Lietz, R. (CM) – Reflecting on Failure: Designing and Evaluating Archetype Profiles as a Tool for Self-Reflection

Self-reflection holds significant potential for learning, behavior change, and emotional processing, yet designing technologies that effectively support it remains challenging, particularly when reflection involves difficult experiences such as failure. Most current technologies avoid negative experiences altogether, leaving users without support at precisely the moments when reflection could be most valuable.
This dissertation investigates how technology can better support self-reflection through three mixed-methods studies. The first examines how people experience and reflect on failure, revealing how identity, self-blame, and emotional avoidance create barriers to productive reflection. These findings informed an iterative design process through which archetype profiles emerged as a promising reflective format. The second study evaluated archetype profiles against standard graph-based visualizations, finding that the quiz-profile sequence effectively scaffolded reflection by supporting emotional re-engagement followed by cognitive reframing. The third study extended this work into a collaborative context, examining archetype profiles derived from sleep tracking data as shareable artifacts for social reflection. Across these studies, this dissertation contributes empirical insights into reflection on failure and design knowledge about archetype profiles as a reflective format.

Event Host: Rebecca Lietz, Ph.D. Candidate, Computational Media

Advisor: Steve Whittaker

Zoom: https://ucsc.zoom.us/j/7855885795?pwd=RS9mWXhQOXNyNmRVSzQrd1MzamJVQT09

Passcode: 172404