It is important for policymakers and managers of higher education institutions knowing how well their universities are operating. This article aimed to show that data envelopment analysis (DEA) can be an excellent benchmarking instrument in higher education. First, by using several inputs and outputs at the institutional level, DEA can identify…

This article is the third installment in a series regarding the conduct, dissemination, and consumption of large-scale secondary research. See Part 1 on conducting secondary analysis (Sullivan et al., 2020) (EJ1239445) and Part 2 on practitioners' use of this research (Kulkarni et al., 2020) (EJ1248185). The purpose in this final installment is to…

States' commitments to tackling long standing inequities have been stifled by missing data, long delays, insufficient data-analysis tools, and the excessive reporting burden placed on states and institutions. If states hope to achieve their completion and equity goals, they need access to data that does not leave them guessing--so they can…

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…

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…