Programs

Keynote Title: Solving the Frankenstein Problem: Why all learning is social, emotional, cognitive and cultural to the brain, and what this means for teaching and learning in the modern world.

Keynote speaker: Dr. Mary Helen Immordino-Yang

As Generative AI becomes increasingly capable — solving complex problems, simulating reasoning, and even mimicking meta-learning — many educators are responding with redesigned assessments, tighter scaffolding, and a return to oral exams and in-class blue books. But are these responses enough? In this keynote from NYU Shanghai’s Education in the Age of Generative AI: Back to Basics showcase, Dr. Mary Helen Immordino-Yang explores what truly drives learning. Drawing on cutting-edge classroom and brain research, she shows that learning is not just cognitive — it is emotional, social, and cultural. To design learning experiences that resonate deeply and foster agency, identity, and purpose, we must return to the fundamentals of learning science — and embrace what only educators can do: create emotionally resonant, human-centered learning experiences that AI cannot replicate.

Join us for this culminating session, where NYU Shanghai faculty and senior students come together for a candid, cross-role conversation about what makes learning feel purposeful and worth the effort in today’s AI-driven landscape. Drawing on student perspectives, faculty experiences, and research on the key drivers of motivation—identity, agency, and purpose—this panel invites us to reflect on how we can co-create learning experiences that are intellectually rigorous, personally meaningful, and responsive to both the opportunities and challenges introduced by generative AI.

How can educators design engaging, real-world learning experiences that foster a sense of purpose while developing students’ agency, reflective thinking, and creative problem-solving skills? This session showcases innovative approaches that move learning beyond the traditional classroom—creating authentic, emotionally resonant experiences that promote deep, meaningful skill development.

As Generative AI becomes a key tool in research and writing, educators must design strategies that help students develop foundational skills while engaging critically with AI-generated content. This session explores how AI can be integrated into research and writing instruction without compromising originality, critical inquiry, or academic integrity. Presenters will share practical approaches for leveraging AI in source evaluation, writing process, and research skills development, while ensuring students retain authorship, rhetorical awareness, and independent analytical thinking.

As GenAI reshapes how students approach learning, assessment design must evolve to promote meaningful and authentic intellectual engagement. This session explores innovative evaluation strategies that promote authentic skill development, critical thinking, and effortful learning. Presenters will share assessment models that minimize AI interference, integrate experiential learning, and reinforce academic integrity while maintaining motivation and student agency.

As students increasingly turn to GenAI for support with coursework, it is critical to examine how their learning habits and engagement are shifting. While the cognitive consequences are still being explored, there are growing concerns that frequent reliance on GenAI may limit opportunities for deep reading, analytical thinking, and effective participation in class discussions. Some research also suggests that overuse of GenAI could hinder the development of essential skills such as empathy and sustained cognitive effort. This session will explore teaching strategies that promote foundational skills like active listening, metacognitive awareness, and perseverance in complex reasoning—while guiding students to reflect on how to use GenAI thoughtfully and effectively.

Generative AI presents both challenges and opportunities in skill development for reading comprehension, writing, and argumentation. This session explores how AI can be integrated into instructional strategies to strengthen foundational  skills rather than bypass them. Presenters will showcase approaches that use AI to enhance analytical reading, structured argumentation, and iterative revision, ensuring that students engage in effortful learning while developing metacognitive awareness and essential academic competencies.

As generative AI becomes more advanced in explaining, visualizing, and solving complex problems, students are increasingly using it to support their learning. While these tools offer new opportunities, they also highlight the need to intentionally reinforce students’ procedural fluency, conceptual understanding, logical reasoning, and independent problem-solving. This session presents classroom-tested active learning strategies that promote deeper engagement with STEM concepts and support the development of these foundational skills.

In this student-created video for NYU Shanghai’s Education in the Age of Generative AI: Back to Basics showcase, six students from diverse academic and cultural backgrounds explore two powerful questions: What is an impactful learning experience to you? What made you truly engage in learning?

Each student recalls a memorable learning experience at NYU Shanghai — a moment when they were deeply invested in the learning process and willing to dedicate independent time and effort to cognitively challenging tasks.

Through their reflections, the video highlights key motivational factors that inspire deep learning: emotional resonance, personal relevance, autonomy, meaningful peer interaction, and opportunities to take intellectual risks. In their own voices, students offer a compelling reminder that authentic engagement is not imposed — it’s inspired.

/*-->*/ /*-->*/ This workshop is in collaboration with NYU AD Hilary Ballon Center for Teaching and Learning

As faculty, we take pride in providing feedback that fosters critical thinking, continuous improvement, and deeper learning. Effective feedback enhances student engagement, supports reflective practices, and drives meaningful learning outcomes.

However, providing meaningful, high-quality feedback requires a significant investment of time and effort. A common challenge is ensuring that students engage with constructive feedback rather than focusing solely on their grades.

Join this session to explore:
- Essential elements of effective feedback
- Evidence-based best practices for delivering impactful feedback
- Time-efficient strategies to streamline the feedback process

Facilitated by Evgeniya Efremova, Director of the Center for Teaching and Learning, NYU Shanghai

Leveraging GenAI for Scaffolded Writing and Critical Thinking: A Sandwich Model Approach

In this session, Professor Ruth de Llobet will share her experience of integrating ChatGPT as an instructional tool to support students at different writing levels in her PoH course. We will demonstrate how ChatGPT can provide targeted and personalized feedback aligned with assignment learning outcomes, enabling students to make independent, iterative improvements across various types of writing assignments—directly within the classroom. As part of this assignment, students not only learn how to adapt GenAI prompts for targeted feedback but also critically evaluate the relevance and limitations of AI-generated feedback while reflecting on their learning process. This session will focus on:

• A step-by-step approach to designing in-class writing activities that foster students' independent writing processes.
• Prompt engineering strategies and key considerations for effective in-class implementation.
• Evidence of student learning outcomes and reflections on their experiences.

Presenter: Ruth de Llobet, Clinical Associate Professor of the Writing Program at NYU Shanghai

The NYUSH CTL Teaching with GenAI Lab is a series of in-person workshops focused on the mindful integration of Generative AI into teaching and learning. Rooted in teaching and learning sciences, the lab ensures that AI tools are not just added for novelty but thoughtfully incorporated to enhance student engagement, deepen learning, and support critical thinking.

Writing letters of recommendation requires balancing honesty, specificity, and ethical considerations while supporting students' professional and academic goals. This session will address key challenges, including how to write honest yet supportive assessments for students across varying performance levels, when and how to decline a student’s request while guiding them toward better options, and strategies for collaborating with students to make the process more meaningful and productive.

Additionally, we will explore the ethical complexities surrounding the use of generative AI—how to handle situations where students’ documents might be AI-written and establish clear boundaries for ethically leveraging AI in drafting recommendation letters.

Understanding your students' backgrounds, skills, and knowledge—especially those beyond your course's prerequisite requirements—is essential for fostering engagement and motivation throughout the semester. In this workshop, we’ll guide you through a step-by-step process to design an effective beginning-of-course survey that aligns seamlessly with your assessments and instructional methods. Using insights from the NYUSH Student Background Survey, we’ll explore how variations in student experiences can influence classroom dynamics and demonstrate how to leverage survey results to refine your teaching strategies and provide targeted support.

Discover how GenAI enhances learning and teaching through classroom cases, gain insights from our keynote speaker, and engage in a panel discussion with faculty and students from NYU Shanghai, Duke Kunshan and other colleagues. Explore the opportunities, challenges, and collaborative paths to integrating GenAI in classrooms.

Discover how GenAI enhances learning and teaching through classroom cases, gain insights from our keynote speaker, and engage in a panel discussion with faculty and students from NYU Shanghai, Duke Kunshan and other colleagues. Explore the opportunities, challenges, and collaborative paths to integrating GenAI in classrooms.

Tired of students fixating on grades rather than learning? How can we shift from external motivation to a genuine passion for knowledge? Discover alternative assessment methods to enhance engagement, promote content mastery, and cultivate growth.

This session explores the risks associated with students' reliance on GenAI tools with respect to fundamental learning skills. In this session ARC fellows and learning assistants will share their observations about the changes in student requests in the face of GenAI by presenting several case studies. We welcome all faculty interested in understanding the nuanced effects of ChatGPT and similar tools on student learning.