Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…

Searching for trials is a key task in systematic reviews and a focus of automation. Previous approaches required knowing examples of relevant trials in advance, and most methods are focused on published trial articles. To complement existing tools, we compared methods for finding relevant trial registrations given a International Prospective…

Organizational management is very important in running an efficient business and keeping up with the modern era. The purpose of this article is to present organizational problems, challenges, and key successes factor for an organization's performance. The first phase of the paper presents the problems seen in organizations, such as corporate…

This project aims to gain insight into the mechanisms by which schools in highly challenging environments avoided learning loss--or even improved--during the pandemic. Using a unique dataset covering multiple levels of school, health, and environmental data, we examine which factors led schools to 'beat the odds' when it comes to learning…

This article provides a systematic literature review about nonprofit and for-profit organizations using "big data" to inform performance improvement initiatives. The review of literature resulted in 4 peer-reviewed articles and an additional 33 studies covering the topic for these contexts. The review found that big data and analytics…

One of the essential problems, in educational data mining, is to predict students' performance on future learning materials, such as problems, assignments, and quizzes. Pioneer algorithms for predicting student performance mostly rely on two sources of information: students' past performance, and learning materials' domain knowledge model. The…

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…

Recent years have witnessed a growing demand for business analytics-oriented curricula. This paper presents the implementation of an introductory Python course at a business university and the attempt to elevate the course's relevance by introducing data analytics topics. The results from a survey of 64 undergraduate students of the course are…

Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…

Policymakers and professional educators attempt to be good stewards of public funds while simultaneously raising expectations for student outcomes that reflect academic excellence in the public school system. The purpose of this study was to determine the efficiency of Texas public school districts and the factors influencing the inefficiency of…

This article estimates the effects of school expenditure on school performance in government secondary schools in New South Wales, Australia over the period 2006-2010. It uses dynamic panel analysis to exploit time series data on individual schools that only recently has become available. We find a significant but small effect of expenditure on…

Thanks to extraordinary and exponential improvements in data storage and computing capacities, it is now possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago. As the world has developed this remarkable capacity to store and analyze data, so have the world's governments…

Performance-based scholarships have two main goals: (1) to give students more money for college; and (2) to provide incentives for academic progress. MDRC launched the Performance-Based Scholarship (PBS) Demonstration in 2008 to evaluate the effectiveness of these scholarships in a diverse set of states, institutions, and low-income student…

This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning…

This article examines how knowledge transfer (KT) indicators affect analyses on efficiency in the Higher Education sector, taking into account the characteristics of the Higher Education Institutions (HEIs). After revising the concept of third mission as a field for data development and its importance in assessing university performance, we…