As organizations' reliance on data increases, the prevalence of data analytics programs in universities likewise increases. However, despite this specialized education, scholars still report a gap between the knowledge and skills students graduate with and those required by industry upon beginning work as an entry-level data analyst. We draw on…

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…

With the rapid advancement of information technology, online education based on big data and artificial intelligence is a hot research topic in education. This study focuses on applying big data and AI in online vocal wisdom classes to enhance personalized teaching and effectiveness. It aims to address issues in traditional vocal education like…

This manuscript describes the use of real data applied to a fictional real-estate firm for teaching data visualization to university students. In the case study, students employ data analytic techniques in Tableau to clean, organize, and analyze real estate data. By creating visualizations, students address several questions about how selling…

This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their…

Students now have readily available and powerful tools to access, manipulate, combine, and visualize data. Acquiring data and visual literacy requires more than knowledge of how to use these tools. Students need to engage with assignments that challenge them to make relatively complex visualizations, interpret them, and explain why these…

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…

Data is a powerful tool for the healthcare industry to use for managing, analyzing, and reporting on critical events in the field. The analysis of broad, salient data files aids healthcare businesses in uncovering hidden patterns, market trends, and customer preferences; these details may then be used to improve the quality and delivery of care to…

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…

While an increased number of industries with business operations have been shaping their use of data analytics, the use of such tools and methods within the higher education research domain, specifically research administration, is still in its infancy. This mixed-methods study collected data to identify best practices in how universities and…

This publication describes the methods and procedures used for the 2008/18 Baccalaureate and Beyond Longitudinal Study (B&B:08/18). The B&B graduates, who completed the requirements for a bachelor's degree during the 2007-08 academic year, were first surveyed as part of the 2008 National Postsecondary Student Aid Study (NPSAS:08), and then…

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…

Many important voices--including The National Council for Teachers of Mathematics (NCTM), the Dana Center's Launch Years initiative, and others--advocate for expanding the traditional course offerings in high school mathematics and statistics to include courses such as the Introduction to Data Science (IDS). To date, the research on the IDS course…

Purpose: This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms. Design/methodology/approach: This paper describes a pedagogical approach that uses a data science…

Early childhood educators play essential roles in providing stable and high-quality child care for young children and supporting their development and growth. As is also true nationwide, historically low wages in the District of Columbia have led to challenges in compensating and retaining qualified early childhood educators, and in turn, building…