AI-Mediated Life Biography Learning Lab is an eight-week, community-centered course that I designed and implemented for an online senior university. The project functions simultaneously as a public good initiative and a design-based research (DBR) environment, exploring how AI-mediated narrative tools can support memory reconstruction, identity development, and intergenerational knowledge building among older adult learners.
As the lead instructional designer, I created the full curriculum—including pedagogical flow, storytelling scaffolds, multimodal prompts, weekly creation tasks, and human–AI interaction frameworks. As the learning-science researcher, I structured the course so that each session generates rich, analyzable multimodal data: oral stories, annotated photographs, thematic clusters, reflective texts, and AI-assisted narrative drafts. These artifacts allow for the study of epistemic agency, narrative reasoning, sensemaking processes, and socio-emotional learning across the lifespan.
In parallel, I collaborated with an edtech engineering team as the co-designer of the AI narrative system used in the course. We developed a low-barrier creative workflow that enables seniors to co-author life stories with AI through iterative refinement rather than one-shot generation. This socio-technical system allows learners to:
- transform fragmented memories into structured chapters;
- negotiate and critique AI output;
- maintain interpretive ownership;
- visualize their reasoning across multimodal traces;
- and ultimately produce a complete AI-generated Life Biography Book.
The “Learning Lab” design blends community storytelling with AI-supported authorship, creating a psychologically safe environment—our “digital story teahouse”—where seniors share lived experiences, co-construct meaning, and act as knowledge producers rather than passive recipients. By the end of the course, each participant produces a personalized biography, while the accumulated classroom interactions offer insight into how AI can scaffold narrative identity, emotional expression, and knowledge reconstruction for populations historically underrepresented in AI research.
This project contributes to emerging conversations in Learning Sciences, human–AI collaboration, multimodal learning analytics, and community-engaged research, while demonstrating how AI systems can be designed to expand—not replace—human voice, authorship, and memory.
Guiding Seniors in Creating Autobiographies with AI: A Results Showcase