Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…

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,…

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…

When we imagine the work of a data analyst, we often picture meaningful data analysis and beautiful data visualizations. Although that is an exciting part of the job, data analysts actually spend the majority of their time acquiring, cleaning, and preparing data for analysis. This teaching case guides students through some of the most common data…

Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…

Undergraduate economics programs prepare students for future careers by developing competency working with data, or "data literacy." Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded…

While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…

The underrepresentation and underperformance of low-income, first-generation, gender minoritized, Black, Latine, and Indigenous students in Science, Technology, Engineering, and Mathematics (STEM) occurs for a variety of reasons, including, that students in these groups experience opportunity gaps in STEM classes. A critical approach to disrupting…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…

Students with disabilities represent 15% of U.S. public school students. Individualized Education Programs (IEPs) inform how students with disabilities experience education. Very little is known about the aspects of IEPs as they are historically paper-based forms. In this study, we develop a coding taxonomy to categorize IEP goals into 10 subjects…

Researchers in the education sciences, like those in other disciplines, are increasingly encountering requirements and incentives to make the data supporting empirical research available to others. However, the process of preparing and sharing research data can be daunting. The present article aims to support researchers who are beginning to think…

Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…

The National Center for Education Statistics (NCES) sponsors the National Teacher and Principal Survey (NTPS) on behalf of the U.S. Department of Education in order to collect data on public and private schools, principals, and teachers in the United States. The U.S. Census Bureau conducts the survey for NCES. The NTPS provides data on the…

The purpose of this descriptive research study was to evaluate the web-based practice experience tracking system at a school of public health (SPH) at a large southeastern university. Applied practice experiences (APEs) are a key component of public health education, and schools and programs of public health in the United States must provide…