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.…

Purpose: This study aims to examine the absorptive capacity of an elementary school participating in a multi-year research-practice partnership (RPP) focused on increasing data science instruction through curriculum development. This research considers how data science initiatives might be sustained with fewer supports from the research team as…

Using research evidence to guide higher education policies and practice may help to promote rich learning experiences and long-term success for all students. This essay explores paths for research on the use of research evidence in higher education and proposes three considerations for researchers engaging in this work. First, to improve the…

Background/purpose: It revisits Partial Least Squares Structural Equation Modeling (PLS-SEM) as a robust tool for analyzing non-normal data and small samples, offering predictive modeling advantages. This study also compares the merits, practical applications, and added value of both tools in tackling complicated research issues, notably in…

Background/purpose: The current study aimed to investigate the extent to which collaborative educational applications based on connectivism theory are used to organize big data and their impact on university students' digital self-efficacy. Materials/methods: The researcher adopted a descriptive survey approach to examine the effectiveness of the…

This toolkit offers guidance on how to implement efficient, engaging, and effective enhanced outreach to students. It includes both messaging strategies and ways to analyze the results of outreach messaging to determine what is working and what is not. The guidance in this toolkit explains how to craft messages and analyze engagement data to…

Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students' academic achievement early using Educational Data Mining (EDM). This study aims to predict students' final grades and identify honorary students at…

To respond to the needs of digital transformation, universities must continue to play their role as proving ground for educating the future generation and innovation. The article is devoted to overview, discussion, and investigation of application in higher education of two modern information technologies: big data and internet of things. The…

Keystroke logs provide a comprehensive record of observable writing processes. Previous studies examining the keystroke logs of young L1 English writers performing experimental writing tasks have identified writing processes features predictive of the quality of responses. Contrarily, large-scale studies on the dynamic and temporal nature of L2…

The COVID epidemic has provided an excellent example of the need to call on a wide variety of statistical tools to address a global problem, and can give students insights into some of the dimensions of data science. Here, we describe some of the characteristics of data that students encounter as citizens. We set out some teaching ideas, which…

A shifting policy landscape in Australian teacher education has led to the introduction of teaching performance assessment tasks in initial teacher education degrees, foregrounding data literacy practices. The aim of this research was to explore pre-service teachers' uses of data to inform and evaluate their teaching practice as demonstrated in…

School closures in the wake of the COVID-19 pandemic led to kids asking pertinent questions about why they were not in school, especially some students suffering financial hardship. Virtual classrooms became the mundane venues for students to piece together the pandemic puzzle and unpack unseen inequities. This article examines disparities that…

Acting to dismantle structural racial inequities begins with identifying and clearly naming the challenges being faced. Data play a powerful role in this process. Several recent publications synthesize data sources, research findings, and expert recommendations to inform and guide equity improvement efforts. A five-part "Statement of the…

This paper describes a preliminary study of how computational methods allow us to know more about citizen science and its connection with education. Citizen science is a practice involving a general public in scientific tasks and generating knowledge and scientific results. Previous studies have shown that the education sector can take benefit of…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…