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The awarded multiple seed grants this spring to help spur research teaming in the college and boost early projects with the high potential for societal impact.

The research theme launched in 2021 and includes research in engineering and computing education and assessment, as well as AI, machine learning and the convergence between those areas. One key goal is to develop the theories, technologies, and know-how for advancing student-centered learning and creating next-generation learning environments in K-16, graduate, and professional engineering and computing education.

The 2023 seed grants ranged in funding and scope and present a great opportunity for collaboration, said theme Co-Director Angela Bielefeldt.

“My co-director, Alessandro Roncone, and I are looking forward to seeing the work after reviewing applications. We hope to have teaming events and activities soon as well, so there is still plenty of time for interested researchers to connect with the theme and tap into it as a resource for their work,” she said.

Supporting Explainable AI for Future Analysts with Interactive Physicalizations

AI is becoming increasingly integrated into nearly every aspect of our daily lives, from the use of large language models for natural language interfaces such as ChatGPT to object detection models for autonomous vehicles. Despite its benefits, AI can also have negative impacts such as reinforcing biases and unfairly distributing harms. As a society, we need ways to understand and educate individuals about the state and impact of these artificial intelligence systems. In this proposal, researchers will use data physicalization techniques to support AI explainability – enabling future professionals to both explore and better explain analytical findings about models to others. This work will serve as the foundation for a large grant proposal to either the National Science Foundation’s Future of Work at the Human-Technology Frontier or the Human-Centered Computing programs. Researchers: Michael Rivera (ATLAS/CS), Ellen Do (ATLAS/CS), Danielle Szafir (CS, University of North Carolina at Chapel Hill), Sandra Bae (ATLAS PhD Student).

Glitching the System: Examining Race-Conscious and Justice-Oriented Approaches to AI and Computing Education with Black Youth 

Research has shown that has shown that Black students consistently endure inequitable, dehumanizing and racially hostile conditions as they traverse the STEM educational pipeline – especially within the computer science discipline. At the same time, AI technologies continue to proliferate within urban classrooms – promising to bolster academic achievement with anti-cheating software for example but potentially compounding historic educational inequality for marginalized students. The goal of this mixed methods research project is to examine the experiences of 25 Black youth students from low-income, urban schools as they engage in a race-conscious, justice-oriented course on artificial intelligence technologies. The program will have rich implications for equity-oriented STEM education. Researchers: Amy Javernick-Will (CEAE), Tiera Tanksley (School of Education).

STEM learning environments abroad with AI for interactive learning

Students who study abroad benefit from a unique opportunity to immerse themselves in another culture and become global citizens. This project will focus on STEM learning environments abroad and how to make those learning environments more interactive with artificial intelligence. Funds will support time and expenses for developing a National Science Foundation EDU Core Research grant proposal including an intensive series of workshops between members of the college at every level. Those sessions will be held at every level of the College of Engineering and Applied Science and will seek to understand student motivation through meetings with student advisors and departments to understand the barriers and strengths of such the proposed center. Researchers: Jessica Leeker (Engineering Management) and Angela Bielefeldt (CEAE).

Juxtaposition of Analog and AI-Generated Student Works in Fine Art, Language Arts, and Computing Education 

This project seeks to study generative AI’s impacts on fine art, language arts, and computing education. Broadly it asks how does – and how will – artificial intelligence like ChatGPT impact education practices at all levels? And what are the opportunities and challenges for teachers and students learning and working with AI in this space. To answer these questions researchers will study the juxtaposition of analog and AI-generated student works such as paintings and essays where generative artificial technology is already being used by educators. Data from this pilot project will be used to inform future large-scale research proposals and will support technology development efforts to build tools to assist teachers in incorporating generative AI in their classrooms. Researchers: Tom Yeh (CS), Diane Sieber (Herbst Program for Engineering, Ethics and Society), Larissa Schwartz (ATLAS PhD Student), Mohsena Ashraf (CS PhD Student).