Kim Nimon, PhD, is Professor in the Department of Human Resource Development (HRD) at The University of Texas at Tyler and Director of the Office of Research and Scholarship’s Research Design and Data Analysis Lab. Dr. Nimon’s expertise spans employee engagement, research design, and analytical methodologies. She currently serves as External Evaluator for two National […]
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.
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 […]
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, […]
Overview The Texas Digital Twin Symposium brings together researchers, students, and industry partners from across Texas to advance the growing digital twin research ecosystem, with a strong focus on data science–enabled methods and real-world applications. The event is designed to spark new cross-disciplinary collaborations spanning engineering, statistics, computer science, and applied mathematics. Through technical sessions, […]
Participants will learn how to identify latent themes in large text collections using unsupervised machine learning and how to interpret and validate these findings. 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: Unsupervised learning, topic modeling concepts, Latent […]
