Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…

The research is a descriptive correlational study that investigates new methods for the creation of innovation for institutions. The research addresses the need for organizations to generate a novel form of innovation for their competitiveness and survival. These novel methods in the generation of innovation include using an organization's big…

Classification, a fundamental data analytics task, has widespread applications across various academic disciplines, such as marketing, finance, sociology, psychology, education, and public health. Its versatility enables researchers to explore diverse research questions and extract valuable insights from data. Therefore, it is crucial to extend…

Sustainability education, as endorsed by the United Nations to address the economic, social, and environmental dimensions of sustainable development, poses challenges due to the extensive spatial and temporal scales of global issues. In this novel, semester-long project, "The Poo-tastic Project: A Deep Dive into Sustainable Sanitation with…

Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…

This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…

Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…

In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…

In this dissertation, I engage in three analytic cuts to think about/with a relational ontological orientation to data and data literacies/science education. The analysis focuses on the following question: What possibilities for teaching and learning about data are made possible when we attune to the relational, noisy, liminal, and material…

Traditional functional budgets are useful for planning under predictable business environments. However, due to increased competition, changes in technology, consumer attitudes, and economic factors affecting supply chains, accountants must understand the characteristics of risk and uncertainty. Additionally, businesses now have access to…

The perceived importance of data in society has led to a surge in interest towards data science education. This article seeks to build on existing literature concerned with the sociopolitical, cultural, and ethical dimensions of data science education by considering the salience of two interrelated concepts discussed in Asian and Asian American…

Biomedical data science education faces the challenge of preparing students for conducting rigorous research with increasingly complex and large datasets. At the same time, philosophers of science face the challenge of making their expertise accessible for scientists in such a way that it can improve everyday research practice. Here, we…

Two-year colleges provide the opportunity for students of all ages to try new subjects, change careers, upskill, or begin exploring higher education, at affordable rates. Many might begin their exploration by taking a course at a local two-year college. Currently, not many of these institutions in the U.S. offer data science courses. This article…

This study examines the impact of changes in exam modalities on the performance and experiences of architectural engineering students in a domain-specific data science class. Specifically, the number and duration of exams (and thereby the amount of content on each) and setting in which the students took the exams in changed among the three years…

Purpose: This study aims to examine the absorptive capacity of an elementary school participating in a multi-year research-practice partnership (RPP) focused on increasing data science instruction through curriculum development. This research considers how data science initiatives might be sustained with fewer supports from the research team as…