Product Redesign for a Cross-Disciplinary Userbase
Situation: A large university course that taught computer fundamentals to a cross-disciplinary audience was at risk of losing funding.
Action: Based on user and stakeholder data, I redesigned the course by making the topics more relatable, and facilitating asymmetric learning.
Outcome: Funding was maintained, course participation increased 47%, and exam scores increased 12%.
Methods used: user interviews*, stakeholder interviews, collaborative design*, content audit, competitive analysis, qualitative surveys, quantitative surveys, metrics analysis, log analysis (*guerrilla methods).
Research composition (estimate): 70%/30% primary/secondary; 80%/20% generative/evaluative.
Feedback Preferences for Mobile Text Entry
Situation: Touchscreen keyboards lack tactile feedback, but typically compensate by having options for auditory (click) and haptic (vibration) feedback.
Action: I investigated which feedback option users prefer, the reason for their preference, and whether feedback type affects typing speed or accuracy.
Outcome: Users prefer having no audio or haptic feedback, and there was no significant effect of feedback on typing performance. Additionally, the survey responses suggest that feedback preference is influenced by social factors.
Methods used: usability-lab studies (i.e., user testing), qualitative surveys, quantitative surveys, metrics analysis, log analysis.
Research composition (estimate): 90%/10% primary/secondary; 50%/50% generative/evaluative.
Gathering Text Entry Metrics on Android Devices
Situation: Researchers require software to record performance metrics for text entry usability studies. Existing solutions worked only for desktop systems, or required a separate solution for each new text entry technique.
Action: I designed and developed a mobile app that was agnostic to the input method being evaluated, and facilitated ethnographic studies.
Outcome: The app (called "TEMA") has been requested by more than 70 researchers globally, in both academia and industry.
Methods used: usability-lab studies (i.e., user testing), usability benchmarking, competitive analysis, quantitative surveys, metrics analysis, log analysis.
Research composition (estimate): 70%/30% primary/secondary; 20%/80% generative/evaluative.
Optimizing Performance in Mobile Text Entry
Situation: The Qwerty keyboard layout was designed for two-handed, ten-finger typing. Gripping a mobile device typically limits users to one or two thumbs for typing.
Action: After conducting a thorough examination of the benefits and drawbacks of existing text entry methods, I designed an optimized layout keyboard for mobile Android devices.
Outcome: A longitudinal usability study revealed positive user feedback, and predicts better than Qwerty performance after only 12 hours of use.
Methods used: usability-lab studies (i.e., user testing), usability benchmarking, diary study, quantitative surveys, metrics analysis, log analysis, heuristic evaluation, user interviews, concept testing.
Research composition (estimate): 60%/40% primary/secondary; 70%/30% generative/evaluative.