Biomedical engineering is a rapidly evolving field, with the pace of evolution spurred by technological advancements, the increasing complexity of human health challenges, and globalization of the workforce. It is timely for biomedical engineering educators to explore afresh the competencies that graduates need at present, but more importantly,…

The significance of ethics in data science research has attracted considerable attention in recent years. While there is widespread agreement on the importance of teaching ethics within computing contexts, there is no clear method for its implementation and assessment. Studies focusing on methods for integrating ethics into data science courses…

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…

Contribution: This article discusses a research-practice partnership (RPP) where instructors from six undergraduate courses in three universities developed data science modules tailored to the needs of their respective disciplines, academic levels, and pedagogies. Background: STEM disciplines at universities are incorporating data science topics…

We present a two-week active learning chemical engineering hackathon event specifically designed to teach undergraduate chemical engineering students of any skill level data science through Python and directly apply this knowledge to a real problem provided by industry. The event is free and optional to the students. We use self-evaluation surveys…

Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…

The integration of generative artificial intelligence (GenAI) is reshaping biomedical engineering (BME) education. This paper presents insights from "The Fifth Biomedical Engineering Education Summit", which brought together educators from across the U.S. to address challenges and opportunities in integrating GenAI into BME curricula.…

Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…