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…

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…

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…

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…

Assessing achievement is a complex task due to its dependence on multiple factors and the hierarchical structure of educational data, yet surveys like TIMSS offer valuable insights into its determining factors like students' mathematics anxiety. However, disregarding the nested structure of data and ignoring the assumptions of models causes poor…

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…

Introduction. Taxonomy is an effective mean of managing and accessing a large amount of digital information. Various techniques have been developed to generate taxonomy automatically. The purpose of this study is threefold: (i) review methods and approaches adopted during taxonomy generation, (ii) identify the factors influencing the choice of a…

On February 23, 2024, the U.S. Departments of Education and Labor (the Departments) published a final rule in the "Federal Register" (89 FR 13814) that defines the sixth performance indicator--effectiveness in serving employers--as "Retention with the Same Employer" in the second and fourth quarters following a participant's…

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…

This study investigated the influence of longhand (paper and pen), keyboard, and stylus note-taking on academic performance in college classes. Students attended mini-lectures and took notes using longhand, keyboard, or stylus. Students took quizzes after each mini-lecture and reported their engagement. Final course grades were recorded.…

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…

The increase in education data and advance in technology are bringing about enhanced teaching and learning methodology. The emerging field of Learning Analytics (LA) continues to seek ways to improve the different methods of gathering, analysing, managing and presenting learners' data with the sole aim of using it to improve the student learning…

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…

In a wide range of fields, professional practice is being transformed by the increasing influence of digital analytics: the massive volumes of big data, and software algorithms that are collecting, comparing and calculating that data to make predictions and even decisions. Researchers in a number of social sciences have been calling attention to…

As we design increasingly complex systems, we run up against fundamental limitations of human imagination. To support practice, it becomes essential to use authentic data and algorithms as design materials to augment designers' intuitions. Recent work has explored some dimensions of using data as a design material, suggesting the contours of a new…