Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…

When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…

We present a concrete situation where there is a difference between the theoretical security of a cipher and its limitations when implemented in practice. Specifically, when entering a PIN, smudges on the keypad substantially reduce its security. We show how the number of possible keys in the presence of the "smudge attack" can be…

Purpose: Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today's data-driven world. This study aims to explore how community college students evaluate their data literacy and further examine demographic and educational/career advancement disparities in their…

Retrospective confidence refers to the phenomenological experience of the level of certainty that retrieved information is, in fact, correct. Retrospective confidence judgments are examined across a range of sub-disciplines in psychology from perception to memory research, and in education and legal applications. This paper focuses on…

The economic significance of open research data is widely acknowledged, yet its quantification remains challenging. This paper presents an effective valuation instrument to help stakeholders understand and evaluate the economic benefits of open research data. By conducting a scoping review and prioritizing user engagement, this study introduces a…

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…

As visual cultures scholars have argued, visual expression and aesthetic artifacts largely comprise the modern world. This includes the production of the school as an institution. A critical approach to education therefore must reinscribe students with the ability to see what educational processes attempt to hide and to construct an understanding…

There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…

This dissertation documented how undergraduate students made sense of data in news media. The participants were 30 undergraduate students enrolled in a course called "Numbers and Social Justice." The study used argument analysis (Toulmin, 2003) and ethnographic methodology to examine students' written work in a naturalistic setting.…

The integration of Internet technology and the collaborative development of smart classrooms is an essential step for colleges and universities to advance English instruction reform. This study utilized data mining (DM) technology to analyze the learning process in college English smart classrooms. The results indicate that the DM algorithm used…

The majority of adolescents communicate via text-based messaging, particularly through WhatsApp, a widely used free communication application. Written content on WhatsApp has the methodological potential to provide rich qualitative interview data. This study compares data collected using text-based WhatsApp versus face-to-face interview…

Data donation is a novel approach to collecting digital trace data, where users are asked to download their retrospective data from a platform and share them with the researchers. Little is known about the willingness to donate data and the potential bias that may arise from nonparticipation. We conducted a study among over 900 German Facebook…

Computer-supported learning technologies are essential for conducting hands-on cybersecurity training. These technologies create environments that emulate a realistic IT infrastructure for the training. Within the environment, training participants use various software tools to perform offensive or defensive actions. Usage of these tools generates…

Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…