The increasing demand for privacy-preserving, ethically aligned synthetic data generation in education has highlighted the limitations of existing tabular data generators. Traditional approaches often sacrifice fairness or privacy in pursuit of predictive accuracy, rendering them unsuitable for high-stakes academic settings. In this paper, we…

Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

Author Jason Williams develops a framework that balances data-based decision making with a deep consideration for addressing students' unique needs to foster improved learning outcomes. Focusing on five qualities integral to a healthy data culture, Williams offers educators a simple, reliable way to assess and reconsider their data practices to…

Purpose: This study aims to analyze the platforming scenario at a Brazilian university as well as the data security process for students and professors. Design/methodology/approach: This research brings an analysis through a qualitative approach of the platformization process in a Brazilian teaching institution. Findings: The results point to a…

A major pre-award administrative challenge research universities face is turnaround time for generation of high-quality NIH Data Training Tables for NIH training grants (e.g., T32, K12, TL1, KL2, R25s) which are required for training grant submission proposals to the National Institutes of Health (NIH). Universities with dedicated training grant…

This study focuses on describing data based school management processes in Türkiye, Spain and Romania. The study group consists of 49 participants. Maximal variation and stratified sampling were applied. For internal trustworthiness, respondent validation, data triangulation and cross check were utilized. For transferability, 'expert opinions' and…

The Nebraska Statewide Workforce & Educational Reporting System (NSWERS) is a state longitudinal data system (SLDS) that coordinates data sharing, processing, and dissemination efforts across the Nebraska public school systems, Nebraska community colleges, the University of Nebraska system, the Nebraska Department of Labor, and other statewide…

In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…

Purpose: In light of a need for more critical education about datafication, this paper aims to develop a framework for critical datafication literacy that is grounded in theoretical and empirical research. The framework draws upon existing critical data literacies, an in-depth analysis of three well-established educational approaches - media…

Substantial shares of eligible students forgo or lose access to tuition-free college benefits, in part due to limited access to information on eligibility and other requirements. Given students' dependence on the Internet for information on how to pay for college, we examine the availability and digital accessibility of critical program…

This work reports on the implementation of a self-contained data-literacy exercise designed for use in undergraduate classes to help students practice data literacy skills such as interpreting and evaluating evidence and assessing arguments based on data. The exercises use already developed data-visualizations to test and develop students' ability…

The methodological controversy surrounding ordinal outcome data has posed a distinct challenge to the conceptualization, design, and conduct of research in the social and behavioral sciences for more than 75 years. Accordingly, this study sought to supply a comprehensive and multidisciplinary perspective of the debate and in so doing lay the…

The research is a descriptive correlational study that investigates new methods for the creation of innovation for institutions. The research addresses the need for organizations to generate a novel form of innovation for their competitiveness and survival. These novel methods in the generation of innovation include using an organization's big…

As ideas from data science become more prevalent in secondary curricula, it is important to understand secondary teachers' content knowledge and reasoning about complex data structures and modern visualizations. The purpose of this case study is to explore how secondary teachers make sense of mappings between data and visualizations, especially…