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…

We consider Bayesian estimation of a hierarchical linear model (HLM) from partially observed data, assumed to be missing at random, and small sample sizes. A vector of continuous covariates C includes cluster-level partially observed covariates with interaction effects. Due to small sample sizes from 37 patient-physician encounters repeatedly…

In this essay, we explored the feasibility of utilizing artificial intelligence (AI) for qualitative data analysis in equity-focused research. Specifically, we compare thematic analyses of interview transcripts conducted by human coders with those performed by GPT-3 using a zero-shot chain-of-thought prompting strategy. Our results suggest that…

Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…

The purpose of this study is to investigate the current state of graduate level business analytics education in the United States. The goal of this research is twofold. The first goal is to understand how higher education institutions are addressing the growing demand for analysts and data-savvy managers in the job market. To achieve this aim, the…

In this article, the author examines how young learners became critical information architects for presenting community and classroom data. The article begins with an overview of the literature on critical literacy, critical data literacy, and young children's visual cultures. Next, it lays out the project's context, modes of inquiry, and methods…

Over the past decade, more attention to data, quantitative, and critical data literacies in writing studies has led to a variety of approaches for getting students to experiment with data in their writing projects. This article explores an approach combining "data feminism" and "quantitative rhetoric" that asks students to…

At City Academies Neighborhood Middle School, there is a gap in student achievement. Over the course of two years, our lowest performing students did not grow at the rate of their peers. This problem has several consequences, including over classification of students with disabilities and a widening achievement gap. The purpose of my research was…

Objective: Several studies have shown that Adult ADHD presents differently in younger and older adults. We sought to assess the difference in care between these two groups using previously identified quality measures (QMs). Methods: Using electronic health record data, we matched a younger group of ADHD patients to an older group. We then assessed…

Children require access to high-quality statistics education to develop the skills to participate in a technological and data-reliant workforce. This study consisted of a five-lesson integrated STEM unit designed to develop the statistical literacy of 62 6th-grade (11-12 years old) emerging bilingual (EB) learners. Learning was situated in the…

Transparency is once again a central issue of debate across types of qualitative research. Work on how to conduct qualitative data analysis, on the other hand, walks us through the step-by-step process on how to code and understand the data we've collected. Although there are a few exceptions, less focus is on transparency regarding…

The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

Research on classroom motivational climates and microclimates--students' shared and idiosyncratic perceptions of motivational classroom features--demonstrates their importance for fostering adaptive motivational and achievement-related outcomes. However, a lack of coherent theoretical guidance about the nature of students' classroom climate…

We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…