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…

Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…

This paper proposes a conceptual framework enabling the development and adoption of descriptive, diagnostic, predictive and recommendatory data analytics in teacher professional learning by harnessing some of the affordances of digital technologies to convert data into actionable insights. The paper argues for a technology-enhanced approach that…

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…

This exploratory qualitative study examined how instructional designers use data to make decisions during the instructional design process. Participants included full-time instructional designers (n = 9) who were involved in one or more phases of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) across different job sectors,…

Multi-lab projects are large scale collaborations between participating data collection sites that gather empirical evidence and (usually) analyze that evidence using meta-analyses. They are a valuable form of scientific collaboration, produce outstanding data sets and are a great resource for third-party researchers. Their data may be reanalyzed…

Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…

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…

To improve and facilitate the acquisition of learning outcomes, teachers often use innovative teaching methods such as gamification to keep students' attention and increase their motivation. In recent years, the use of educational data mining (EDM) methods to explore academic topics has increased. With the expansion of EDM, a gap in the literature…

The IPEDS Finance survey is a key resource for academic research, policy analysis, and efforts to improve transparency and accountability. However, the data from the survey can be difficult to use properly. This research note addresses a specific challenge: how to incorporate the $16 billion in revenues and expenditures reported annually within…

The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…

This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…

The purpose of this article is to offer both theoretical and practical support to evaluation professionals preparing to facilitate the utilization phase of evaluation with a program or organization team. The Systems Evaluation Protocol for Participatory Data Use (SEPPDU) presented here is rooted in a partnership approach to evaluation and is…

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…

Despite the increasing availability of data used to inform educational policies and practices, concerns persist regarding its quality and accessibility. This study surveys quality education data from Brazil, Colombia, and Peru and evaluates their alignment with the FAIR principles and availability to support academic analytics (AA) and learning…