This paper describes the construction and descriptive analysis of a data set of United States school shooting events. Three hundred forty-three shooting events are included, spanning 175 years of United States educational history. All levels of US educational institution are included. Events are included when a firearm is discharged, regardless of…

An alternative to null hypothesis significance testing is presented and discussed. This approach, referred to as observation-oriented modeling, is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. In terms of analysis, this novel approach complements traditional methods…

Predictive studies have been widely undertaken in the field of education to provide strategic information about the extensive set of processes related to teaching and learning, as well as about what variables predict certain educational outcomes, such as academic achievement or dropout. As in any other area, there is a set of standard techniques…

For the appraisal of single-case intervention data, school psychologists have been encouraged to focus most, if not all, of their interpretive weight on the visual inspection of graphed data. However, existing software programs provide practitioners with limited features for systematic visual inspection. R (R Development Core Team, 2014) is a…

The rise of learning analytics, the application of complex metrics developed to exploit the proliferation of "Big Data" in educational work, raises important moral questions about the nature of what is measurable in education. Teachers, schools and nations are increasingly held to account based on metrics, exacerbating the tendency for…

Augmented Graph Grammars are a graph-based rule formalism that supports rich relational structures. They can be used to represent complex social networks, chemical structures, and student-produced argument diagrams for automated analysis or grading. In prior work we have shown that Evolutionary Computation (EC) can be applied to induce…

Growth curve models are widely used for investigating growth and change phenomena. Many studies in social and behavioral sciences have demonstrated that data without any outlying observation are rather an exception, especially for data collected longitudinally. Ignoring the existence of outlying observations may lead to inaccurate or even…

Python is a popular, general purpose programming language that is gaining wide adoption in beginning programming courses. This paper describes the development and implementation of an introductory Python course at a business university open to students in a variety of majors and minors. Given the growing number of career opportunities in…

Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…

AACSB has now mandated that analytics be integrated into the undergraduate business curriculum. Given that the subject of statistics provides the underpinnings of the developing discipline of business analytics, this article focuses on effective course delivery aimed at enhancing the learning of introductory business statistics in the modern world…

Inspired by the 2017 Big Ten Academic Alliance Library Conference's collective collection theme, the authors undertook a study to better understand the consortium's resource-sharing needs for Spanish and Portuguese materials published in Latin America. The authors employed multiple technologies to expedite gathering, reconciling, and analyzing…

Reproducibility crises have arisen in psychology and other behavioral sciences, spurring efforts to ensure research findings are credible and replicable. Although reforms are occurring at professional levels in terms of new publication parameters and open science initiatives, the credibility and reproducibility of undergraduate research deserves…

Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this article, we review the recent automated text methods relevant to educational…

There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this…

Previous studies on educational data mining (EDM) acceptance were focused on antecedents that were adopted from various models and theories. However, the ways in which such antecedents became the most important tools for educational improvement have not been researched in detail. This study aims to identify the priority antecedents of EDM…