By De Angela L. Duff, Associate Vice Provost, NYU, and Industry Professor, NYU Tandon
NYU’s Office of the Provost hosted a virtual symposium, Teaching and Learning with Generative AI: Student Perspectives, on October 10, 2024. The symposium brought together students and faculty from across NYU’s global network to discuss the impact of generative AI on higher education.
I had the pleasure of moderating the first session, which was a student roundtable featuring:
- Hallelujah Abe – BA, Economics, NYU Abu Dhabi, ’26
- Sara Jakubowicz – MA, Learning Technology and Experience Design, Games for Learning Concentration, NYU Steinhardt, ’25
- Xiaochen (Nigel) Lu – MS, Computer Science, NYU Tandon, ‘25
- Bianca Mandapat – BA, Social Research and Public Policy, NYU Abu Dhabi, ‘25
- Qi Sun – BS Computer Science and Mathematics, NYU Shanghai, ‘27
- David Wang, BA, Global Liberal Studies, NYU Liberal Studies, ’27
In this roundtable, students expressed the need for faculty to acknowledge generative AI in the classroom, because, as one of the student panelists remarked, “It is no longer a secret.” They emphasized the importance of receiving more guidance from faculty on its use, while also lamenting that banning these tools outright is not the solution. Additionally, students voiced a desire to engage in conversations about the ethical and privacy concerns associated with generative AI, while also addressing the challenges and opportunities these tools present and their implications for learning.
The second session consisted of five student lightning presentations, moderated by Hui Soo Chae, executive director of the Learning and Teaching Nexus and clinical professor of education and technology at NYU SPS. Student presenters shared their experiences using generative AI for a variety of purposes, from research and writing to project management and career development.
In “AI as My Academic and Personal Assistant: From Essays to Emotional Well-being,” Nada Alwahedi (BA, political science, business organizations & society, NYU Abu Dhabi ‘26) discussed how generative AI had become an invaluable tool in her daily life, enhancing both her academic performance and personal growth. She described using it to organize study notes, brainstorm essays, and discuss readings, as well as to support her fitness goals, to help manage anxiety, and for personal journaling. As a result, generative AI has transformed the way she learns, plans, and reflects.
In “My AI Journey: From Panic to Exploration,” Tiansheng Hu (BS, computer science, NYU Shanghai ‘27) described his journey from having no experience with generative AI tools and holding a firm stance against using them to embracing these tools for his coursework and current research project.
In “Meaningful Co-Learning with Generative AI,” Zulsyika Nurfaizah (MA, learning technology and experience design, NYU Steinhardt ‘25) discussed using generative AI in a flipped classroom to summarize reading materials, to highlight key takeaways, and as a peer tutor. She suggested that generative AI could be a powerful peer tutor because it provides personalized learning, availability around the clock, and motivational boosts. She walked us through her use of Microsoft’s Copilot as a peer tutor and how she engages in back-and-forth interactions with the tool, asking it to explain concepts to specific age groups and to adopt different roles in answering. Additionally, she reminded us to always verify the output, emphasizing that generative AI “is just a tool. It cannot, will not, and should not replace our thoughts.” She also reminded us to be mindful, purposeful, and responsible in our use of the technology.
In “Using AI for Capstone Project Development Process,” Deziree Harmon (BS, interactive media & business, NYU Shanghai ‘25) shared how she is using AI for her capstone to solve for limitations of time, process creation, information organization, and idea generation. She discussed how she uses Perplexity for initial research and ChatGPT for plan generation, organization, and documentation. She also discussed how the tools failed when turning information into insights or giving insightful feedback. She found the responses too predictable and generic, concluding that it is much better to develop insights on her own and to lean on professors and other human beings for feedback. Ultimately, she emphasized that interaction with others remains key to learning, even when using these tools in tandem.
In “Getting Corporate-Ready with Generative AI,” Anisha Arora (MS, project management, NYU SPS ‘24) walked through how she is leveraging generative AI for her active job search as a graduating student. She discussed generative AI as a job seeker’s new best friend, highlighting its role in building a personal brand, applying for jobs with tools like Simplify and Microsoft’s Copilot, and preparing for interviews through mock interviews and getting personalized feedback on interview answers. She stressed the importance of using these tools ethically and using your own voice and answers during actual interviews.
During the Q&A portion of the presentation panel, students discussed how generative AI can aid in understanding concepts, but emphasized that it cannot replace the student-professor relationship or provide the experiential knowledge and personal connection that professors offer. They noted that while some faculty are open to using generative AI in their classes, others are not, expressing a desire for more faculty to embrace its potential. They highlighted the importance of open dialogue between faculty and students to help define ethical and responsible use of generative AI. The discussion ended with an emphasis on the need for faculty to clearly communicate their policies on generative AI while creating a safe space for discussing it.
The third session consisted of five faculty lightning presentations, moderated by Anandi Nagarajan (assistant vice provost for pedagogy, NYU Office of the Provost). Faculty presenters discussed how they are incorporating AI into their teaching and research and offered insights on how to effectively and ethically use these tools. Some key guidelines emerged: the benefit of transparency regarding how faculty are experimenting with and learning about generative AI; the importance of setting guidelines and expectations around student generative AI use; and the value of modeling the use of generative AI with students.
In “Shifting Student Expectations Around Faculty Use of AI Tools,” Negar Farakish (assistant dean, Division of Programs in Business, and clinical associate professor, NYU SPS) and Kristine Rodriguez Kerr (academic director, MS in professional writing, and clinical associate professor, professional writing, NYU SPS) shared students’ reactions to the incorporation of AI video avatars of the two faculty members, created using the AI app HeyGen, into their teaching materials for role play and video feedback. The faculty’s transparent communication about the use of these AI video avatars—explained in the syllabus and further clarified on the first day of class—resulted in positive and receptive feedback from students overall.
In “Graduate Student Engagement with NYU’s High Performance Computing Infrastructure: Anecdotes from a Small Seminar at ISAW,” Sebastian Heath (director of graduate studies and clinical associate professor of computational humanities and Roman archaeology, NYU Institute for the Study of the Ancient Word) and Patrick Burns (associate research scholar, digital projects, ISAW Library, NYU Institute for the Study of the Ancient Word) discussed the co-taught graduate seminar “Generating Antiquity: Artificial Intelligence for the Ancient World.” The course was designed to explore the impact of generative AI tools on Ancient World research. All students, ultimately, chose to implement projects using local, not cloud-based, large language models in NYU’s High Performance Computing (HPC) infrastructure. The faculty were pleased that students were eager to dive into the technical aspects of doing so while engaging with the question, “What is better?” to generate “better” results from generative AI. They also noted that while it required considerable effort to familiarize students with NYU’s HPC infrastructure, the students successfully learned how to use it over the course of the semester.
In “Visualizing Historical Texts with AI Tools,” Shuang Wen (clinical assistant professor of history, NYU Shanghai) integrated generative AI student use in response to challenges faced in teaching history as a graduation requirement. Some of the challenges with teaching this course include students’ lack of interest in history, limited knowledge of history, lack of engagement with the subject matter, and decreasing attention spans. To address these issues, Profesor Wen had students visualize historical texts by using generative AI tools in order to help them learn and better understand history. To Professor Wen’s surprise, students showed increased engagement with the original texts, as opposed to using generative AI to simply summarize them, as long as the readings were not too long.
In “Contextualizing Vision-Language Models for Personalized Learning in Intro-level Programming: Student Perspectives on Engagement and Effectiveness,” Hongyi Wen ( assistant professor of computer science, NYU Shanghai) discussed the challenges students face when using ChatGPT for self-regulated learning in an introduction to computer programming course. These challenges include a lack of integration with course materials and difficulty obtaining personalized, step-by-step guidance and feedback. To address these issues, the professor introduced an assistive learning system designed to integrate class materials into a chatbot and a coding Integrated Development Environment (IDE) where students can write and execute code. Findings from a four-week user study were shared, reflecting students’ perspectives on interacting with the system and revealing interesting use patterns. Some students prioritized engaging with the chatbot to explore course content, while others focused on using the coding IDE to ask questions and debug code. Overall, most students reported improved learning outcomes when using the system compared to other generative AI tools such as ChatGPT and coding IDEs.
In “What Drives Students’ use of GenAI and How It Shapes Their Engagement Patterns?,” Evgeniya Efremova (director of the Center for Teaching and Learning, clinical assistant professor of teaching and learning, NYU Shanghai) presented key findings from 20 focus interviews with diverse students at NYU Shanghai, exploring their varied engagement with GenAI. The study was interested in two main questions: “How do students engage with generative AI?” and “What drives their motivation to engage in such ways?” The talk highlighted three distinct, but common trends: generative AI as tutor and learning partner, as a survival tool, and as an efficiency tool for academic shortcuts. The three cases demonstrate how a combination of student goals and skills lead to different engagement with generative AI, which may or may not support their learning. The question posed at the end of the presentation was “How can we better assess and support students’ individual learning contexts to promote meaningful engagement?”
In the closing remarks of the session, Deziree Harmon returned to read a passage from Letting Art Teach by Gert Biesta, emphasizing that “what ultimately matters in teaching is the freedom of the student.” She highlighted how this moment in education encourages professors to better understand students and their motivations for pursuing higher education. This approach allows educators to support and focus on what students want out of their experience, rather than focusing solely on achieving predefined learning objectives set by their faculty. Sara Jakubowicz followed by stressing that generative AI is here to stay and rather than avoiding discussions about it, faculty should explore ways to integrate generative AI into the classroom effectively by using it to push students’ abilities and expand their perceptions. Additionally, she urged students to be mindful of the sustainability issues associated with using generating AI and to acknowledge its use in their assignments.
Overall, the symposium highlighted the transformative potential of generative AI in education and underscored the importance of ongoing dialogue and collaboration between students and faculty to ensure that these tools are used responsibly and ethically during this paradigm shift of teaching and learning.
To learn more and watch select videos from the symposium, visit https://wp.nyu.edu/2024studaisymposium.