“One of the greatest challenges in qualitative research is self-reporting error, in which people provide incorrect information not out of dishonesty, but because their memories or self-perception differ from their actual behavior.”
Humans have limits. We struggle to remember simple daily tasks. So what do we do? We generate to-do list upon to-do list. I know personally, I am keeping Post-It Notes in business. Additionally, with dependencies on electronic devices, we forgo the need to remember how to calculate a tip at 15 percent, or what our closest friend’s phone number is.
So, if we have trouble remembering where we parked, or what we wore yesterday, or better yet — what we have to do this week, how can we be expected to self-report accurately when questioned?
Our textbook, Designing for the Digital Age: Creating Human-Centered Products and Services, by Kim Goodwin, covers user research methods and self-reporting error — this topic resonated with me this week (54–57).
When collecting data, accuracy counts and ultimately determines credibility. Goodwin notes it takes good technique to minimize self reporting error, and that that some self-reporting error is inevitable (55). While a margin of error is expected in all reporting methods, it is important to mitigate as much risk for error as possible.
Having sat in on usability testing sessions myself, in which participants are questioned and prompted, it is noticeable that some participants are not as confident as others in their self-reporting. Thus, some may not be reporting as accurately as others, whether it is recall or the need to provide the “correct” answer.
While “no research is perfect,” Goodwin goes on to provide a solution that generates optimal results, by recommending the combination of two methods of research. Through the act of conducting both observations and interviews — this allows for information to be gathered quickly, while minimizing self-reporting error (57).
As we move forward in our learning, understanding how to circumvent error is key, and finding methods that will provide us with the most accurate results is ultimately the preferred approach.