Oxford-style debate supported by ScholarStack AI. House Motion: This House believes that wisdom cannot be synthesized by AI. Patrick Dempsey (Proposition) vs. Anand Rao (Opposition). Floor vote before & after; moderated Q&A.
ScholarStack AI is a B2B platform that positions itself as "AI infrastructure" for higher education, giving institutions, faculty, and students a governed alternative to informal use of tools like ChatGPT. Rather than letting AI simply hand students answers, it uses guided, Socratic-style... Read More →
Global decline in reading motivation has coincided with educators assigning fewer whole books. Moreover, teaching reading has become challenging as AI offers automated-summaries, allowing students to skip deep reading. Drawing on research from the neuroscience of reading, this interactive session will address questions from both the instructors’ and students’ perspectives:What is the purpose of reading? If AI can summarize a text, what are the pedagogical implications for reading instruction?How is reading interconnected with writing and other multimodal ways of learning? What cognitive capacities are lost when reading becomes optional?What teaching practices in Liberal Arts colleges can be advantageous to make reading meaningful? Using concrete pedagogical approaches from Amherst, we will investigate how AI is reshaping students’ relationship with reading. These examples will help us together probe the ways that reading functions not an isolated skill but rather as a multimodal, social, and intellectually resilient experience.
Director of Technology for Curriculum and Research, Amherst College
Jaya Kannan is Director of Technology for Curriculum and Research at Amherst College, where she leads the Academic Technology Services unit. She holds a PhD in Computer Assisted Language Learning and her higher education background spans international teaching, faculty development... Read More →
As many campuses begin adding AI tools into their classrooms, there is immense pressure to figure out how to quickly implements these technologies in order to avoid being left behind. As digital humanists, though, we also emphasize incorporating new technology carefully and critically which often contrasts with the ways these technologies flood bland, AI generated text into our classrooms. To this end, the presenter will offer his approach and lessons learned from implementing an assignment sequence that required students to “audit” the outputs of generative AI platforms. Students worked in small groups to develop a report that assessed the accuracy and effectiveness of the genAI platforms’ source use. In treating AI technologies as a site for critical inquiry, students acquired a more nuanced understanding of AI hallucinations and a greater appreciation for how academic sources support arguments.
I build the AI systems that liberal arts educators worry about. Seven years of designing enterprise cloud and AI platforms for higher education and healthcare has produced an unexpected conviction: the more capable these systems become, the more indispensable the liberal arts skills they cannot replicate. This session names the paradox directly. The same tools that automate writing also raise the bar on judgment about what should be written. The same models that summarize at scale make source criticism a survival skill, not a humanities luxury. Drawing on three production case studies advising, hiring, and public communication .I will trace where AI fails, why it fails in those specific places, and how that maps onto the disciplinary strengths of a liberal arts curriculum. Participants leave with a shared vocabulary for talking to students and employers about the work AI cannot do and the work it makes more valuable.
This hands-on workshop uses a tabletop role-playing game format to build practical AI literacy in an engaging, low-stakes environment. Participants take on characters facing real-world scenarios, such as drafting a research paper, responding to a workplace email, evaluating a suspicious source, and must decide how, when, and whether to use AI tools to help. Dice rolls and simple game mechanics introduce chance and consequence (a "critical fail" might mean an AI hallucination slips into a report; a "success" might mean catching a bias in a generated summary), turning abstract concepts like ethical decision-making, verification, bias, and academic integrity into lived experience rather than lecture material.
Artificial intelligence has intensified a question many educators were already beginning to ask: What evidence truly demonstrates learning? For decades, higher education has relied on products—papers, exams, presentations, and projects—as proxies for student understanding. Generative AI challenges this assumption by making it increasingly difficult to determine whether a finished product reflects a student's own thinking. While many institutional responses have focused on detection, surveillance, or restrictions, this workshop explores a different possibility: What if AI is not simply creating an assessment problem, but revealing one that has existed all along? Drawing on experiences redesigning undergraduate and graduate courses through ungrading, authentic assessment, and AI-integrated pedagogy, participants will examine how process-centered approaches can make learning more visible while preserving student agency. Through examples of self-assessment, reflective learning narratives, revision cycles, and AI transparency practices, attendees will explore ways to shift attention from evaluating products to cultivating evidence of growth, judgment, and engagement. Participants are encouraged to bring an existing assignment or assessment practice to the workshop. Using a guided redesign framework, they will identify opportunities to incorporate reflection, process documentation, feedback loops, and authentic engagement in ways that center human learning in AI-rich environments. Situated within the liberal arts tradition, this workshop embraces the paradox that AI simultaneously challenges and clarifies the value of education. As machines become increasingly capable of generating polished outputs, the most meaningful aspects of learning may be those that are difficult to automate: curiosity, ethical reasoning, self-awareness, intellectual risk-taking, and the ability to make meaning from experience.
Narrative is deeply embedded in everything from our personal habits to socioeconomic guidelines and the operation of digital systems. This presentation introduces how—by connecting the study of literature to daily interactions with these systems—we can increase the value students discover in their literature courses, and better communicate how they apply that value to their personal and professional goals. Through this process, systems like social media, algorithms, and AI become organic topics of discussion in context of story structure and narrative form. By articulating how the study of narrative unlocks the tools and techniques of systems designed to gain our attention and stir emotion, students learn to use those same tools and techniques to take greater agency in the control of information and their own meaning-making. Practical uses of AI will be explored that supplement and augment this process, without diminishing practice of critical skills.
Director of First Year Writing/Assistant Professor of Practice, University of New Haven
Ryan Crawford is Assistant Professor of Practice and Director of First-Year Writing in the Department of English at University of New Haven. His research, including the book Emotional Value in the Composition Classroom: Self, Agency, and Neuroplasticity, combines neuroscience, composition... Read More →
Academic Integrity in the Age of AI (Bertram Gallant, Davis, & Khan, 2026) includes a speculative fiction story imagining a university in 2045, a future in which institutions layer AI onto outdated teaching and assessment models instead of rethinking academic integrity for this new era. This pop-up book club uses that story to spark conversation across two 30-minute sessions. No advance reading required - we'll hand out short quotes to react to on the spot. In the first session, we'll dig into where our own institutions already feel like they're drifting toward that imagined future. In the second session, we turn toward alternatives: what could a better path actually look like? Each session stands on its own, so come to one or both.
AI is compressing the timeline from idea to publication—but faster doesn't have to mean sloppier. In this 30-minute session, Second Draft Labs, a new publishing company, walks through their publishing process, showing how AI tools can accelerate drafting, editing, and production without sacrificing the judgment and craft that good publishing depends on. Attendees will leave with a clear picture of what a modern, AI-assisted publishing workflow actually looks like in practice, where human editorial decisions still matter most, and a roadmap for getting published.
Oral assessments are often proposed as an “AI-resistant” alternative to written assignments that foster cognitive skills that are especially important in an AI-infused world, such as empathy, conversational communication, and situated-decision making. The unique opportunities offered by oral assessments, however, also come with unique equity challenges that require creative and potentially unfamiliar solutions. Students’ lack of practice with the format, anxiety and performance stress, language and cultural barriers, and neurodiversity (including differences in processing time, speech, and social fluency) all constitute hurdles for equitable assessment, particularly for instructors who have never designed an oral examination. In this session, we will explore these risks, identify strategies for designing and implementing assignments that reduce their impact, and apply those strategies to participants’ specific instructional contexts. Participants will leave the session with a clearer understanding of the equity challenges associated with oral assessment, knowledge of concrete techniques for addressing them, and at least one new or reformed assignment that incorporates inclusive oral assessment components ready to be implemented into their existing courses.
At Amherst College, Mead Art Museum and Academic Technology Services work to apply innovative applications of technology including enhancement of digital accessibility. Emerging AI technology has recently brought us together in collaboration focused on making the Mead’s digital collection more searchable, discoverable and accessible through the production of multimodal collection descriptions.In this workshop, we share an activity we have developed with relevance to art pedagogy in the classroom: inviting community members to critically evaluate the technology’s potential for good when responsibly applied to a specific context, and to lend their voices to make a direct impact. Participants may bring their own device to try the activities themselves.Our larger project centers student engagement and participation in developing the project’s workflow and evaluation. We will discuss how to further trustworthy museum metadata, how to facilitate critical evaluation of the potential benefits from AI applications, and propose models for peer institutions.
Prakhar is a rising junior at Amherst College, pursuing a triple major in Computer Science, Mathematics, and Economics. He is deeply interested in leveraging emerging technologies to solve interdisciplinary challenges and advance accessibility initiatives. With experience working... Read More →
Andres is a rising sophomore at Amherst College, pursuing a double major in English and Mathematics. He is curious about the applications of AI in a range of fields, including museums. He is passionate about channeling his curiosity of AI into learning about the various ways by which... Read More →
Doug Hall provides support across the disciplines for academic research computing and emerging technologies. This includes pedagogy-driven consultation and workshops for high performance computing and artificial intelligence applications. He has a Ph.D. in Polymer Science and Engineering... Read More →
Manager of Collections Access and Academic Engagement, Mead Art Museum, Amherst College
Dr. Miloslava Hruba is an accomplished museum professional and researcher dedicated to bridging the intersections of art collections, pedagogy, and digital accessibility. Her current work focuses on the ethical integration of generative AI within academic programming, exploring how... Read More →
Colleges and universities have barely begun to evaluate the risks and rewards of ubiquitous AI use on their campuses. This session introduces a framework for assessing AI readiness and risk in divisions, departments, centers, and programs. This presentation will highlight key research, legal precedents, and strategies for identifying gaps between policy and pedagogy. Using an experiential approach, attendees will have space to reflect on the profound AI-related changes taking place and consider which roles or areas are most exposed to AI-driven change. Organized into six readiness domains, the session aims to help participants develop a practical, data-driven approach that supports student learning and academic integrity while managing the changing landscape of faculty and staff work. Participants will also have the opportunity to complete a brief AI readiness and risk survey, which offers a diagnostic starting point for administrative or department heads, program or staff leaders, and task force members.
From the ancient Greeks forward, liberal arts education has never been only about storing information. It has been about forming judgment through practice: rhetoric in the agora, philosophical dialogue, ethical deliberation, and the disciplined use of language in public life. Oratory, dialectic, and disputation were not simply ways of displaying knowledge, but of testing whether a person could think, respond, persuade, and act wisely in context. As generative AI unsettles traditional assessments, this older tradition becomes newly relevant. This presentation argues that AI-powered simulations can recover something essential to liberal arts learning by shifting assessment from static recall to situated performance. Using GENESIS as a case example, this talk will explore how conversational, competency-based simulations can make visible the capacities the liberal arts have long aimed to cultivate: judgment, communication, ethical reasoning, interpretive agility, and the ability to use language as action. Rather than abandoning the humanistic tradition, simulations may help us reclaim it in a new form.
This session includes the following four talks: 10 minutes for each presenter with 20 minutes of Q&A for the group. 1. Hegel, Mastery and Servitude, and the Pathologies of AI Michael Reno | University of Mary Washington 2. Scaffolding Rhetorical Authority through Intentional Failure Jeffrey L. Jackson | State University of New York Cortland 3. Tools of One's Own: Portable Prompting and the Iterative Craft of Professional Identity Ben Harwood | Skidmore College 4. Adding Nuance to Student AI Refusal Annabel Rothschild & Theresa Law | Bard College
This workshop is designed for educators who want to help students learn how to formulate meaningful questions as researchers and thinkers in the liberal arts while creating classroom spaces where critical engagement with AI can occur.First we will share artifacts from Pratt Institute classrooms that highlight faculty and student exploration of new forms of inquiry. Second, we will introduce conceptual maps created within our faculty learning community as tools for “charting new courses” in an AI-infused educational landscape. Together, these artifacts model an open, experimental, and collaborative approach to learning that prioritizes process over product and illuminates the power of the human dimension of education in response to the current technological shift. After discussing these materials, participants will engage in a conceptual mapping activity adapted from our faculty learning community, followed by reflection and assessment exercises that can be applied in their own teaching contexts.
This lightning talk introduces Iterative Failure Tracing (IFT), a framework that reframes generative AI errors as catalysts for critical inquiry. While Large Language Models threaten to replace student effort, their propensity for noun-heavy syntax and factual hallucinations creates a productive validation burden (Sanz-Tejeda et al., 2026). By identifying these critical incidents, students transition from the success trap of passive acceptance to genuine rhetorical authority (Colby, 2025). My presentation demonstrates how prompting as writing functions as a rigorous rhetorical act. Drawing on sabbatical findings from 42 student artifacts, I illustrate the metacognitive shift that occurs when students perform linguistic repair on AI output (Graham, 2023). Finally, I will examine how to scaffold assignments that require students to locate and correct AI failures, ensuring the human writer remains the primary agent of meaning-making in the liberal arts tradition.
Jeffrey L. Jackson, PhD, is an Instructor of First-Year Composition at SUNY Cortland with over 20 years of experience teaching writing at the university level. He earned his doctorate in Mass Communication from Syracuse University, where his research focused on identity and moral... Read More →
Many students use AI passively, and AI literacy is often taught apart from disciplinary work, so students graduate owning neither their nascent professional identity, their digital presence, nor their AI workflows. Crafting Digital Identity answers that gap by teaching tools of one's own. Because its real content is the students themselves, the course is interdisciplinary by design. Students build a Creative Thought Journey, a story-driven digital narrative of their learning on Skidmore Domains, and design custom AI bots they can keep. The lesson is portability: once you learn to prompt, on BoodleBox or any platform, the skill travels with you. Professional identity develops the same way, through iteration and revision across text, audio, and video. Run as a platform pilot, the course treats AI as a liberal arts question of identity, authorship, and reflection, and shows how ownership turns AI from a force that flattens voice into one that amplifies it.
Ben Harwood works as an instructional designer in the Learning Experience Design and Digital Scholarship (LEDS) group in the Information Technology office. He partners with community members to analyze and support technology needs and offers instructional opportunities that promote... Read More →
Bard College students often have an unusually steadfast position of AI refusal, resulting, for example, in campus protests against a planned generative AI promotional event and reticence to engage in assignments that necessitate thinking with AI. We are both heartened and concerned by this stance. While students are finding their voices, their standpoint is based on a limited understanding of AI as a technology and sociotechnical phenomenon. Here, we describe our efforts to help students better understand how generative AI works so that they can communicate their position to various stakeholders, including post-graduate colleagues and managers. As students graduate into a working world which increasingly demands the use of generative AI systems, they will be confronted with pushback on their stance; our intention is not to dissuade them, but to help equip them with the critical AI understanding and literacy that they will need to explain and justify their position.
"The sleep of liberal arts produces AI." At the opening of the previous symposium, the keynote speaker shrewdly put forward this statement, proposing the liberal arts education to stay awake in the age of AI. At Colby College, the Davis Institute for Artificial Intelligence endeavors to integrate the two, interrogating and experimenting a liberal arts education organically intertwined with AI. In collaboration with academic and administrative departments across campus, Colby has initiated a responsible AI ecosystem for research, learning, and entrepreneurship. We are developing a multitude of AI programming by situating faculty, students, and staff at the center, while piloting privacy preserving and cost-effective technical infrastructure for campus use. During this session, we will share our approach to a responsible AI ecosystem, attempting to carve out a space and time for the audience to think through a practical AI integration in the context of their home institution.
Vibe coding — building working software through natural-language conversation with AI rather than traditional programming — has quietly removed the technical barrier that once kept faculty and students from creating their own interactive learning tools. This session embodies the symposium's central paradox: the same capability that lets a student generate code without understanding it can let a humanities professor build a simulation that finally makes an abstract concept click. In thirty minutes, participants watch a fully playable classroom simulation emerge live from a plain-language prompt, then interrogate what that means for learning. When a literature, economics, or government instructor can prototype a simulation in minutes, who is doing the thinking — and is that a problem or a breakthrough? Participants leave with a shared, honest framework for deciding when vibe-coded simulations deepen understanding and when they short-circuit it.
The rapid integration of artificial intelligence into higher education has created an urgent and widespread need for course redesign, yet most institutions lack the time, funding, and staffing to support faculty at scale. This presentation introduces a structured, AI-assisted course redesign protocol developed at the Yale School of Public Health to address this gap. Designed to be completed in a single two-hour sitting, the protocol guides faculty through a ten-step process that audits learning objectives, assesses AI substitution risk at the assessment level, redesigns for process visibility, authentic student thinking, optional AI integration, and generates ready-to-use syllabus language — all without altering the fundamental nature or intent of the course. Early piloting with YSPH faculty has yielded consistently positive responses, with participants reporting renewed confidence and inspiration around assessment redesign. Attendees will leave with a replicable framework they can adapt and deploy at their own institutions.
At a time when headlines suggest AI use among students is rapidly accelerating, Denison University’s second How I GenAI survey revealed a more complicated (and surprising) story. This session explores unexpected findings about how students are actually engaging with generative AI, including shifts in usage patterns, student concerns, trust, academic integration, and evolving attitudes toward AI tools.Alongside survey insights, we’ll highlight initiatives from Denison’s AI Student Ambassador program, where students are helping shape campus conversations around AI literacy, responsible use, creativity, and career readiness. Through peer-led programming and collaborative experimentation, students are playing an active role in defining what thoughtful AI engagement can look like at a liberal arts institution.Participants will leave with practical ideas for gathering student input, designing student-centered AI initiatives, and creating spaces where students can critically and creatively engage with emerging technologies in meaningful and values-driven ways.
Associate Vice President of Digital Innovation, Denison University
Heath Hase’s distinguished career in academic technologies and IT leadership has spanned key roles at esteemed institutions such as Southeast Missouri State University, the University of North Carolina, William Jewell College, and Denison University. Recognized by Apple as a Distinguished... Read More →
Lori Robbins is Denison University's Head of AI Strategy, where she leads campus-wide initiatives focused on AI literacy and professional development. With a background in international education and educational technology, she creates programs that help students, faculty, and staff... Read More →
Academic Integrity in the Age of AI (Bertram Gallant, Davis, & Khan, 2026) includes a speculative fiction story imagining a university in 2045, a future in which institutions layer AI onto outdated teaching and assessment models instead of rethinking academic integrity for this new era. This pop-up book club uses that story to spark conversation across two 30-minute sessions. No advance reading required - we'll hand out short quotes to react to on the spot. In the first session, we'll dig into where our own institutions already feel like they're drifting toward that imagined future. In the second session, we turn toward alternatives: what could a better path actually look like? Each session stands on its own, so come to one or both.
This workshop is for any instructor who has sat in front of a paper wondering whether the words on the page truly represent the work of the student who submitted it. How do we preserve the valuable intellectual work fostered by extended writing projects while maintaining confidence that the submissions we receive reflect what students can actually do? Some instructors seek certainty by moving most writing into the classroom; this workshop explores another approach: building confidence in out-of-class work through low-stakes in-class activities that provide meaningful checkpoints for student capabilities. Starting from the question “What evidence would help me determine whether this student wrote this paper?,” participants will identify the evidence they wish they had and work backward to design activities that generate it. Participants will leave with a collaboratively developed collection of activities that offer snapshots of current student abilities while doubling as scaffolding for learning.
AI provides an unmatched opportunity for both accelerating and degrading high quality learning. Institutions of higher education must adapt by providing guidance to faculty and students across all departments; integrating AI literacy into the larger curricula rather than only covering it in specific computer science courses. In order to most effectively plan and evaluate these actions, we argue institutions implement a capabilities-based framework that understands faculty and students in terms of their capacities and functions in relation to existing college missions to produce socially and intellectually responsible graduates. The four capabilities—Access, Association, Involvement, and Literacy—give faculty, staff, and students a shared scaffolding and vocabulary for preserving the cognitive work genuine learning requires. We illustrate this recommendation through concrete examples across disciplines and work with the audience to brainstorm how they can apply this framework to their own classrooms and institutions.
In this presentation, I'll review the recent data on student attitudes towards AI, which show consistent negative trends in students optimism that AI will make their lives better and their belief that AI itself is ultimately a positive force in the world. I'll then discuss the challenges and opportunities that these trends present for liberal arts faculty and institutions. I'll argue that, within a curriculum that prioritizes critical thinking and open discussion, students' growing antipathy towards AI can be a strength, because it makes them more resilient the totalizing narratives around AI promoted by technology companies and the media, and it makes them more likely to scrutinize their own AI use.
What is a faculty learning community (FLC)? Why is this model so relevant for the topic of AI and the Liberal Arts? This session proposes to answer these questions by introducing the FLC model, which brings together faculty and staff in a community of practice, and to argue for its relevance as a means of fostering interdisciplinary and collaborative connections, debates, and discussions, as well as practical outputs, in relation to the role of AI in higher education and more specifically in the Liberal Arts. Through a demonstration of how to form an AI-focused FLC, interactive activities, and shared resources, this session will leave the audience with the means of forming their own AI-focused FLCs at their home institutions, as well as giving audience members the opportunity to connect with colleagues from a variety of institutions who plan to undertake this same goal.
Visiting Assistant Professor - Francophone Studies, Trinity College
Elisabeth Herbst Buzay is a Visiting Assistant Professor of Francophone Studies at Trinity College. Her research focuses on topics including multimedia medievalism and extraordinary communication, in works ranging from French Medieval literature to contemporary French fantasy works... Read More →
Saturday October 17, 2026 3:30pm - 4:00pm EDT Blaustein 210
As noted at last year’s conference, liberal arts colleges are in a unique and important position to tackle AI and its effect on higher education. A key facet of this position is our ability to encourage critical thinking in our students across a variety of courses, research, and leadership positions on campus. To that end, and as my institutions continues to grapple with its response to generative AI, I formed an AI student council. The AI student council helps develop programming for students, serves as a sounding board for policies and procedures, and helps with communication. The council serves a complement to the AI Community Council, which brings in professionals, alumni, and other friends of the college, into conversation with Eckerd faculty and staff. This presentation talks about why and how to form the student council, setting goals and objectives for the council, and key takeaways.
Assistant Dean for AI and Learning Integrity, Eckerd College
Alexis E. Ramsey-Tobienne is the Assistant Dean for Artificial Intelligence and Learning Integrity and the Director of Writing at Eckerd College, St. Petersburg, FL where she helped launch a new AI studies minor. She also oversees the college's Academic Honor Council and serves on the General Education Committe. Her work examines the intersections of Artificial Intelligence, Faculty Development, Academic Integrity, and Writing... Read More →
What if we trusted them? As institutions scramble to regulate AI, students are positioned as potential cheaters rather than intellectual partners. But Gen Z sentiment toward AI has shifted—many students arrive determined to protect learning, effort, and authentic thinking. This presentation shares what happened when we took that seriously. Over three semesters, we transformed our Language Center into The LAB—a student-led research hub where multilingual students investigate AI's impact on language and meaning-making. Students led every stage: interviewing and hiring peer researchers, organizing our Active Language Forum, shaping research agendas. The results exceeded expectations. LAB students presented research rivaling graduate work. In my Literature and Media Transformation course—which emerged from LAB conversations—students wrote media autobiographies of stunning honesty. When we opened new LAB applications, we received unprecedented, and ambitious proposals revealing how hungry this generation is for these conversations. This presentation offers a replicable model for institutions willing to trust students as co-creators of knowledge. When we give students agency, they lead.
Navigating generative AI in a liberal arts context requires breaking traditional silos to foster campus-wide dialogue. In this interactive workshop, leaders from Smith College share a collaborative framework developed with the Student Government Association and the Sherrerd Center for Teaching and Learning. This partnership bridges the faculty-student divide through an automated syllabus AI policy generator, student-led residential and classroom discussions, and a faculty learning cohort. After a brief showcase of these initiatives, participants will transition into an active session. Working in small groups, attendees will analyze their own institutional ecosystems, identify cross-departmental partnership opportunities and co-design a low-stakes AI literacy project tailored to their home campuses.
Director of Learning, Research and Technology, Smith College
Jean Ferguson is the Director of Learning Research and Technology at Smith College, a joint appointment between the Libraries and Information Technology Services. In this role, she leads a team of instructional technologists, media producers, research librarians, and a scholarly communications... Read More →
Associate Director, Learning Research & Technology, Smith College
Travis is the Associate Director of Learning Research & Technology at Smith College, and is committed to empowering faculty to learn and adopt new instructional technologies in ways that best meet their teaching objectives. He has experience teaching undergraduate classes in blended... Read More →
In a world where students are increasingly expected to graduate with AI experience, providing equitable, affordable and safe access to AI models is becoming a tricky problem for colleges and universities. This session will cover the creation of ChatGBC, Gettysburg College's OpenWebUI/OpenRouter based AI hub. ChatGBC gives all campus members access to multiple AI models plus a built in RAG knowledge base, maintains control of the data submitted to AI models and is reasonably affordable and supportable for a small liberal arts college. We'll cover initial setup, beta testing, scaling for the entire campus, initial faculty and student feedback and data on costs and support requirements.
As artificial intelligence rapidly evolves, liberal arts institutions face a pressing challenge: how do we swiftly update our curricula to meet the demands of students, parents, and employers across nearly all academic domains? Traditional curriculum development can be slow, but the pace of AI requires agility. A solution is an underutilized resource: our students. They bring unique expertise and lived experiences that can drive curricular innovation.This presentation explores three distinct collaborative structures we implemented to partner students with faculty to develop and revise AI-related curricula. We have successfully used these models to co-create curricular materials across disciplines, including creative writing, economics, sociology, cognitive science, and ethics. By leveraging these partnerships, institutions can design course materials that are deeply engaging to students, while allowing faculty to gain vital insights into how students actually interact with AI. When using this approach, both sides of the partnership benefit. Faculty evolve their approach to AI, and students' involvement in curriculum development changes how they approach learning.
Associate Professor of Computer Science, Franklin & Marshall College
I am trying to guide our campus in ethical AI practices. I have been working with students, faculty, and staff to educate them on AI, its strengths, and its weaknesses. I'm also listening to their concerns and how they would like to use AI.
Students, faculty, staff, and administration all have different needs and objectives. Also, faculty from STEM and humanities usually have vastly different experiences with AI and are taking very different approaches. I'm looking to talk with people about how to get people on the same... Read More →
When AI arrived on campus, most institutions responded the same way: individual faculty experimenting in isolation, policy committees deliberating, and a general sense of productive chaos. At Hobart and William Smith Colleges, the Digital Learning Center took a different path: restructuring one role to make AI integration its central focus, then building outward from there. In this interactive session, participants will explore how a single department can catalyze institution-wide AI culture change without a massive budget or a dedicated AI office. Drawing on initiatives including a faculty Community of Practice, a BoodleBox pilot, and intentional strategies for amplifying student voice, this session offers a replicable framework for moving from scattered experimentation to coordinated community effort. Participants will leave with concrete strategies they can adapt to their own institutional contexts and the conviction that meaningful, human-centered AI integration is within reach, regardless of institutional size or resources.
