Students typically find research methods and statistics classes intimidating. In particular, learning different types of data measurement and operationalization can take significant time and practice to understand. Utilizing a pedagogical approach that turns a party game into a fun exercise, students collaboratively learn to operationalize…

The purpose of the study was to understand the experiences of data scientists regarding common skills and strategies of interpreting and creating data visualizations. In this Delphi study, the participants were researchers in Data Science using three rounds of surveys. Skills and strategies were identified after Delphi Panel 1 and then brought…

Algebra has been identified as a gatekeeper to careers in STEM, but little research exists on how algebra appears for practitioners in the workplace. Surveys and interviews were conducted with 77 STEM practitioners from a variety of fields, examining how they reported using algebraic functions in their work. Survey and interview reports suggest…

Data preparation (also called "wrangling" or "cleaning") -- the evaluation and manipulation of data prior to formal analysis -- is often dismissed as a precursor to meaningful engagement with a dataset. Here, we re-envision data preparation in light of calls to prepare students for a data-rich world. Traditionally, curricular…

The main goal of this study was to evaluate the impact of an animation and visualization of data structures (AVDS) tool on both perceptions and objective test performance. The study involved a rigorous experiment that assessed the usability, acceptability, and effectiveness of the AVDS tool in solving exercises. A total of 78 participants…

The SQL-Explore Learning Module detailed in this teaching tip provides an opportunity for students to apply database course knowledge beyond solving traditional pre-determined Structured Query Language (SQL) coding questions. In this unique constructivist activity using the apropos 5E Instructional Model, students explore tables to locate data…

This research explores the perspectives of marketing students and educators about the Big Data courses in marketing education programs. It also examines drivers that predict interest on the part of marketing students in taking Big Data courses. Data was collected through interviews with 20 marketing educators, and a survey was completed by 480…

Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…

Data analytics is a rapidly growing field that plays a crucial role in extracting valuable insights from large volumes of data. A data analytics practicum course provides students with hands-on experience in applying data analytics techniques and tools to real-world scenarios. This practicum is intended to serve as a bridge between the student's…

Faculty teaching data analytics at undergraduate level are often faced with the tension created by student under-preparedness, the demands of the course, and time constraints. How do faculty close this gap? In this paper, we propose the use of flow diagramming as an accessible method for interpreting regression analyses, in ways that are time…

We draw on our experiences with mentoring two students to develop a framework for undergraduate research projects with Twitter data. Leveraging backward design principles, we share our learning objectives and rubric for summative assessments. To illustrate the value of Twitter as a data source, we detail methods for collecting and analyzing…

Analysis of keystroke logging data is of increasing interest, as evident from a substantial amount of recent research on the topic. Some of the research on keystroke logging data has focused on the prediction of essay scores from keystroke logging features, but linear regression is the only prediction method that has been used in this research.…

Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…

The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…

Although the use of tables, graphs, and figures to summarize information has long existed, the advent of the big data era and improved computing power has brought renewed attention to the field of data visualization. As such, it is crucial that introductory statistics courses train students to become critical authors and consumers of data…