Building a testing framework of visual web aesthetics

After having read about what aesthetic experiences are, which different visual aesthetics exist in UX design, how aesthetics can influence usability (or vice versa), it is time for a first trial experiment. My goal for this term is not to build a complete user test to determine the connection, but rather lay the groundwork, experiment, and deepen my understanding for it to build a test hypothesis and prepare for an A/B-test in the future.

For this, I want to build a first trial framework of atomic web aesthetics and try different variations (possibly replicating large-scale UX trends), taking the general principles of “beautiful design” into account. To build a first set of testing variables, I will loosely orient myself on previously conducted research like a study by Odushegun (2023) who tested the affect ratings of atomic visual web aesthetics (see: previous blog posts). Odushegun (2023)  tested the effect of different typefaces, colours and animation effects. However, I will leave out motion in my following experiments to simplify the research. In addition to those factors, I will observe the use of white space and the use of stylistic devices (drop shadow and glow, gradients and gloss, transparency) in accordance with previous readings.

As a first testing interface I am going to use a feature from an old personal project of mine: the app “Plantlove”. The purpose of the app is to help people take care of their house plants and the selected screen depicts a search database where you can enter which plant you own is having problems, select the type of problem the plant encounters and then search for a solution.

Task for the test user:

“Your rubber plant has brown leaves. Search for a solution in the database.”

In the next week, I will experiment with the visual web aesthetics of this basis interface.

References:

  • Odushegun, L. (2023). Aesthetic semantics: Affect rating of atomic visual web aesthetics for use in affective user experience design. International Journal of Human-computer Studies, 171, 102978. https://doi.org/10.1016/j.ijhcs.2022.102978
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