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Session Description

Ticketed event: SUNDAY WORKSHOP: The use of Generative AI - $5.00 advanced registration and $10.00 on site registration
The use of artificial intelligence (AI) based applications is increasing across all engineering disciplines. Higher education needs to keep pace with this development to leverage these developments to conduct better research and training and, critically, to ensure that students are prepared to use these tools in their work and for lifelong learning.

In particular, in recent years, the use of generative AI (GAI) driven tools and applications such as ChatGPT, Dall-E, Midjourney, CoPilotand Autodesk, has become popular. GAI a subfield of AI in which deep learning and large language models are used to generate new content. Generative writing is being used to generate copy, write job descriptions, and technical documentation. Generative design systems allow engineers to start with pre-designed models whereas generation of code based on a prompt is making the software development process more efficient.

This workshop will focus on several aspects related to use of GAI including: (1) Research: Data Generation, Data Analysis, Data Reporting, Instrument Creation, Data Presentation, and Paper Drafting; and (2) Teaching: Assessment, Question Creation, Assignment Generation, Preparation for Teaching, Syllabi Generation, Topic/Concept Generation, and Topic Summarization. In addition to introducing attendees to different uses of GAI, we will work through some in depth scenarios. We will also discuss ethical issues related to the use of AI and GAI and how to use these applications in a more responsible manner.

This workshop presents a unique format that allows attendees to see the impacts of these tools through analysis and first-hand experience. Attendees will be invited to create accounts on different GAI application sites so that they can experience them firsthand. After the workshop, attendees will be given a list of tools and applications to continue to explore different features and evaluate the applications' usefulness for their research and teaching practices.

Speakers

1. Dr. Aditya Johri

   George Mason University

   Aditya Johri is Professor of Information Sciences & Technology and Director of Technocritical Research in AI, Learning & Soceity Lab (trailsLAB) at George Mason University, USA. He studies how technology shapes learning across formal and informal settings and the ethical implications of using technology in education. He publishes broadly in the fields of engineering and computing education, educational technology, and computer-supported collaborative work and learning. His research has been recognized with several best paper awards and his co-edited volume, the Cambridge Handbook of Engineering Education Research (CHEER), received the 2015 Best Book Publication Award from Division I of AERA. Most recently he served as a Fulbright-Nokia Distinguished Chair in ICT at Aalto University, Finland (2021). He is a past receipient of the NSF Early Career Award and in 2022 University Teaching Excellence Award and Mentoring Excellence Award for undergraduate research at George Mason University. He was awarded a Ph.D. in Learning Sciences & Technology Design (2007) from Stanford University, Palo Alto, CA. More information is available at: http://mason.gmu.edu/~johri

2. Dr. Andrew Katz

   Virginia Polytechnic Institute and State University

   Andrew Katz is an assistant professor in the Department of Engineering Education at Virginia Tech. He received his Ph.D. in engineering education from Purdue University, has a master’s degree in environmental engineering from Texas A&M University and a bachelor’s degree in chemical engineering from Tulane University. His research focuses on engineering ethics, decision-making, and system development. To do this, he examines topics such as faculty mental models of engineering ethics and education, processes of change in ethics education, and students’ views of ethics and social responsibility. Three particular, current areas of interest in the lab are: environmental sustainability (i.e., how students learn and make decisions that affect the environment), automated technologies (i.e., how educators can use digital technologies as well as how engineers make design decisions for automated technologies that affect communities), and human health (i.e., how we can make sure education systems promote a holistic student formation that foster mental and physical health, minimizing the stereotypical grind associated with pursuing an undergraduate engineering degree).