Missing data are common with large scale assessments (LSAs). A typical approach to handling missing data with LSAs is the use of listwise deletion, despite decades of research showing that approach can be a suboptimal strategy resulting in biased estimates. In order to help researchers account for missing data, we provide a tutorial using R and…

Personalized assessments are of increasing interest because of their potential to lead to more equitable decisions about the examinees. However, one obstacle to the widespread use of personalized assessments is the lack of a measurement toolkit that can be used to analyze data from these assessments. This article takes one step toward building…

Often, eye-tracking researchers define areas of interest (AOIs) to analyze eye-tracking data. Although AOIs can be defined with systematic methods, researchers in organic chemistry education eye-tracking research often define them manually, as the semantic composition of the stimulus must be considered. Still, defining appropriate AOIs during data…

The development of research methodology in any scientific field is closely tied to technological advancements that allow for deeper and more sophisticated data analysis. To help readers understanding the scope of current lexical availability research, this chapter provides a description of the tools and research resources specifically developed…

The COVID-19 pandemic uniquely affected nearly all the subject matter in a typical principles of macroeconomics class. Fluctuations in the basic macroeconomic data in the COVID era were staggering and offer new teaching opportunities. In addition, because the recession was primarily driven by supply side shocks, the entire episode offers a unique…

Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of…

The practice of statistics has the power to motivate and support learning across the STEM (Science, Technology, Engineering, and Mathematics) disciplines. When connected with meaningful science contexts, statistical problem solving through the collection of data and subsequent data analysis, supported by contemporary graphing technology, presents…

Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…

This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…

Research in cultural anthropology and the interdisciplinary field of science and technology studies (STS) has demonstrated that environmental disasters are not only techno-scientifically and socio-politically complex but also epistemically complex -- involving perspectival diversity; multiple, often conflicting forms of evidence; data gaps and…

Only weeks into its new term, the Trump administration has taken steps to lay off federally funded education research staff, cancel nearly $1 billion in contracts and dismantle the U.S. Department of Education. These moves have upended evaluations of federally funded education programs and threatened access to massive data sets that states,…

This article examines contemporary educational practices within the rapidly evolving landscape of Artificial Intelligence. We do so by analysing the relationship between artificiality and naturalness in education. Education, often characterized as a human and thus natural-historical phenomenon, now appears increasingly shaped by artificial…

Beyond informing human resources (HR) policies and practices, information gleaned from predictive analytics, visualized via dashboards, can increase awareness and prompt employee and management actions based on identified variables often related to intent to leave and employee wellness. While considerable research, relevant measurements, and tools…

When teaching the Civil Rights Movement in elementary classrooms, heroic figures such as Rosa Parks and Martin Luther King Jr. tend to dominate the curricular landscape. While it is essential for students to learn about their contributions and struggles, it is equally important to frame the broader injustices they were combating. In this article,…

In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…