Cognitive Science Research

Investigating the fundamental mechanisms of human cognition and behavior

Cognitive and Perceptual Abilities in Card Game Players

Lab Manager Role - Led team hiring, interviewing, and management

Led a comprehensive research project investigating the cognitive and perceptual abilities of Magic: The Gathering players compared to non-players. This study examined multiple cognitive domains including reasoning, numeracy, visual memory, and attention processing to understand how strategic gaming experience relates to cognitive performance.

Research Focus Areas:

  • • Reasoning and problem-solving abilities
  • • Numeracy and mathematical cognition
  • • Visual memory capacity and retention
  • • Visual attention and processing speed
  • • Strategic thinking and planning

Technical Implementation:

  • • PsychoPy experiment development
  • • Pavlovia deployment and data collection
  • • Statistical analysis using R and Python
  • • Correlation and regression modeling
  • • ANOVA/ANCOVA comparative analysis

Methodology & Analysis:

Our methodology involved creating and collecting cognitive assessment stimuli, developing PsychoPy experiments deployed on Pavlovia, and conducting comprehensive statistical analyses using R and Python. The project employed advanced statistical methods including correlation analysis, linear/logistic regression, and ANOVA/ANCOVA to identify cognitive differences between gaming populations.

E

Experimental Design

D

Data Analysis

M

Team Management

User Experience Design and Research

Contributed to interdisciplinary research that bridges cognitive psychology and user experience design. This project developed both subjective and objective measures to track user journeys, assess usability, and quantify customer satisfaction through rigorous experimental methods.

Research Methodologies:

  • • User journey mapping and analysis
  • • Usability testing protocols
  • • In-depth user interviews
  • • Qualitative data coding and analysis
  • • Mixed-methods research design

Technical Skills Applied:

  • • Figma design and prototyping
  • • Statistical analysis in R and Python
  • • Qualitative coding methodologies
  • • User testing facilitation
  • • Data visualization and reporting

Interdisciplinary Applications:

This research combines principles from cognitive psychology, human-computer interaction, and design thinking to create evidence-based UX methodologies. Our work contributes to understanding how cognitive processes influence user behavior and decision-making in digital environments, with applications in product design, interface optimization, and user satisfaction measurement.

Graph Perception and Data Visualization

Investigated fundamental questions about how people interpret graphs and data visualizations, including common misconceptions and perceptual biases. This research provided insights into statistical literacy and data comprehension that inform better visualization design practices.

Core Research Questions:

  • • How do people interpret novel graph formats?
  • • What misconceptions arise in data interpretation?
  • • How does statistical literacy affect comprehension?
  • • What design principles improve understanding?
  • • How do cognitive biases influence perception?

Experimental Contributions:

  • • Participant recruitment and scheduling
  • • Experiment piloting and refinement
  • • Data collection supervision
  • • Statistical analysis and interpretation
  • • Experimental material development

Mixed-Methods Approach:

Our research employed both quantitative and qualitative methods to comprehensively understand graph perception. We combined controlled experiments measuring accuracy and response times with qualitative interviews exploring reasoning processes and misconceptions.

EXP

Controlled Experiments

INT

User Interviews

VIZ

Visualization Design

STAT

Statistical Analysis