Different Sample - Different Results? How Who We Ask Impacts What We Find

Aufgabenstellung / Topic

The people we recruit for user studies can substantially influence the results we obtain. For example, studies that primarily recruit computer science students, friends, or colleagues may yield different findings than studies with more diverse participant samples. Participants' prior knowledge, technical background, and relationship to the researchers can introduce biases that affect both behavior and reported perceptions. While Human-Computer Interaction research relies heavily on empirical user studies, it remains unclear which participant samples are most commonly used, how recruitment strategies differ across studies, and how these choices impact research outcomes. In this thesis, you will investigate participant sampling practices in HCI research (specifically in the field of Usable Privacy) and their potential effects on study results. The goal is to develop a better understanding of recruitment strategies, identify possible biases, and derive recommendations for designing more robust and generalizable user studies. This includes analyzing published HCI literature and conducting an empirical study that systematically varies participant samples to measure their impact on results.

You will:

• Review literature on participant recruitment, sampling bias, and external validity in HCI and related fields
• Analyze common participant samples and recruitment strategies used in HCI research
• Design and conduct an empirical study to investigate how different participant samples influence study outcomes
• Explore strategies researchers use to mitigate sampling bias
• Analyze and summarize findings in a thesis
• (Optional) contribute to a research publication

You need:

• Interest in Human-Computer Interaction research methods
• Interest in empirical research and study design
• Basic skills in data analysis (e.g., Python, R, or similar)
• Motivation to work with scientific literature
• Experience with user studies or statistics