Recently, the rise of generative AI tools such as "ChatGPT" have prompted deep and wide considerations about teaching and learning, student success, research and development, and the use of data for informed institutional decision making. In this volume, authors discuss specific concepts, considerations for use, and some specific tools…

Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it…

In a ranking created by using data from multiple data sources, including CareerBuilder, GitHub, Google, Hacker News, the IEEE, Reddit, Stack Overflow, and Twitter, Python was shown to be the top programming language of 2023. Created in 1990, Python has seen a recent uptick in popularity driven primarily by its ability to sustain the use of…

Sport analytics remains a growing area in the sport industry. As such, the demand for skills and knowledge in this area has grown. This demand includes off-field data, such as marketing trends, as well as financial data related to sport organizations. There has been a trickle-down effect in sport management (and other) education programs to teach…

This paper introduces the LEGO® Database, a large natural dataset that can be used to teach Structured Query Language (SQL) and relational database concepts. This dataset is well-suited for introductory and advanced database assignments and end-of-semester group projects. The data is freely available from Kaggle.com and contains eight tables with…

Despite the increasing interest in data analytics applications within postgraduate education research, there remains a significant gap in research dedicated to exploring mixed methods research for such investigations. This study undertook to bridge this gap by exploring the application and use of mixed methods research to examine data analytics…

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…

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…

In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…

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…

This study explores the association between having a transit stop within walking distance of campus and Pell Grant recipient completion rates at US commuter institutions, using a novel dataset on transit stop locations and institutional level data. The findings indicate that there is a positive association between transit access and Pell…

The increasing use of learning management systems (LMSs) generates vast amounts of clickstream data, opening new avenues for predicting learner performance. Traditionally, LMS predictive analytics have relied on either supervised machine learning or Markov models to classify learners based on predicted learning outcomes. Machine learning excels at…

Chinese universities face a persistent paradox: Despite substantial investments in R&D and strong knowledge production performance, their socioeconomic impact remains limited. To address this disconnect, we develop a dual-stage efficiency framework distinguishing knowledge production (KPE) from knowledge transformation (KTE) and implement a…

Purpose: This study aims to analyze the platforming scenario at a Brazilian university as well as the data security process for students and professors. Design/methodology/approach: This research brings an analysis through a qualitative approach of the platformization process in a Brazilian teaching institution. Findings: The results point to a…

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…