Effectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management…

Massive online Open Courses (MOOCs) make extensive use of videos. Students interact with them by pausing, seeking forward or backward, replaying segments, etc. We can reasonably assume that students have different patterns of video interactions, but it remains hard to compare student video interactions. Some methods were developed, such as Markov…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

The purpose of this study was to evaluate the relationship of pre-entrance factors and the success of students in an Associate of Applied Science (A.A.S.) degree nursing program at a community college in East Tennessee. The criterion variable was success in the nursing program. Success was defined as academic success in all nursing courses and…

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,…

Background: Systematic reviewers often encounter incomplete or missing data, and the information desired may be difficult to obtain from a study author. Thus, systematic reviewers may have to resort to estimating data from figures with little or no raw data in a study's corresponding text or tables. Methods: We discuss a case study in which…