When perceiving colors, our vision is more sensitive to edges in color than brightness. Differentiating these colors is called categorical perception. Gen Z-ers, known as 'digital natives', grew up with technology and depend on it in their everyday lives. In contrast, older generations did not grow up with technology, and visual processing declines during aging.
I hypothesized that Gen Z-ers will be faster and more accurate at detecting digital stimuli than older generations. To test this hypothesis, I conducted a quantitative research study shown below. This study was my Psychology senior thesis. Check out the complete study with references here.
Methods & Procedure
This is an experimental study conducting quantitative research. It is a between-groups design (two groups studied simultaneously). The independent variables are age (Gen Z vs Older Gen) and stimuli difficulty levels (easy, medium, hard). The dependent variables are speed and accuracy of responses.
Participants click on a link to a Qualtrics survey. Then, they sign a consent form and demographic questionnaire. They perform the exercise and interact with stimuli. Results are measured by Qualtrics heat mapping software.
stimuli
Sample Easy Stimuli
Sample Medium Stimuli
Sample Difficult Stimuli
How do the users react to the stimuli? During the demonstration video, the subject performing the exercise primarily clicks the center of the stimuli.
Heat-Mapping
Accuracy Results
Horizontal bar graphs of the mean accuracy percentages were created to reveal trends. Standard error bars are included to display variability.
A notable result is older generations scored higher than Gen Z in accuracy when interacting with the easy stimuli. This refutes the hypothesis that Gen Z interacts more accurately with stimuli than older generations. However, the standard error is 8.02, so this result is uncertain.
Gen Z scored consistently higher in accuracy than the older generations when interacting with the medium and difficult stimuli. This supports the hypothesis that Gen Z interacts with stimuli more accurately than older generations.
A Repeated Measures Analysis of Variance (ANOVA) was created to determine statistical significance of the results.
Speed Results
Horizontal bar graphs of the mean total speeds are created to show trends in the results. Standard error bars are included for variability. Note that I was unable to calculate separate speeds for each of the difficulty levels so the speed data reflect speed across all trials. The older generation has a higher total speed, which supports the hypothesis.
An Independent Samples T-Test was conducted to determine statistical significance of the results.
Challenges
Limitations of this study include its remote nature and lack of statistical significance.
Lessons Learned
This study can be valuable to UX and HCI research, as it reveals generational differences when interacting with the digital world. When designing apps for Gen Z-ers versus other generations, referring to this study could be useful. For example, when designing a button, the knowledge that users primarily click on the center of a digital stimuli would be helpful.
