Thursday, October 26, 2023
Please note all times are in US Eastern Time. The schedule and speakers are subject to change.
Sessions with an asterisk (*) will not be recorded!
We will have two pre-conference workshop tracks: foundational and intermediate, as well as two shared sessions! The shared sessions will use the same Zoom link as the foundational track.
Foundational Track
8–9am EDT
Hands-on with Generative AI
Tim Schaffer, Senior Educational Technologist, Office of Educational Technology, NYU Arts & Science
Faculty new to generative AI will learn the basics of Large Language Models (LLMs such as ChatGPT, Google’s Bard, or Microsoft’s Bing), and privacy and ethical concerns.
9:30–11am EDT
(Re)Designing Assignments and Assessments Using Generative AI
Shaina Dymond – Educational Technologist Specialist, Office of Educational Technology, NYU Arts & Science
Faculty and staff will explore ways of designing and redesigning assignments and assessments that integrate generative AI tools and encourage their effective use where appropriate, as well as encourage originality and discourage over-reliance on AI. We’ll also discuss the ethical implications and potential misuse of AI tools in academic settings.
Intermediate Track
8–9am EDT
ChatGPT for Teaching and Learning around Computational and Quantitative Data Analysis and Visualization
We will explore and demonstrate how ChatGPT can be integrated and deployed for teaching and learning around computational and quantitative data analysis and visualization from the perspectives of both instructional technologists and learners.
Leveraging LLMs for Application Development: A Developer’s Perspective on Building Applications with LLMs
Utku Tuluk – Senior Associate of Emerging Technology, NYU Shanghai Library
A Socratic Tutor with Empathy: An early exploration to using LLMs as tutors and teaching assistants
Guangyu (Tim) Wu – Research Associate, PhD candidate, Shanghai, Key Laboratory of Urban Design and Urban Science, NYU Shanghai
ChatGPT for Visualization: ChatGPT for Teaching and Learning around Computational and Quantitative Data Analysis and Visualization
Xinyi Zhu – Motion Graphics and Animation Specialist, NYU Shanghai Library
ChatGPT in Data Lifecycle
Yun Dai – Data Librarian, NYU Shanghai Library
9:30–10am EDT
Leveraging Ed Tech Resources to Promote Academic Honesty in Coding Classes
Slides: Ed Discussion, Ed Workspaces, and Ed Lessons
Slides: Gradescope
Craig Kapp – Clinical Professor, NYU Courant
Andrew Greene – Senior Educational Technologist, Office of Educational Technology, NYU Arts & Science
We will explore and demonstrate the Ed Tech tools, ED STEM and Gradescope, specifically in the context of teaching introductory computer science courses.
10–11am EDT
A Survey of Generative AI Tools for Text, Audio, Image, and Video Generation and Editing
We will explore and demonstrate the Advanced Data Analysis tool in ChatGPT, Google’s NotebookLM, ElevenLabs for audio generation, and image and video generation and editing using DALL-E, Duet AI in Google Slides, Powerpoint Designer, Adobe Photoshop, Runway, and Descript.
De Angela L. Duff – Associate Vice Provost, NYU, and Industry Professor, NYU Tandon
Hui Soo Chae – Executive Director, Learning and Teaching Nexus, and Clinical Professor, Education and Technology, NYU SPS
Shared Track
9–9:30am EDT
Evaluating and Acknowledging AI-Generated Text
Michelle Demeter – Head of Undergraduate & Instructional Services, NYU Division of Libraries
This librarian–led session will address ways faculty can better evaluate & acknowledge AI–generated text.
11am–12pm EDT
Zoomside Chat: Generative AI for Teaching and Learning*
There were no slides for this session.
Clay Shirky – Vice Provost for AI and Technology in Education
Faculty can share experiences, ask questions, and exchange ideas with one another about the challenges and advantages of using generative AI tools.