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,…

CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…

This paper presents the R Analyzer for Large-Scale Assessments (RALSA), a newly developed R package for analyzing data from studies using complex sampling and assessment designs. Such studies are, for example, the IEA's Trends in International Mathematics and Science Study and the OECD's Programme for International Student Assessment. The package…

This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…

This teaching brief explores how and why location analytics should be taught in business schools using three objectives. First, an explanation is provided for the importance of including location analytics in the standard business school curriculum--especially in the field of supply chain management. Second, a lack of GIS-based location analytics…

We briefly review the emergence of internet research ethics (IRE) since 2000 across three stages, showing how the last, IRE 3.0, focuses on ethical challenges and issues evoked by Big Data. We explore specific examples of IRE 3.0 as occasioned by requirements for informed consent -- including Big Data analyses of a closed Facebook group -- as…

Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors…

In the business environment, the goal of data analytics can be characterized as improving decision making and its links to big data and other data-driven technologies. In UK higher education, degree apprenticeships are business-led and government-supported nationally recognized qualifications, where delivery is tailored to partner employer…

In May of 2020, the Advanced Distributed Learning Initiative (ADL) and the Defense Acquisition University (DAU) partnered with USALearning/PowerTrain to create a practical application of ADL's 2019 TLA Reference Implementation. The purpose of this project was to recreate key components of the Reference Implementation with commercially-available,…

We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…

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…

In this article, we argue that the contributions of documentation studies can provide a useful framework for analyzing the datafication of students due to emerging learning analytics (LA) practices. Specifically, the concepts of individuals being 'made into' data and how that data is 'considered as' can help to frame vital questions concerning the…

Research students in social science disciplines frequently struggle to master statistical analysis. A contributing factor may be the statistical software that is used, as the design of such software may not address the needs of non-statisticians or non-computer programming students. Hence, decisions about which statistical software tools are most…

Corpus analysis methods have been widely employed in literary translation research by numerous scholars. However, their integration into literary translation training has yet to be developed. With the advancement of AI technology, this paper explores the potential of employing AI-enhanced corpus text analysis and text mining techniques in this…

This paper explores third-wave post-neoliberalism as an assemblage, fractured and dis/embodied, a mobile tool of governance articulated in various shapes across geopolitical sites. Post-neoliberalism is assembled alongside other key cultural shifts, such as post-truth, posthuman and the computational turn. In light of this Special Issue, this…