This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

The increasing rate of permanent school closures in U.S. public school districts presents unprecedented challenges for administrators and communities alike. This study develops an early-warning indicator model to predict mass closure events -- defined as a district closing at least 10% of its schools -- five years in advance. Leveraging…

Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…

The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…

Purpose: The main objective of the paper is to develop an investment model using data envelopment analysis (DEA) that provides a decision-making framework to allocate resources efficiently, such that the relative efficiency is improved within an available investment budget. Design/methodology/approach: Firstly, DEA models are used to evaluate the…

Those asked to make valid decisions with data don't have the technical knowledge to understand nuance around data quality, assessment aims, and statistical limitations that influence how they should interpret the data. This reality is what Greg Thompson, Leslie Rutkowski, and David Rutkowski call the validity paradox. Educators can surmount this…

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…

Data-based decision-making has been a frequently used policy and practice intervention used in schools to help inform the decision-making processes of educational practitioners, with the aim of improving student outcomes. Interim benchmark assessments are designed by commercial test developers to support educators in this framework. In fact, the…

Traditional functional budgets are useful for planning under predictable business environments. However, due to increased competition, changes in technology, consumer attitudes, and economic factors affecting supply chains, accountants must understand the characteristics of risk and uncertainty. Additionally, businesses now have access to…

Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision-making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data-driven Intelligent Supervision Platforms in…

We discuss our experience in teaching data analytics, and in particular prescriptive analytics, to students in business schools using an inter-coherent case study, where a managerial decision is decomposed into a series of research problems with interlocking analyses and the outcome of one analysis is the input of other analysis. Students who…

Only weeks into its new term, the Trump administration has taken steps to lay off federally funded education research staff, cancel nearly $1 billion in contracts and dismantle the U.S. Department of Education. These moves have upended evaluations of federally funded education programs and threatened access to massive data sets that states,…

"Best Practices in School Psychology" is one of the most influential books in school psychology history. Originally published in 1985 by Thomas and Grimes, it was the first book offered by the National Association of School Psychologists. Its six editions have been revised every 5-8 years. Utilizing Publish or Perish as well as…

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…

Single-case design is a research methodology that entails repeated measurement to assess the influence of an independent variable on a dependent variable over time. Data collected in this manner are regularly analyzed using visual analysis of data displayed in a linear graph. Although there is agreement regarding critical elements of visual…