Modern life is increasingly influenced by networks, making cybersecurity a crucial area of study. However, due to their few resources and varied makeup, they are more vulnerable to a wide range of cyber-attacks. Such risks result in sensitive information being stolen as well as financial and reputational harm to firms. How far malicious detection…

Data are storied, often with rich histories and powerful stories to tell, yet often presented in a format that belies these stories. The arts can help put the body back into seemingly disembodied data. Arts-based approaches can help students embrace the storied nature of data and leverage the power of stories to affect change. Rahul Bhargava et…

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…

Effective undergraduate statistical education requires training using real-world data. Textbook datasets seldom match the complexities and messiness of real-world data and finding these datasets can be challenging for educators. Consulting and industrial datasets often have nondisclosure agreements. Academic datasets often require subject area…

There is wide agreement that ethical considerations are a valuable aspect of a data science curriculum, and to that end, many data science programs offer courses in data science ethics. There are not always, however, explicit connections between data science ethics and the centuries-old work on ethics within the discipline of philosophy. Here, we…

The advent of Career Enrolment Data (CED) in Higher Education is an important development for graduate employability practitioners and other stakeholders seeking to understand, analyse and enhance students' career readiness. CED, collected annually from all students in participating universities, requires students to self-report on their own…

This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…

Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…

Objective: This paper describes several automation tools and software that can be considered during evidence synthesis projects and provides guidance for their integration in the conduct of scoping reviews. Study Design and Setting: The guidance presented in this work is adapted from the results of a scoping review and consultations with the JBI…

Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…

The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…

Based on the sociocultural theory of learning and distributed cognition, using learning aids should benefit students' performance, as learning aids can compensate for a lack of knowledge or skills and reduce strain on short-term memory. The present study investigated the use of a diverse set of learning aids in Grade 8 of vocational education in…