When feedback becomes a learning signal.
A mixed-method study examining how timing and specificity of feedback influence persistence during difficult learning tasks.
I investigate how people learn, decide, and adapt, combining experimental design, behavioral data, and transparent interpretation to turn hypotheses into useful evidence.
The portfolio is organized around the research arc: a sharp question, a defensible method, an interpretable result, and a clear implication.
A mixed-method study examining how timing and specificity of feedback influence persistence during difficult learning tasks.
Experimental work on task resumption, notification timing, and the hidden cost of switching contexts.
Behavioral analysis of how visual structure changes recall and transfer when learners build spatial representations.
I favor methods that make claims inspectable: preregistration, transparent measures, thoughtful sampling, and analysis that stays close to the research question.
Controlled studies, counterbalancing, manipulation checks, and participant-centered protocols.
Model-based reasoning, uncertainty-aware interpretation, and reproducible analysis workflows.
Qualitative interviews paired with quantitative evidence to explain not only what changed, but why.
Leading collaborative studies on feedback, attention, and learning behavior; mentoring junior researchers and translating findings for education partners.
Designed behavioral experiments, developed analysis protocols, and contributed to multi-site research on cognitive adaptation.
Doctoral research focused on how learners update mental models when feedback conflicts with prior expectations.
Built participant protocols, supported longitudinal data collection, and developed an early interest in evidence communication.
I welcome research collaborations, academic partnerships, invited talks, study design conversations, and interdisciplinary projects where the question is still being shaped.
Typical response time: within two business days.