjustments prompted in response to student performance data. Through this qualitative observation study, this paper explores the varying perspectives of teachers, including their level of assessment literacy, and the dynamics of their…

This dissertation intends to inform self-assessment and data collection practices within Rutgers University and act upon the encouragement of university leadership to advance the potential of the public service mission. These goals are accomplished by exploring relevant questions to inform the practices of institutional research (IR) and…

In 2018, the United States Congress passed the "Strengthening of Career and Technical Education for the 21st Century Act." This legislation included the requirement to conduct a comprehensive local needs assessment, which must include input from community stakeholders. This project designed and evaluated a three-step process that…

Public school districts are frequently targeted by cybercriminals to gain access to a wealth of under-protected sensitive data. As a result, information technology (IT) leaders in public school districts must implement measures to maintain the security and confidentiality of sensitive data collected and stored by their schools. This qualitative…

This study examines administrator perceptions of Pennsylvania's state assessment data. This study had three main purposes. The first purpose was to investigate the value and utility of state assessment data to inform decision making and the possibility of improving student achievement through the routine use of state assessment data. The second…

This dissertation will address the questions: In what ways can MBR theory be applied to design training that will improve the capacity of Citizen scientists to collect and analyze high quality scientific data?; To what degree does this training impact their ability to formulate complex understandings of environmental problems in their Citizen? The…

There is growing consensus that data-informed decision-making through human-centered inquiry and design process results in improved outcomes for designed artifacts. Among the latest trends is a group of tools and processes loosely assimilated under the umbrella term, "design thinking." These "designerly ways of knowing" are…

Digitally-based assessments create opportunities for collecting moment to moment information about how students are responding to assessment items. This information, called log or process data, has long been regarded as a vast and valuable source of data about student performance. Despite repeated assurances of its vastness and value, process data…

Higher education institutions in the United States face an urgent need to use evidence of their students' outcomes to inform improvements and increase educational attainment. Data about student outcomes are abundant and professionals who interpret and report the data are commonplace today. Yet, the higher education landscape continues to be…

My dissertation comprises three studies designed to explore nuances of data use in education that presently confound the relationship between variation in teachers' practice of data use and student outcomes: (1) the relationships between different data sources within and across instructional practices; (2) the dimensionality of teachers' practice…