Most studies on the use of digital student data adopt an ethical framework derived from human-subject research, based on the informed consent of the experimental subject. However, consent gives universities little guidance on using learning analytics as a routine part of educational provision: which purposes are legitimate and which analyses…

Early Warning Systems (EWSs) aggregate multiple sources of data to provide timely information to stakeholders about students in need of academic support. There is an increasing need to incorporate relevant data about student behaviors into the algorithms underlying EWSs to improve predictors of students' success or failure. Many EWSs currently…

Background: The study explored the grief process of persons with intellectual and developmental disabilities (PWIDDs) as perceived by direct care workers (DCWs) and how such workers can guide and support PWIDDs experiencing grief. Materials and Methods: A thematic analysis approach was used to examine data from nine focus groups with 60 DCWs from…

Interest in the regression discontinuity (RD) design as an alternative to randomized control trials (RCTs) has grown in recent years. There is little practical guidance, however, on conditions that would lead to a successful RD evaluation or the utility of studies with underpowered RD designs. This article describes the use of RD design to…

The benefits of Big Data Analytics are cited frequently in the literature. However, the difficulties of implementing Big Data Analytics can limit the number of organizational projects. In this study, the authors evaluate business, procedural and technical factors in the implementation of Big Data Analytics, applying a methodology program. Focusing…

We demonstrate how the DEWIS e-Assessment system may use embedded R code to facilitate the assessment of students' ability to perform involved statistical analyses. The R code has been written to emulate SPSS output and thus the statistical results for each bespoke data set can be generated efficiently and accurately using standard R routines.…

Large quantities of data are now generated, collated and processed within schools through computerized systems and other digital technologies. In response to growing concerns over the efficiency and equity of how data is used, the concept of 'open data' has emerged as a potential means of democratizing data access and use across school…

The challenges of Big Data (BD) and Big Data Analytics (BDA) have attracted disproportionately less attention than the overwhelmingly espoused benefits and game-changing promises. While many studies have examined BD challenges across multiple industry verticals, very few have focused on the challenges of implementing BDA solutions. Fewer of these…

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

This short brief for education decision makers discusses three main factors that may contribute to a finding of no effects: failure of theory, failure of implementation, and failure of research design. It provides readers with questions to ask themselves to better understand "no effects" findings, and describes other contextual factors…

This research connects several data-driven educational data mining approaches to a framework for interaction developed in educational research. In particular, 10 million usage data points collected by a Learning Management System used by students and teachers in 450 online undergraduate courses were analyzed with this framework. A range of…

All research accounts are partial. Who we are--our biographies, experiences, ideological stances, and so on--affects the entirety of the research process. Who we are shapes what types of research questions we find interesting, how we frame our research objectives, how we collect data, how we analyze these data, and how we present our findings. In…

This work is a contribution to the usefulness of climate-related authentic material for pedagogical purposes in Higher Education. The two case studies had the aim of raising environmental awareness of a sustainable future among university students, while encouraging them to explore language use and draw their own conclusions and considerations…

One tool that many families own, across the globe, is a basic mobile phone. The use of low-cost basic mobile phones for educational purposes in humanitarian settings is critical where access to connectivity and higher cost devices is limited. The portability of mobile phones, combined with their communication features, offers multiple uses to…

Quantitative literacy is an essential twenty-first century skill that universities are heavily invested in teaching to students. The social sciences play an important role in these efforts because they attract students who might otherwise avoid data and mathematically oriented courses and because they ground quantitative reasoning in political and…