For over a dozen years at Brown, Dawn King, now Deputy Dean of the College for Curriculum and Teaching Professor in Environment and Society, has been a staunch advocate for experiential learning and community engagement. King has engaged more than 1500 students in her courses Humans, Nature and the Environment and Local Food Systems and Urban Agriculture. Students’ projects with local community organizations in Community-Based Learning and Research (CBLR) courses not only connect course content and theory with practice, but also develop the vital skill of adaptability. As King notes, “One of the learning outcomes that I appreciate the most with my CBLR courses is learning how to be disappointed, learning that, unlike a syllabus in a traditional class, CBL is not linear. There are pivots and obstacles with almost every engaged project. Students get a little aggravated and then have to work through, how do we solve this problem?”
The implications generative Artificial Intelligence has for how professors teach and students learn gives new urgency and importance to the use of high-impact educational practices, including CBLR. Participating in a Sheridan Center-sponsored program this summer, King realized that the list of traits that increase AI resilience overlapped significantly with the qualities of CBLR courses: project-based and process-oriented (assignments at multiple stages of the project), authentic (contextualized and complex, with value beyond the classroom), personally relevant, experiential and reflective. CBLR courses connect students with unique “real-world” learning experiences that interactions with Artificial Intelligence simply cannot replicate. This is powerful for students – and, at a time when both technological and political developments renew existential questions about the relevance of universities, the experience and skills students learn in CBLR courses can serve as a powerful rejoinder to critics of higher education.
Designing AI resilient learning experiences means first acknowledging that generative AI use is already prevalent among students and nearly impossible for instructors to police. As Michael Littman, University Professor of Computer Science and Brown’s inaugural Associate Provost for Artificial Intelligence, noted in a recent letter to faculty, AI detectors are far from foolproof. High error rates can lead to instructors falsely accusing students of misconduct. Open AI, the company behind ChatGPT, even terminated their own AI detection software because of how inaccurate it was at detecting AI generated work. Moreover, the AI tools one student might use to avoid doing work and genuinely learning may be the very same tools that make the course accessible to another student with verified/ documented accommodation. In response to the difficulty of monitoring student use of AI, Brown has convened a special committee that will be developing new guidelines on AI use across the University, including in the classroom. In the meantime, CBLR courses offer possibilities for meaningful learning experiences that are relevant to students’ lives. While no assignment design can prevent every inappropriate use of AI tools, research shows that students are more intrinsically motivated to learn when they feel like the work they are being asked to do has real impact.
At Brown, CBLR courses are designed by faculty to connect students with community partners to investigate important social issues. They facilitate knowledge creation in partnership with community organizations (see examples under “Developing Community Collaborations in Courses” on Swearer’s Engaged Teaching webpage) and allow students to gain skills, competency, and confidence that will serve them at Brown and beyond. This new video about CBLR courses features not only King but also an example of the kind of learning and impact these courses can have. It includes interviews with Emily Qazilbash, a CBLR instructor in Education, Andrea Gonzalez Sanchez from Young Voices, a community partner in the course, Jada Wooten, a Brown alumna who took Qazilbash’s course and then served as CBLR Fellow with her, and current Brown student Marco Lima ‘27, who as a high schooler involved in Young Voices was encouraged to apply to Brown by Jada. This Fall fourteen CBLR courses in eight concentrations are being offered: AFRI 0300: Performing Ethnography and the Politics of Culture, FREN 1410T: L'experience des refugies: deplacements, migrations, and PHP 1810: Incarceration, Disparities and Health, to name only a few.
When designing AI resilient learning experiences, instructors are often encouraged to consider what they want their students to be able to do at the end of the course even if the students have access to and use AI tools. Both CBLR courses and AI resilient learning experiences pay particular attention to experience, skills, and encourage students to demonstrate their knowledge of course content in ways that connect to work in specific contexts. As TJ Kalaitzidis, Assistant Director, Classroom Technology and Innovation, Sheridan Center, notes, AI could also “be integrated within CBLR to expand its potential. For example, students could use AI (with partner consent and safeguards) to translate materials, visualize community data, or prototype communications—always with Critical AI Literacy, reflection, and community validation built in.”
The Sheridan Center for Teaching and Learning will, among other events, facilitate a self-paced, asynchronous workshop titled Assignment Design in the Age of AI October 20-November 3, 2025. If you would be interested in a strategy session with Dawn King and the Sheridan and Swearer Centers specifically about CBLR courses and generative AI – or in a community of practice on developing CBLR courses more generally – please email julie_plaut@brown.edu, Julie Plaut, Director of Engaged Scholarship in the Swearer Center, is also available to consult one-on-one about any existing or potential CBLR course.