Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg offers a comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events,…

This article looks back over the past two decades to describe how teaching of undergraduate marketing research has (or has not) changed. Sweeping changes in technology and society have certainly affected how marketing research is designed and implemented--but how has this affected teaching of this important topic? Although the purpose of marketing…

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…

Data-based decision-making is a well-established field of research in education. In particular, the potential of data use for addressing heterogeneous learning needs is emphasized. With data collected during the learning process of students, teachers gain insight into the performance, strengths, and weaknesses of their students and are potentially…

The digital era has significantly reshaped journalism, emphasizing the pivotal role of data-driven reporting. This review delves into the nexus of data journalism and journalism education, investigating dominant study characteristics, challenges, and gaps for future research. Examining 41 relevant articles through the Arksey and O'Malley…

This paper explores an emerging methodological approach called doppelganger as method. This method uses the idea of a doppelganger or double to explore the social world. It is specifically used to examine datafication, or the increase in the production and use of data and its impact on education. Doppelganger as method begins by locating doubles,…

With the development of the information age, the quality of physical education teaching in universities has become an important goal of teaching reform. Improving the quality of physical education and significantly improving students' physical fitness is one of the development goals of higher education. Therefore, this article proposes an…

Students' emotions in the classroom are highly dynamic and thus typically strongly vary from one moment to the next. Methodologies like experience sampling and daily diaries have been increasingly used to capture these momentary emotional states and its fluctuations. A recurring question is to what extent aggregated state ratings of emotions over…

While violence against children (VAC) has been a long-established global concern, more recently attention has been drawn to how violence occurs in and around schools (VACS) and the role of education in preventing and responding to violence. Whilst awareness about VACS is growing, more robust data are needed to inform policy and practice. Concerns…

In this article, we discuss the methodological implications of data and theory integration for Theory-Based Evaluation (TBE). TBE is a family of approaches to program evaluation that use program theories as instruments to answer questions about whether, how, and why a program works. Some of the groundwork about TBE has expressed the idea that a…

Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, accelerating the review process, and enhancing the quality and reliability of extracted data. In this…

This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…

Meta-analyses have become the gold standard for synthesizing evidence from multiple clinical trials, and they are especially useful when outcomes are rare or adverse since individual trials often lack sufficient power to detect a treatment effect. However, when zero events are observed in one or both treatment arms in a trial, commonly used…

Graph neural networks (GNN) are vital for analyzing real-world problems (e.g., network analysis, drug interaction, electronic design automation, e-commerce) that use graph models. However, efficient GNN acceleration faces with multiple challenges related to high and variable sparsity of input feature vectors, power-law degree distribution in the…

The purpose of this invited paper is to show the learning disabilities field what LDbase is, why it's important for the field, what it offers the field, and examples of how you can leverage LDbase in your own work.