Aaron Sedley

Survey Research in HCI

Surveys, now commonplace on the Internet, allow researchers to make inferences about an entire population by gathering information from a small subset of the larger group. Surveys can gather insights about people’s attitudes, perceptions, intents, habits, awarenesses, experiences, and characteristics, at significant moments both in time and over time. Even though they are easy to administer, there is a wide gap between quick-and-dirty surveys and surveys that are properly planned, constructed, and analyzed.

Online microsurveys for user experience research

This case study presents a critical analysis of microsurveys as a method for conducting user experience research. We focus specifically on Google Consumer Surveys (GCS) and analyze a combination of log data and GCSs run by the authors to investigate how they are used, who the respondents are, and the quality of the data. We find that such microsurveys can be a great way to quickly and cheaply gather large amounts of survey data, but that there are pitfalls that user experience researchers should be aware of when using the method.

Minimizing change aversion for the google drive launch

Change aversion is a natural response, which technology often exacerbates. Evolutionary changes can be subtle and occur over many generations. But Internet users must sometimes deal with sudden, significant product changes to applications they rely on and identify with. Despite the best intentions of designers and product managers, users often experience anxiety and confusion when faced with a new interface or changed functionality. While some change aversion is often inevitable, it can also be managed and minimized with the right steps. This case study describes how our understanding of change aversion helped minimize negative effects for the transition of the Google Docs List to Google Drive, a product for file storage in the cloud. We describe actions that allowed for a launch with no aversion.

Designing unbiased surveys for HCI research

Surveys are a commonly used method within HCI research. While it initially appears easy and inexpensive to conduct surveys, overlooking key considerations in questionnaire design and the survey research process can yield skewed, biased, or entirely invalid survey results. Fortunately decades of academic research and analysis exist on optimizing the validity and reliability of survey data, from which this course will draw. To enable the creation of unbiased surveys, this course demonstrates questionnaire design biases and pitfalls, provides best practices for minimizing these, and reviews different uses of surveys within HCI.

Designing Surveys for HCI Research

Online surveys are widely used in human-computer interaction (HCI) to gather feedback and measure satisfaction; at a glance many tools are available and the cost of conducting surveys appears low. However, there is a wide gap between quick-and-dirty surveys, and surveys that are properly planned, constructed, and analyzed. This course examines survey research approaches that meet HCI goals, selecting the appropriate sampling method, questionnaire design best practices, identifying and avoiding common survey biases, and questionnaire evaluation. Attendees will gain an appreciation for the breadth and depth of surveys in HCI, combined with keys to conducting valid, reliable, and impactful survey research themselves.