GenAI in the Classroom: A Double-Edged Sword of Potential, Pitfalls, and Uncertainty

Mortaza Jamshidian Chair
California State University-Fullerton
 
SUNNY LE Discussant
California State University Fullerton
 
Matheus Bartolo Guerrero Organizer
California State University Fullerton
 
SUNNY LE Organizer
California State University Fullerton
 
Tuesday, Aug 5: 2:00 PM - 3:50 PM
0442 
Invited Paper Session 
Music City Center 
Room: CC-Davidson Ballroom A1 

Applied

Yes

Main Sponsor

Section on Statistics and Data Science Education

Co Sponsors

American Educational Research Association
Business Analytics/Statistics Education Interest Group

Presentations

AI's Impact on Teaching at Williams and Beyond

AI has already starting reshaping our teaching by changing how we approach content, delivery, and assessment. With the rapidity by which AI is "learning" who knows what the impact will be by the time I give this talk? This semester I will no longer be giving take home exams and am contemplating giving an oral midterm or final. And that's only the tip of the iceberg of the changes that I anticipate. This talk will highlight some of these changes in teaching that I and others at Williams have implemented as we attempt to navigate this new world and I hope to generate a conversation about where we are headed.  

Keywords

Artificial Intelligence (AI)

Educational Technology

Assessment Methods

Pedagogical Innovation

Future of Education

Teaching Strategies 

Speaker

Richard De Veaux, Williams College

Educating Students and the Public on Using AI and Statistics to Make Decisions

How do we make choices when faced with a health crisis? Or a natural disaster? AI is being developed and deployed in technology to help us navigate a new route, summarize large collections of documents, or protect our devices using face recognition, but the gap between autonomous decision-making and human decision-making still exists. Moreover, people make decisions under uncertain, dynamic, and resource-constrained circumstances and often incorporate concerns about risk, equity and trust. All concepts grounded in foundational statistics, making our educational programs more important than ever. In this talk, we'll look at the education efforts of the NSF AI Institute for Societal Decision Making (centrally housed at Carnegie Mellon University) to train the public - including K-12, community college, undergraduates, graduate students, and the workforce - to use both AI and statistics as well as understand their potential to positively impact society. 

Keywords

Artificial Intelligence (AI)

Statistical Education

AI Ethics

Workforce Training 

Co-Author

Rebecca Nugent, Carnegie Mellon University

Speaker

Rebecca Nugent, Carnegie Mellon University

GenAI in Action: A New Approach to Student-Centered Learning

In this case study, we explore the transformative role of generative AI in enhancing student-centered learning within the College of Natural Sciences and Mathematics at California State University, Fullerton. Through an innovative project, students from diverse majors, including Mathematics and Statistics, were trained to design AI-based educational activities that address gaps in traditional teaching methods. These activities were implemented and tested in collaboration with faculty, with results showing significant improvements in student engagement, understanding, and satisfaction. This presentation highlights the potential of AI to close equity gaps, increase retention rates, and prepare students for success in a technology-driven world. 

Keywords

Generative AI

Educational Innovation

Student-Centered Learning

Equity in Education

Interdisciplinary Collaboration 

Co-Author

Matheus Bartolo Guerrero, California State University Fullerton

Speaker

Matheus Bartolo Guerrero, California State University Fullerton

Large Language Models and Statistics Education

AI, large language models, and deep learning are changing the way we all work. Many changes are macro-level changes, effecting the world or at least economic or employment sectors. But others are quite specific. In the statistics curriculum, we need to adapt to new modes of instruction, new types of problem sets, and new data analytics. This talk lists some of the changes in my classroom, and tries to look over the horizon to further changes. 

Keywords

Artificial Intelligence (AI)

Statistics Education

Educational Trends

Curriculum Development 

Speaker

David Banks, Duke University