This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the…

Meta-analysts often encounter missing covariate values when estimating meta-regression models. In practice, ad hoc approaches involving data deletion have been widely used. The current study investigates the performance of different methods for handling missing covariates in meta-regression, including complete-case analysis (CCA), shifting-case…

The field of learning analytics has advanced from infancy stages into a more practical domain, where tangible solutions are being implemented. Nevertheless, the field has encountered numerous privacy and data protection issues that have garnered significant and growing attention. In this systematic review, four databases were searched concerning…

Sociologists increasingly face choices among competing algorithms that represent reasonable approaches to the same task, with little guidance in choosing among them. We develop a strategy that uses simulated data to identify the conditions under which different methods perform well and applies what is learned from the simulations to predict which…

Multistate models are often used in social research to analyze how individuals move between states. A typical application is the estimation of the lifetime spent in a certain state, like the lifetime spent in employment, or the lifetime spent in good health. Unfortunately, the estimation of such quantities is prone to several biases. In this…

Accompanied with the development of storage and processing capacity of modern technology, educational data increases sharply. It is difficult for educational researchers to derive useful information from much educational data. Therefore, educational data mining techniques are important for the development of modern education field. Recently,…

Accountability pressures in education have risen steadily over the last two decades and public schools and districts now track school- and student-level data in response to state and federal mandates. Catholic schools and dioceses have not faced the same level of regulation over this period, and less is known about data access and use in the…

Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility in meta-analysis, the transparency and reproducibility of the data extraction phase is still lagging behind. Unfortunately, there is…

State law requires that Ohio's superintendent of public instruction annually report on the status of implementation of special education and related services for children with disabilities. This includes the number of children identified with disabilities and the number of identified children receiving services. The Ohio Department of Education…

Moving Beyond the Ordinal Methodological Controversy: A Systematic Review (Manuscript 1): Ordinal outcome data is a common byproduct of education research. Yet more than seventy-five years after the development of Stevens' original measurement framework, the permissibility of select analytic techniques to ordinal outcome data remains a topic of…

Learning analytics are starting to become standardized in higher education as institutions use the techniques of Big Data analytics to make decisions to help them reach their goals. The widespread use of student information brings forth ethical concerns primarily in relation to privacy. While the overarching ethical issues related to learning…

Data science, as a discipline can be used in any area. However, in order to utilize data science techniques, data scientist must be taught domain knowledge, referred to as a partner discipline, in the area with which the techniques are to be utilized. Using a quantitative analysis of publicly available information and survey methodology, this…

Having access to accurate and reliable data is essential in decision-making. A wealth of data is spread across the University of Delaware (UD). These data include, but are not limited to, financial information, budget information, student enrollment, credit hours taught, and numerous metrics about faculty, staff, and sponsored programs. These data…

In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The…

Background: In educational settings, individuals are often best served by an intervention that is adapted over sequential stages to suit their initial and changing needs. The salience of an adaptive intervention is, perhaps, most clear in the classroom. Learning itself is a sequential process: mastering a given concept or technique frequently…