Questionnaire measures real moments of unexpected discovery online
The Serendiptionnaire: a Questionnaire for Measuring Experienced Serendipity
Human-Computer Interaction
Summary
Serendipity means finding something surprising and interesting by chance, but it's hard to measure accurately. The authors created a new questionnaire called the Serendiptionnaire to capture how people feel when they experience serendipity, based on a detailed concept of what makes an encounter refreshing and enriching. They tested and refined the questions by watching how different people used popular apps like Instagram and YouTube. This tool can help researchers and developers better understand and improve moments of surprise and delight in digital recommendations.
What this means in practice
- •For mobile app developers: Assess and improve surprise and enjoyment in content recommendations using a validated user questionnaire for experienced serendipity.
- •For user experience teams: Validate and benchmark serendipity metrics in user studies to better understand how users find unexpected value in platforms.
Authors
Brett Binst, Annelien Smets
Abstract
Serendipity is important to design for, yet it remains difficult to measure and evaluate. No validated questionnaire exists, so studies either borrow ResQue's novelty scale, which does not measure serendipity, or build their own items, which makes findings hard to compare and synthesize. Building on our earlier conceptualization of experienced serendipity as a fortuitous encounter with content that is both refreshing and enriching, we developed the Serendiptionnaire, a questionnaire that operationalizes our framework. We conducted twenty-seven cognitive interviews over three iterations with respondents who varied in age, education level, country of birth, and English proficiency, while they browsed recommendations on platforms such as Instagram, TikTok, YouTube, and Spotify. After each iteration, we revised the items until respondents interpreted them as intended. The resulting instrument consists of modular scales that researchers can combine to target the specific flavor of serendipity they want to study or design for. The Serendiptionnaire offers a ground truth for validating system-centered serendipity metrics and LLM-based evaluations, and it provides a nuanced evaluation of users' experienced serendipity.