Quantitative UX Research · AI Enablement · Learning Experience Design
Usability benchmarks, A/B testing, and inferential statistics (ANOVA, Regression, t-tests) leveraging SPSS, R, and SQL.
Benchmarking LLM workflows (Claude, ChatGPT, Gemini) to measure reliability, mitigate friction, and accelerate enterprise adoption.
Mixed-methods research scaling educational technology and tracking longitudinal learning outcomes across diverse cohorts.
A quantitative usability and engagement study measuring session length, feature adoption, and 30-day retention for a live gamified application.
Analysis informed iterative testing cycles that resolved critical onboarding drop-offs.
SUS 87/100Achieved a "Good" grade usability rating, placing the application well above the 71 industry benchmark.
A mixed-methods usability benchmark study conducted across three diverse financial-literacy segments.
Findings directly informed a segmented onboarding redesign.
Increase in overall SUS score post-redesign
Reduction in session error rates
A structured mixed-methods research initiative evaluating technology adoption and the learning experience of AI-assisted workflows across 150+ participants.
Synthesized findings into stakeholder recommendations that successfully integrated AI into production workflows.
+21%Improvement in measured operational efficiency
A rigorous academic experimental study comparing competing theoretical frameworks (Moral Foundations Theory vs. Dyadic Template).
Ensured high data quality and statistical power for publication-ready samples while maintaining ethical compliance across all active studies.