Program 2025

Keynote Speaker

The Showcase will feature a keynote by Dr. Mary Helen Immordino-Yang, who will offer research-based insights on the cognitive and emotional dimensions of learning in the age of AI. 

Dr. Mary Helen Immordino-Yang, is the Fahmy and Donna Attallah Professor of Humanistic Psychology and a professor of education, psychology, and neuroscience at the University of Southern California in Los Angeles, USA. She is the founding director of the USC Center for Affective Neuroscience, Development, Learning and Education, or CANDLE. Immordino-Yang received her doctorate from Harvard University in 2005 and completed postdoctoral training in affective neuroscience with Antonio Damasio in 2008. She has since pioneered novel approaches to the study of child and adolescent social-emotional and brain development, and has written extensively on implications foe educational practice and policy. She has received numerous national and international awards for her work, and in 2023 was elected to the U.S. National Academy of Education

Keynote Title: Transcendence!: Supporting Youths’ Coordinated Neural Development of Abstract Thinking, Social Emotion, and Self-Awareness in the Age of AI

Abstract:

The proclivity to think and feel deeply about complex issues and ideas is a hallmark human achievement—a foundation of global society as well as of personal growth. This achievement rests on capacities for transcendent thinking, that is, on one’s abilities and dispositions to consider the broader personal, ethical and systems-level implications that transcend situations and pertain to bigger concepts, values and identities. In this talk I will discuss our transdisciplinary, longitudinal studies of transcendent thinking in adolescents, demonstrating its underlying neural dynamics, its power to predict future brain and psychosocial development, and its role in neural resilience.  The findings reveal a novel predictor of mid-adolescents’ neural development, and underscore the active role adolescents play in their own brain development through the meaning they make of the social world.

Next, I will share some of our new brain, interview, and classroom observation data from urban public secondary teachers as they teach, grade students’ work, provide student feedback, and the like. The findings shed light on the neural correlates of social skill in a highly trained domain-- that of secondary teaching. For those interested in educational innovation, they also present new ways to think about the emotional and social work involved in skilled teaching, with implications for teacher professional development and the incorporation of AI technologies into the classroom. 

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.

Student participants:

Jiale (Cecilia) Zheng, Honors Math & Data Science, Class of 2025

Muhammad Saffi Ullah, Economics, Class of 2025

Mateo Rengifo Orozco, Business & Finance, Class of 2025

Anya Zhukova, Interactive Media Arts, Class of 2025

Rong (Richard) Xiang, Undecided, Class of 2028

Tania Hartano, Interactive Media Arts, Class of 2025

Produced by:

Deziree Joy Harmon, Interactive Media and Business, CTL Researcher, Class of 2025

Nartay Ualikhan, Interactive Media Arts, Class of 2025

Directed by Evgeniya Efremova, Director, Center for Teaching and Learning

Session Introduction

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.

1. Maintaining Active Physics Learning in the Era of Artificial Intelligence 

Paul Stanley, Associate Dean for Undergraduate Studies, Academic Services, Duke Kunshan University

Changcheng Zheng, Associate Professor of Physics, Division of Natural and Applied Science, Duke Kunshan University

Abstract: As AI tools become increasingly accessible, traditional physics homework assignments are losing their effectiveness as assessments of student understanding. We explore strategies to foster critical thinking, meaningful engagement, and deep learning in physics classrooms where AI is readily available. We will present classroom activities that encourage students to engage with physics concepts actively, even when AI assistance is used. These activities emphasize collaboration, cognitive reflection, and knowledge sharing, promoting deeper conceptual understanding. These learning tasks designed to be resistant to AI-generated solutions while still challenging and engaging for students. We also quickly highlight surprising findings about what AI can—and cannot—do when educational strategies fail to account for its capabilities. Through brief examples, we will examine the impact of these strategies on student engagement and learning outcomes, drawing from real-world classroom experiences. Key takeaways for educators will include practical methods for designing AI-aware physics instruction, techniques to encourage metacognition and peer learning, and insights into the evolving role of assessment in the age of AI. Participants will leave with concrete strategies to navigate the challenges and opportunities that AI presents in physics education.

2. Problem-Solving and Generative AI in Linear Algebra

Donatella Delfino, Clinical Professor of Mathematical Studies, School of Professional Studies, Division of Applied Undergraduate Studies, NYU New York 

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Abstract: In MATH1-UC 1180 Linear Algebra, I encourage students' critical thinking and problem-solving skills by structuring assessments and class discussions to challenge AI reliance and promote independent reasoning. This strategy integrates three key components: (1) crafting quiz questions that expose AI-generated answers by requiring engagement with class discussions, (2) incorporating visual problems where AI struggles, and (3) prompting AI to generate subtly flawed solutions for students to critique.
Discussions have been productive, and students actively analyze both their reasoning and potential AI errors. Observations suggest that students are becoming more discerning in evaluating solutions and are less likely to accept AI-generated output uncritically. This strategy transfers seamlessly to the online synchronous version of MATH1-UC 1180, where assessments and discussions can be structured similarly. The key principles—designing assessments and discussions that reveal AI use, incorporating problems AI struggles with, and prompting AI to generate subtly flawed responses for critique—may be applicable across disciplines. For example, in a writing course, students could evaluate an AI-generated argument that appears well-reasoned but subtly favors one perspective. In data analysis or statistics, students could assess AI-generated interpretations of data, identifying biases or errors.

3. Advancing Critical Thinking Through Three-Stage Collaborative Analysis (TSCA) in the AI Era

Joohyun Lee, Assistant Professor, Department of Natural and Applied Science, Duke Kunshan University

Abstract: Undergraduate education is uniquely challenged by the widespread access to artificial intelligence tools. As proposed, the innovative introductory Biology course (BIOL110- Integrated Sciences: Biology) teaching methodology, Three-Stage Collaborative Analysis (TSCA), utilizes structured peer engagement to convert challenges into enriched learning opportunities. My approach addresses two fundamental challenges: preserving academic rigor and developing students' analytical capabilities. The methodology centers on a three-stage learning process: initial content delivery through focused lectures, application through carefully selected past examination questions or real-world scenarios, and structured small-group analysis. Students first develop independent solutions, then engage in guided four-person group discussions, culminating in collaborative problem-solving. Assessment emphasizes analytical progress over correct answers, with evaluation based on the quality of discussion rather than solution accuracy. Each student submits a comprehensive analysis that includes their own perspective, individual insights from each peer, and the group's conclusions. This structured approach naturally discourages AI dependence by emphasizing personal engagement and collaborative reasoning. The methodology's effectiveness is demonstrated through quantitative and qualitative metrics. Class attendance consistently exceeds 95%, reflecting students' recognition that success requires active engagement with current lecture material. Student feedback highlights enhanced conceptual understanding, with participants noting improved analytical skills and deeper subject comprehension. Educators aiming to apply this method should consider these fundamental principles: (1) organizing assessments based on analytical processes instead of results, (2) incorporating instant application of lecture ideas, (3) blending individual responsibility with group learning, and (4) tracking the development of analytical thinking through multi-perspective analysis.
 

4. Solvers and Graders Game: Problem-Solving Method for AI-Independent Classes

Eric Ossami Endo, Assistant Professor of Practice in Mathematics, Department of Mathematics, NYU Shanghai

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Abstract: Solvers and Graders Game is an effective strategy to make the students active during problem-solving activity classes. The method consists of three phases: (1) Students make groups of five to solve questions on blackboards at the same time; (2) They rotate to the next group to correct and comment on their solutions; and (3) The instructor gives a final comment for each question. This method provides an AI-independent engagement designed to encourage students to discuss the material in groups and with the instructor. Moreover, during the third phase, the instructor can focus on commenting on their solutions and giving tips to improve their written justification. The principal point of this activity is to keep the students active during the lecture time, and their solutions are important resources to discuss the expected answer. This activity highly supported students in learning theoretical concepts and doing step-by-step calculations since mathematics is an area that requires problem-solving assessment. It has been successful in a class of 30 students at different levels. Students’ feedback shows that the Solvers and Graders Game motivates them to attend the recitation and boosts their confidence to solve high-level problems. Since the game itself does not depend on mathematics, it can easily be adapted to any problem-solving activity lectures in different classrooms.

Session Introduction

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.

1. AI Reading Chatbot: Enhancing Student Engagement with Course Readings

Jay Ludowyke, Clinical Assistant Professor, Writing Program, NYU Shanghai

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Abstract:  Getting students to engage meaningfully with assigned readings is a persistent challenge in higher education, particularly as GenAI tools offer easily accessible reading ‘shortcuts’. While such tools provide convenience, they risk bypassing the intellectual labour of reading, analysing, and critically engaging with texts. This shift raises concerns about the erosion of foundational academic skills, particularly in courses that emphasise deep reading and scholarly discourse.

This presentation introduces a targeted intervention: a private AI Reading Chatbot designed to facilitate, rather than replace, student engagement with course readings. By using Retrieval Augmented Generation (RAG), the chatbot allows students to engage in dynamic, text-specific discussions. It responds to student inquiries, clarifies complex concepts, and encourages critical reflection through Socratic questioning. Crucially, students define how they want to engage—whether seeking assistance in understanding the text or opting for a more analytical, debate-driven discussion. In this latter mode, the chatbot challenges interpretations, introduces counterarguments, and prompts students to articulate and refine their perspectives.

This session will examine the chatbot’s implementation, focusing on its design parameters and effect on student reading practices. It will present data from student surveys, assessing the chatbot’s effectiveness in fostering comprehension and critical thinking, as well as student reflections on how it facilitated deeper reading practices and where refinements were necessary. This approach is highly transferable, offering a model for attendees to adapt in their own classrooms to integrate AI in ways that support reading comprehension, promote deeper inquiry, and sustain student investment in effortful learning.
 

2. Finding Sources with Scopus AI, Google Scholar, Google: Helping Students Explore Arguments Across Majors

Simon Thomas, Centre for English Language Education, University of Nottingham Ningbo China

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Abstract: This talk presents a strategy for developing students’ critical thinking and reading comprehension by supporting them to find, understand, and evaluate arguments using Scopus AI, Google Scholar, and Google. In a first-year interdisciplinary module with over 1,200 students from seven subject areas, students explored an argument linked to their major using the “Six Thinking Hats” framework. Each group received targeted research questions, with suggested search terms to guide their use of Scopus AI and other tools.

Students initially found the research task challenging, but reflections show they quickly gained confidence after using Scopus AI to identify clear academic positions. They then used all three tools to explore supporting and opposing views, practising skim- and scan-reading of peer-reviewed sources and other materials. Their findings were summarised in digital group posters, with evaluation of their chosen argument’s strengths and weaknesses, and a clear statement of the group’s position.

The strategy is highly transferable: it enabled one teaching team to support students from multiple disciplines using structured prompts and AI-supported searches, without requiring deep subject expertise. The approach could easily be extended to other academic fields where students need to investigate, evaluate, and reflect on arguments in context.

3. Scaffolding Critical Thinking and Independent Learning: A GenAI-Supported EAP Classroom Strategy

Jinyang (Sam) Song, EAP Lecturer, English Language Centre, School of Languages, Xi’an Jiaotong-Liverpool University 

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Abstract: Developing critical thinking and independent learning skills is essential in higher education, yet students often struggle to engage meaningfully with academic reading and writing tasks when using Generative AI (GenAI) tools. This classroom-tested strategy implements a structured scaffolding approach to help students transition from AI dependence to AI as a learning partner, fostering metacognitive awareness and deeper engagement with academic content.

The intervention guided students through AI-assisted reading and writing tasks, followed by structured reflection exercises to critically evaluate AI-generated outputs. Over time, AI reliance was reduced, prompting students to refine their analytical and self-regulation skills. Findings showed greater autonomy, improved critical thinking, and increased engagement in reading and writing tasks.

This approach is transferable across disciplines, including STEM, social sciences, and hybrid learning, by adapting AI-supported tasks and reflective scaffolding techniques to develop discipline-specific analytical skills. This session provides practical strategies for educators seeking to integrate AI while reinforcing effortful learning and academic autonomy.

4. AI for Revision

Jingsi Shen, Clinical Assistant Professor, Writing Program, NYU Shanghai

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Abstract: “AI for Revision” is an interactive activity that integrates AI into the writing and revision process, encouraging students to critically engage with AI-generated feedback while refining their work. This strategy develops critical thinking and writing skills by guiding students through an iterative revision of a specific paragraph from their essays. Using targeted prompts, students interact with AI tools, assess the effectiveness of AI suggestions, and reflect on their writing decisions. Students demonstrated high engagement throughout the activity, and their reflections highlighted both the strengths and limitations of AI tools, as well as a deeper awareness of their own voice as writers. This approach is adaptable to any course incorporating writing or essay assignments and is also relevant for classes exploring digital literacy and responsible AI use.

Session Introduction

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.

1. Listening Journals to Build Metacognitive Skills

John Jordan, Senior Lecturer, English for Academic Purposes, NYU Shanghai

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Abstract: Listening instruction has several challenges: the invisible nature of listening, learners’ limited awareness of listening processes, reliance on product-oriented approaches, and learners’ anxiety and lack of confidence. For the last three years, the presenter's EAP course has been tackling those issues by having students engage in metacognitive practice, using regular writing in listening journals. Writing twice a week in Google Doc journal shared with the instructor, students document their listening experiences; observe and evaluate impressions, performance and strategy use; and use this observation to inform their understanding of themselves as learners. This metacognitive approach produces learners who understand the challenges of listening in a second language, think about their learning development, and habitually make plans to self-direct and manage their progress in listening. Additionally, the GenAI application NotebookLM was used to produced podcasts listening journals that students listened to as a further reflective tool. Student work, feedback, and evaluation have shown the listening journals to be meaningful and impactful in both improving listening and forging better learners. Habitual writing about learning combined with reflective practices is a powerful tool for any course developing student skills in a challenging area, providing empowerment for students and insight for instructors. 

2. Fostering Independent Critical Thinking through Logical Reasoning in the Classroom

Allison Airhart, Senior Lecturer, English Language Center, Liverpool Jiaotong University

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Abstract: This talk will demonstrate how to integrate logical reasoning into the classroom through engagement with popular and academic debates, fostering independent critical thinking skills in students and discouraging reliance on AI-generated answers and conclusions. The tasks introduced in the session were developed for a critical thinking component of an ethics course, in which students first built a foundational understanding of argument structure and practiced key reasoning skills (e.g., drawing logical comparisons and recognizing implicit assumptions) in preparation for engaging with contemporary ethical debates spanning technology, the environment, and social justice. This talk focuses on the scaffolded process students followed in applying the reasoning skills to the various debates—some in audio and video formats (such as podcasts and livestreams), others in written form (such as magazine and journal articles). It
presents guided argument analysis tasks that provide a foundation for students to construct their own arguments and refutations. Though challenging, the tasks proved successful in sharpening students’ critical thinking. Throughout the course, students reported feeling empowered by their ability to think more consistently and creatively about issues raised in the lessons and beyond. Because reasoning skills are transferable across fields, this approach can be adapted to diverse academic and professional contexts.

3. A Guided Brainstorming Activity to Foster Critical Thinking about the Social Effects of AI

Junius Brown, Visiting Assistant Professor, Political Economy, Duke Kunshan University

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Abstract: This teaching strategy develops students’ critical thinking about AI, and in particular, its socio-political dimensions: how AI tools are developed and deployed, who controls and benefits from their implementation, and their effects on society. It takes the form of a structured activity in which students first brainstorm answers to questions in small groups, then share their answers in a class-wide discussion. I evaluated the effectiveness of this activity using an online survey with both Likert scale and open-ended questions, and found that for several students, this was their first time evaluating AI based on its social effects rather than its capabilities. Though initially designed for a Political Economy course, this lesson module can easily be transferred to courses in other disciplines.

4. Applying Playback Theatre–Inspired Exercises to Strengthen Students’ Active Listening

Yanyue Yuan, Undergraduate Coordinator of Interactive Media and Business (IMB), Assistant Arts Professor of Interactive Media Business (IMB), NYU Shanghai

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Abstract: This presentation explores a strategy for strengthening active listening, a foundational component of problem-solving in project-based learning settings that involve user interviews and peer reviews.

In a Fall 2024 "Design Thinking" course, I co-designed two workshops with a Playback Theatre performer, integrating body movement and role-play to cultivate deeper engagement. Preliminary findings from in-class observations, student reflections, and interviews suggest that these exercises heighten awareness of active listening while fostering a more engaging and supportive learning environment.

This approach is adaptable across disciplines where attentive listening and peer learning are valued.

Session Introduction

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.

1. Meaningful Assessment in the Common Core: Three-Day Simulations and Oral Exams

Jan Hua-Henning, Assistant Professor of the History and Philosophy of Science and Technology, Division of Arts & Humanities, Duke Kunshan University        

Kyle Fruh, Assistant Professor of Philosophy, Division of Arts and Humanities, Duke Kunshan University

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Abstract: The common core course Global Challenges in Science, Technology, and Health aims to provide students with the interdisciplinary skillset to analyze global challenges and propose actionable solutions. The course uses two assessment strategies: simulations and oral exams. The two three-day simulations serve as the main assessment. Students respond to a transnational scenario (e.g., disease outbreak) in science, technology, and health. Each simulation is structured into three phases: research sharing, argument presentation, and an open forum. Students work together in stakeholder groups. The activity requires effortful research and analysis, informed judgment, goal-oriented argumentation, and open, transparent discussion. Course evaluations and feedback are overall positive. Students appreciate the selection of meaningful scenarios and challenges. Engagement is high, as students must respond to faculty and peer questioning during the simulation. Some students find the group component challenging, but oral exams provide a counterweight and chance for individual assessment. Initially, oral exams were summative, while simulations were authentic assessments. However, oral exams have evolved into authentic experiences that require knowledge application, independent research, and effective communication. The class emphasizes experiential learning. In-class activities serve as preparation for both simulations and oral exams. 

2. Developing Synthesis: In-class Tests to Foster Academic Integrity in the AI Era: A Case Study from a Year 1 EAP Module at a Transnational University

Jiashi Wang, Language Lecturer, School of Languages, Liverpool Jiaotong University

Shuangxin Zhang, Language Lecturer, School of Languages, Liverpool Jiaotong University

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Abstract: The rise of artificial intelligence (AI) has made it easier for students to generate academic content, raising concerns about academic integrity and the reliability of traditional assessments (Yeadon et al., 2022). While AI detection tools exist, they are not always reliable (Kumarage et al., 2023), necessitating a shift in assessment design to ensure student learning and intellectual ownership remain central.

This presentation examines how synthesis—a key academic skill—was fostered through in-person, closed-book tests in a Year 1 Advanced English for Academic Purposes (EAP) module. Aligned with Jisc’s (2023) AI in assessment framework, we adopted the "avoid" strategy by implementing:  integrated summary writing – a closed-book test requiring students to synthesize ideas from a reading passage and lecture, ensuring independent critical engagement; source-based group discussion – a structured, in-person speaking assessment emphasizing critical thinking, synthesis of multiple sources, and spontaneous idea development.

While students used Generative AI during preparation, assessments ensured authentic demonstration of skills. AI was also leveraged to create rigorous, contextually relevant test materials. Performance data indicate these assessments effectively enhance academic integrity and foundational skills. The Integrated Summary Writing and Source-Based Group Discussion assessments can be transferred across disciplines by adapting their core principles to subject-specific content.

3. Putting Humanity Back into Feedback – Approaching Feedback as a Diegetic Process

Garrett Durkee, Professional Development Officer, Centre for English Language Education, University of Nottingham Ningbo China

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Abstract: One of the most vital forms of feedback in higher education is formative assignment feedback that builds long-term towards the course-required, summative assessment (Biggs, 2014). However, research has demonstrated that only 58% of Chinese university students understand teacher feedback, and only 15% of teacher written feedback was considered ‘objectively sound’ (Lee, 2019). This is being further exacerbated by the ever increase accessibility, prevalence, and preference of AI generated feedback among learners (Escalante, Pack & Barrett, 2023). This presentation will highlight the classroom-proven technique of implementing feedback as a process, rather than a product, through the use of diegetic feedback video recordings. Ongoing use of this strategy has created feedback that is not easily appropriated by AI, feedback that authentically feeds forward into student engagement with assessments, and feedback that is valued by learners without increasing teacher workload. The examples used in this presentation will represent feedback for written essays, but this process is easily transferable across disciplines for a variety of assignment types. This diegetic, process-approach to feedback leaves the robotic aspects of feedback to be handled by robots, allowing teachers to focus on the humanistic aspects.

4. Role-Playing Pedagogy for Historical Analysis: Simulating the 1929 Republic of China Central Health Committee Conference

Liangliang Zhang, Assistant Professor of Global China Studies, Global China Studies, NYU Shanghai

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Abstract: This classroom case study explores a role-playing simulation in Medicine in China, where students reenacted the 1929 Central Health Committee Meeting in the Republic of China—a pivotal debate over abolishing indigenous Chinese medicine. The activity examined how the socio-political and economic contexts of early 20th-century China, along with attendees' backgrounds and biases, shaped this crisis in Chinese medical history.

Over 20 students took on historically grounded roles, including government officials, Western-trained doctors, medical educators, and journalists, alongside fictionalized Chinese medicine practitioners and patient advocates—voices absent from the original conference. ChatGPT was leveraged to streamline the creation of detailed, student-centered role descriptions. The simulation generated intense debate, culminating in students overwhelmingly rejecting the abolition proposal—an outcome starkly opposed to historical reality. A post-simulation reflection encouraged students to critically and empathetically assess the motivations of historical actors while deepening their understanding of the era’s medical and political tensions.

This immersive approach heightened student engagement while strengthening historical and ethnographic analysis skills. By bringing a key historical moment to life, the activity transformed a specialized topic into a dynamic learning experience, demonstrating the power of role-playing pedagogy to foster deeper intellectual and emotional connections with course material.

Session Introduction

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.

1. AI as a Plus: A Collaborative Workshop on Skimming and Scanning Reading Skills for Source Selection

Vanessa Lawrence, Instructional Services Librarian, NYU Shanghai

Catherine Journeaux, Senior Lecturer, EAP, NYU Shanghai

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Abstract: This collaborative workshop focused on teaching students essential reading skills (skimming and scanning) in combination with critical thinking in the specific context of selecting sources from a list of library search results. The workshop presented these core skills along with supplemental generative AI methods students could use, and offered them the chance to critically reflect on the suitability of these methods for different contexts. A goal of the workshop was to emphasize through workshop structure the necessity of a grounding in these core skills in order to evaluate the efficacy of generative AI tools. This workshop took place in the larger context of the “Research Foundations + AI” workshop series, which implemented a similar approach and structure across four different skill-based workshops. Not only is the teaching approach transferrable to other teaching contexts, so too are the foundational research skills targeted in each workshop.

2. Discovering Your Voice with AI

Layla Shelmerdine, Senior Lecturer, Language & Culture Center, Duke Kunshan University

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Abstract: As AI writing tools become more prevalent, students must learn to engage critically with them while maintaining their unique writing voice. Discovering Your Voice with AI, a mini-term course, guided students through structured activities to explore authorship, audience awareness, and AI-assisted writing.
Students compared AI-generated and human-authored texts to analyze differences in style, tone, and emotional depth. They revised AI-generated content to reflect their voice, adapted AI writing for different audiences, and debated ownership in AI-assisted writing through structured discussions with ChatGPT.
Reflections and discussions revealed that while AI enhances efficiency, it struggles with personal expression and rhetorical nuance. By helping students recognize their voice and use AI responsibly, this course offers a possible framework for integrating AI literacy across disciplines.

3. Leveraging ChatGPT for Scaffolded Writing and Critical Thinking: A Sandwich Model Approach

Ruth de Llobet, Writing Program, NYU Shanghai

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Abstract: In the course Perspective on the Humanities – The City as Text: Southeast Asia Cities (NYUSH), students were guided through a series of scaffolded exercises to construct a literature review, using ChatGPT as a feedback tool. The exercise aimed to help students build confidence in their writing and enhance their critical thinking skills by leveraging AI to refine their work. Key challenges observed in second-year students included difficulty with creating detailed analyses and establishing clear connections between sources. Given these challenges, students tended to underutilize ChatGPT, using it improperly to write or fix minor issues rather than improving their overall analysis. To address this, I designed a “sandwich model” approach: first, students wrote independently, followed targeted feedback based on a pre-designed prompt in line with rubrics from ChatGPT that required students to assess recommendations and make a choice on what to focus on their feedback  on, e.g., clarity of the summary, relevance and credibility of the sources, depth of analysis, quality of writing and then a final revision based on that feedback. This approach not only helped students refine their work but also encouraged them to develop a more sophisticated understanding of their sources, moving beyond general summaries. The results were successful, as students produced more refined, cohesive, and analytical literature reviews, and developed a relational understanding of sources based on the assessment to students' interaction and their reflections. The exercise demonstrated the value of using scaffolded exercises and AI tools in enhancing writing quality, promoting deeper analysis, and encouraging critical thinking. The approach also emphasized how ChatGPT could be used constructively to foster engagement and improve writing without undermining the learning process.

4. Developing Critical Research Skills with SCOPUS AI and DeepSeek: Evaluating Sources Using the CRAAP Standards

Russell Frank, PhD, EAP Course Tutor, Centre for English Language Education, University of Nottingham Ningbo

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Abstract: This presentation highlights a practical, classroom-tested strategy to help students in a foundational year program develop critical research skills using SCOPUS Kimi AI, and Deepseek for source discovery. The challenge of the current digital research landscape is ensuring students can identify reliable sources and critically assess their relevance to their research projects. Using SCOPUS AI, Kimi AI and Deepseek, students locate sources relevant to their research topics. To evaluate these sources, students apply the CRAAP standards—Currency, Relevance, Authority, Accuracy, and Purpose—ensuring they select high-quality, credible information. I will demonstrate the "Review, Evaluate, Re-prompt (RER)" method, which guides students through an iterative process of refining their searches, evaluating the sources they find, and re-prompting AI tools for more targeted results. The session will provide examples of how this approach improves students’ ability to critically analyze and select appropriate research materials. Evidence of its impact on student engagement and the development of inquiry skills will also be shared. Educators will leave with actionable techniques for integrating SCOPUS AI, Deepseek (or other generative AI tools), and the CRAAP standards into their own classrooms, fostering students’ independent, critical thinking skills in research.

Session Introduction

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.

1. Scaffolding Real-World Language Learning: A Multimodal Adventure of Community-Engaged Approach Beyond the Classroom

Jing CHAI, Senior Lecturer of Chinese Language, NYU Shanghai

Qian LIU, Senior Lecturer of Chinese Language, NYU Shanghai

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Abstract: While studying in Shanghai, students are surrounded by a rich target language environment, yet they often struggle to engage in meaningful conversations with locals. Chinese language classrooms frequently simulate real-world interactions, but authentic engagement remains limited. To bridge this gap, I sought to design scaffolded experiences that would foster deeper student interactions with local communities. However, finding a compelling theme that interests both learners and native speakers—without relying solely on traditional language exchange—was a challenge.

2. Fostering Self-Directed Learning & Industry Engagement in Business Education: A Case Study from RTCM

Yinghong Wang (Rayn), Graduate and Advanced Education, NYU Shanghai

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Abstract: Fostering self-directed learning, metacognition, and industry engagement is essential for preparing students for a rapidly evolving workforce. The Retail Technology and Channel Management (RTCM) course at NYU Shanghai integrates structured reflection, mentorship, and real-world application to cultivate analytical thinking and decision-making.

The course emphasizes student ownership through self-directed learning and iterative reflection. Students actively engage with industry-relevant challenges, connecting course concepts with real-world insights. AI tools, such as MidJourney, serve as aids—helping students visualize ideas—while structured mentorship ensures they critically evaluate and control their use of technology rather than rely on it passively.

Industry engagement plays a pivotal role. Guest speakers from Amazon, Tencent, and Ogilvy provide real-world perspectives, while consultation exercises with external mentors challenge students to justify and refine their ideas before executive reviews. Competitive group projects and mock CMO vs. CFO debates further develop their ability to assess trade-offs and defend strategic decisions.

Student feedback highlights significant growth in analytical skills, strategic reasoning, and confidence in leveraging AI responsibly. This case study demonstrates how structured reflection, mentorship, and industry collaboration empower students to take ownership of their learning, equipping them with adaptability and decision-making skills for the future.

3. Scaffolding Creativity: Integrating AI in Business Education

Nicole Wang, Interactive Media & Business, NYU Shanghai

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Abstract: This session introduces a three-phase model for integrating generative AI into business education to scaffold students’ creative and critical thinking skills. In Phase 1, students explore tools like ChatGPT through guided prompts to build foundational AI literacy, supporting creative ideation and inquiry into unfamiliar topics. Phase 2 combines AI-assisted brand creation with real-world experiences, including supplier outreach and market observation, allowing students to validate and refine AI-generated insights. Phase 3 introduces multimodal tools to support product visualization and storytelling.

4. Enhancing Oral Fluency & Metacognition Through Video Projects in Language Learning

Jessica Brümmer, German Department, NYU Berlin

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Abstract: This presentation details a video project in elementary German classes, developing writing, oral fluency and metacognition by engaging students in authentic communicative tasks and reflective practices during video creation. The core teaching strategy is a collaborative project-based approach, where students work in groups to create scripted videos, optionally utilizing AI tools to analyze and refine pronunciation, or generate personalized feedback on grammar, thus enhancing language learning. Evidence of impact was significant. Student engagement was exceptionally high, manifested in enthusiastic participation and creative output, as observed in class and through video production quality. Student reflections and feedback data demonstrate increased confidence and fluency in oral communication, alongside heightened awareness of their learning processes. This collaborative, project-based video strategy, optionally leveraging AI for language analysis and feedback, is adaptable across disciplines by providing a structured framework for students to practice and improve oral communication and presentation skills while reflecting on their learning, through a media-rich, engaging format.

Faculty-Student Panel

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.

NYU Shanghai Faculty Panelists:

• Lihua Xu, Area Head of Computer Science, Professor of Practice in Computer Science, NYU Shanghai
• Pekka Santtila, Professor of Psychology, NYU Shanghai; Global Network Professor, NYU New York

NYU Shanghai Student Panelists:

• Jiale (Cecilia) Zheng, Honors Math & Data Science,  Class of 2025, NYU Shanghai
• Mateo Rengifo Orozco, Business and Finance, Class of 2025, NYU Shanghai
• Deziree Harmon, CTL Research Assistant, Interactive Media & Business, Class of 2025, NYU Shanghai

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