Recurrent event data arise frequently in various fields such as biomedical sciences, public health, engineering, and social sciences. In many instances, the observation of the recurrent event process can be stopped by the occurrence of a correlated failure event, such as treatment failure and death. In this article, we propose a joint scale-change…

This study presents a systematic review of the literature on the predicting student retention in higher education through machine learning algorithms based on measures such as dropout risk, attrition risk, and completion risk. A systematic review methodology was employed comprised of review protocol, requirements for study selection, and analysis…

Background: Data-driven investigations of how students transit pages in digital reading tasks and how much time they spend on each transition allow mapping sequences of navigation behaviours into students' navigation reading strategies. Objectives: The purpose of this study is threefold: (1) to identify students' navigation patterns in…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Grade retention, the practice of holding a student back in the same grade, has been a controversial topic in the United States for decades. English learners, a growing population in US schools, are consistently identified for grade retention more often than their English-only counterparts. The purpose of this study is to test the impact of grade…

Purpose: A faculty development program (FDP) introduced postsecondary instructors to a module focused on the food-energy-water (FEW) nexus, a socio-hydrologic issue (SHI) and a sustainability challenge. This study aims to examine factors influencing faculty interest in adopting the instructional resources and faculty experience with the FDP,…

This paper describes the integration of geographic information system (GIS) technology in a high school environmental science classroom, specifically examining the impact of GIS technology on student engagement, critical thinking, and interdisciplinary learning for Education for Sustainability (EfS). This environmental science classroom utilized…

The dataset includes data from 1699 higher education students from two Slovenian universities. Among those participants were also 56 students with special educational needs (SEN). Students were enrolled in all study fields and levels. The study aimed to measure the use of online learning resources (OLRs) among higher education students and…

In the second edition of "Data-Driven Dialogue: A Facilitator's Guide to Collaborative Inquiry," authors Bruce Wellman and Laura Lipton provide strategies that transform school culture through data-driven inquiry. By applying a three-phase model and a host of process tools to facilitate collaborative data analysis, K-12 school and…

This paper outlines the journey of one Scottish primary school in taking nurturing approaches forward over a 5-year period, with the aims of improving staff understanding of their role and feeling skilled in using nurturing approaches and improving pupil's health and well-being and confidence. Using an action research methodology and the local…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

Process mining methodologies are designed to uncover underlying business processes, deviations from them, and in general, usage patterns. One of the key limitations of these methodologies is that they struggle in cases in which there is no structured process, or when a process can be performed in many ways. Learning Management Systems are a…

Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…

Predicting the students' performance has become a challenging task due to the increasing amount of data in educational systems. In keeping with this, identifying the factors affecting the students' performance in higher education, especially by using predictive data mining techniques, is still in short supply. This field of research is usually…

Data--their collection, analysis and use--have always been part of education, used to inform policy, strategy, operations, resource allocation, and, in the past, teaching and learning. Recently, with the emergence of learning analytics, the collection, measurement, analysis and use of student data have become an increasingly important research…