Data ethics have emerged as an essential topic in education. Educators must know how to use data effectively and responsibly. This is a complex and systemic issue that involves bringing awareness to all stakeholders, building human capacity, modifying policy, and considering equitable solutions to data use. This article posits an initial framework…

This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…

Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision-making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data-driven Intelligent Supervision Platforms in…

This paper introduces the concept of infrastructure into discussions on climate change and education. We focus on the links between the increased use of digital data and the central role of data infrastructures in education, and the energy infrastructure needed to support their growing use in schools and school systems. We elaborate a need for a…

The rapid development of online education has underscored the necessity of data-driven teaching functions for enhancing teaching quality and efficiency. This paper investigates the role of data-driven approaches in online education, with a particular focus on the practical application of data for evaluating learning outcomes. It highlights the…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

Instructional leadership is a complex dimension, which requires that principals possess expertise in goal setting, leading the instructional program, and creating the conditions for a successful school environment. Effective instructional leaders manage the instructional program by planning, coordinating, and evaluating the work of teachers and…

Accelerating advancements in learning analytics and artificial intelligence (AI) offers unprecedented opportunities for improving educational experiences. Without including students' perspectives, however, there is a potential for these advancements to inadvertently marginalize or harm the very individuals these technologies aim to support. This…

In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…

This work focuses on simulation, design, development, and evaluation of a visual Learning Analytics (LA) tool -- Real-time Educational AI-powered Classroom Tool (REACT) -- to support educators' data-driven decision-making. The educational institutions face one of the biggest challenges, such as predicting student performance, detecting undesirable…

This manuscript presents an exploratory mixed-methods case study examining the impact of artificial intelligence (AI) in the form of generative pretrained transformers (GPTs) and large language models on special education administrative practices in one school district in the Northeast United States. AI holds tremendous potential to positively…

The question: "What is an appropriate role for AI?" is the subject of much discussion and interest. Arguments about whether AI should be a "human replacing" technology or a "human assisting" technology frequently take centre stage. Education is no exception when it comes to questions about the role that AI should…

Educational analytics tend toward aggregation, asking what a "normative" learner does. In "The Left Hand of Data," educational researchers Matthew Berland and Antero Garcia start from a different assumption--that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should…

The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students' trends of activities towards success and risk and design intervention methods to improve learning performance and experience. However, many factors contribute to the challenge of designing and building effective…