Organized by the Center for Teaching Excellence. This workshop highlights the importance of aligning course learning outcomes with content and demonstrates how generative AI tools can support this process. Participants will review the purpose of learning outcomes and explore practical ways to use generative AI to enhance alignment.
Danilo Silva is an Associate Professor in the Department of Electrical and Electronic Engineering at the Federal University of Santa Catarina, Brazil, where he leads the Machine Learning and Applications Research Group. He has also been a Visiting Researcher at the TAMIDS Scientific Machine Learning Lab since January 2026. He received his Ph.D. degree in […]
Organized by the Center for Teaching Excellence. This workshop introduces instructors to the principles of student-centered learning experience design, with a focus on integrating generative AI tools available at Texas A&M University. Participants will explore how generative AI can support personalized, engaging, and enhanced learning environments, and will apply these insights to design a student-centered […]
Wai Tong is an Assistant Professor in the Visual Computing & Computational Media section and the Virtual Production Institute in the College of Performance, Visualization and Fine Arts at Texas A&M University.
Organized by the Center for Teaching Excellence. This workshop introduces graduate student instructors to practical and ethical approaches for incorporating generative AI tools into teaching and learning. The session will cover strategies for designing assignments that leverage AI responsibly, setting clear expectations for student use, and managing potential challenges such as academic integrity. Participants will […]
Organized by the Center for Teaching Excellence. This workshop introduces instructors to open licensing through Creative Commons and details the six licenses and their permissions that allow use, reuse, and revision without violating copyright laws. Participants will also see how these licenses allow material with Creative Commons licenses to be ingested into AI tools to […]
Participants will learn techniques for exploring and describing textual datasets, identifying patterns, and communicating findings through visualization. It will be one hour of theory and explanation of the concepts, and the last hour will be hands-on practice in Python. Key topics include: Interpreting exploratory findings in a social science context, word frequency analysis and comparative […]
Qiben Yan is an Associate Professor of Computer Science and Engineering at Michigan State University, where he directs the Secure and Intelligent Things (SEIT) Lab. His research focuses on cyber-physical systems security and trustworthy AI systems, spanning voice/assistive technologies, autonomous and robotic systems, and sensing/communication pipelines. Location: Blocker 220 and Zoom Zoom ID: 974 9688 […]
This workshop is designed for faculty and staff who have no prior experience in AI and have a limited technical background. Learn the strengths and limitations of generative AI (GenAI) and discuss key principles of responsible use in education while exploring everyday, no-code tools like ChatGPT. This workshop will be held virtually and hosted by […]
Organized by the Center for Teaching Exellence. This hands-on workshop guides instructors through the principles of personalized learning, emphasizing intentional design and learner agency. Participants will explore strategies for engaging students as co-designers in their learning journeys and discover how generative AI tools, especially those available through Texas A&M University can support differentiated instruction and […]
Texas NLP Symposium is a one-day workshop featuring invited talks, oral presentations, and poster sessions. Our goal is to bring together NLP researchers across Texas to share and discuss ongoing or published research, as well as to foster future collaborations. Participants from outside Texas are also welcome.
Participants will learn how to train models to categorize texts based on labeled examples and understand evaluation metrics. It will be one hour of theory and explanation of the concepts, and the last hour will be hands-on practice in Python. Key topics include: Classification algorithms like Naive Bayes and Logistic Regression, Evaluation metrics such as accuracy, […]
