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…

Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…

Development of graphical methods for representing data has not kept up with progress in statistical techniques. This article presents a brief history of graphical representations of research findings and makes the case for a revival of methods developed in the early and mid-twentieth century, notably ISOTYPE and Chernoff's faces. It resurrects and…

This article introduces an open-source software package--R for Qualitative Data Analysis (RQDA). RQDA is an R package for analysis of text-formatted data, which is compatible across operating platforms. It is user-friendly and seamlessly integrates with R, which makes it possible to conduct statistical analyses on qualitative coding. Alternative…

Integrating the use of large datasets into our teaching provides critical and unique opportunities to build students' skills and conceptual knowledge. Here, we discuss the core components needed to develop effective activities based on large datasets, which align with the 5E learning cycle. Data-based activities should be structured around a…

Chemistry is increasingly data centric and the undergraduate curriculum needs to adjust to keep up. To address this, we created the "Air Quality Activity," a new first-year undergraduate activity where students use Microsoft Excel to analyze a unique subset of atmospheric ozone (O[subscript 3]) and nitrogen dioxide (NO[subscript 2])…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…

The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…

Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…

In recent years professional accountancy bodies (e.g., CPA), accreditation institutions (e.g., AACSB) and employers have steadily raised, and continue to raise expectations regarding the need for accounting graduates to demonstrate skills in data analytics. One of the obstacles accounting instructors face in seeking to implement data analytics,…

This paper introduces the Lang-Track-App, a smartphone application and backend system to aid second language acquisition researchers in implementing the experience sampling method (ESM). Surveying research participants with the Lang-Track-App multiple times per day can yield exceptionally rich data that can be analyzed in multiple ways. This…

Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

We advocate for greater emphasis in training students about data management, within the context of supporting experience in reproducible workflows. We introduce the "L"ancaster "U"niversity "ST"atistics "RE"sources (LUSTRE) package, used to manage student research project data in psychology and build…

It is recommended that teacher-scholars of data science adopt reproducible workflows in their research as scholars and teach reproducible workflows to their students. In this article, we propose a third dimension to reproducibility practices and recommend that regardless of whether they teach reproducibility in their courses or not, data science…

The use of large, open-source data sets is ubiquitous in scientific research. Scientists--ranging from meteorologists to chemists to epidemiologists--are researching and investigating critical questions using data that they have not themselves collected. To contribute to the growing effort to bring data science into classrooms, the authors have…