Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

This study examines accounting faculty perceptions of the alignment of the newly revised CPA exam with the evolving demands of the accountancy profession. Triggered by significant technological advancements and the CPA Evolution initiative, the exam now encompasses broader coverage of data analytics, information technology, and emerging…

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…

Educational dashboards are increasingly prevalent visualising technologies that display data from educational processes to help learners and educators track learning pathways, alert for deviations, and make interventions. This study contributes to critical studies on data visualisations in education by examining dashboards in higher distance…

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,…

Business analytics is an emerging and prominent tool in many industries seeking to exploit the advantages of data-driven decision making. Simultaneously, educational institutions are developing and delivering business analytics offerings to equip business professionals with the tools necessary to implement business analytics in modern businesses.…

The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…

"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…

Assessing student achievement over multiple years is complicated by students' memberships in shifting upper-level nesting structures. These structures are manifested in (1) annual matriculation to different classrooms and (2) mobility between schools. Failure to model these shifting upper-level nesting structures may bias the inferences…

Construction, one of the largest industries in the world, consistently underperforms and faces barriers in leveraging the full potential of applying analytics to sensor data due to a lack of a skilled workforce. The prospects for data-driven solutions to address emerging construction challenges and enhance performance across project life cycles…

Ensuring consistent and reliable scoring is paramount in education, especially in performance-based assessments. This study delves into the critical issue of marking consistency, focusing on speaking proficiency tests in English language learning, which often face greater reliability challenges. While existing literature has explored various…

Individual participant data meta-analyses (IPD-MAs) have several benefits over standard aggregate data meta-analyses, including the consideration of additional participants, follow-up time, and the joint consideration of study- and participant-level heterogeneity for improved diagnostic and prognostic model development and evaluation. However,…

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…