This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

Supervision models are fundamental to our supervision practices and criticized for lacking empirical support. As a data-driven approach based on research with expert supervisors, Cohesive Model of Supervision unifies existing models' central premises in a meaningful manner and emphasizes the understated areas of supervision practice.

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…

As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…

The interest in Data Envelopment Analysis (DEA) has grown since its first put forward in 1978. In response to the overwhelming interest, systematic literature reviews, as well as bibliometric studies, have been performed in describing the state-of-the-art and offering quantitative outlines with regard to the high-impact papers on global…

The education faculty aims to assess departmental effectiveness by analyzing the relationship between service levels, output variables, and input variables. This objective is coupled with the formulation of faculty development strategies tailored to enhance efficiency while accommodating individual professionals' unique requirements and…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…

The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…

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…

The focus of this study was derived from staggering attrition rates that it calls centers year over year. At times call centers post-COVID-19 pandemic saw attrition rates fluctuating between 30%-50%. With any job there are challenges that are faced. These attrition rates stand 28%-40% higher than the United States 2023 national attrition rates of…

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…

Performance-based funding policies for postsecondary institutions have been enacted throughout the United States as an answer to reductions in public funding and increased accountability mandates. Institutional effectiveness, as demonstrated through metrics such as graduation and retention rates, dictates the level of funding received. Educational…

This paper reports on teachers developing their own data literacy and then acting as data coaches for colleagues in their schools. The 13 teachers from 7 schools in the study analysed standardised data using a data conversation protocol to identify students with significant mathematical misconceptions. They then took data-informed action with…

We present data from the Schools and Staffing Survey and the National Teacher and Principal Survey to document the prevalence of instructional coaching programs (ICPs) and consider how ICPs are distributed by school level, urbanicity, new teachers in a school, student enrollment, school poverty levels, student achievement levels, and state. We…