Dr. Brooke Macnamara

Associate Professor

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Biography

I am interested in factors that predict skilled performance variance, both performance changes and individual performance differences among individuals. Predictors of skilled performance variance include experiential factors (e.g., training, practice), environmental factors at multiple levels (e.g., task characteristics, pressure situations, societal structures), cognitive factors (e.g., working memory capacity), and non-cognitive factors (e.g., affective traits, stress responses, motivation). For example, I explore how engagement with artificial intelligence leads to skill decay among professionals, as well as how acquiring dynamic, spatial skills differs from acquiring skills in a static environment and how context affects learning transfer. My research includes investigations into how cognitive abilities predict performance depending on task characteristics, how mindset predicts academic achievement, and how the performance domain (e.g., sports, music, occupation) moderates the role of practice performance. Additionally, I seek to understand popular theories of achievement, including deliberate practice and mindset, and the factors that influence their popularity. I am currently recruiting graduate students for Fall 2026 admission.

Research Interests

Experience

Associate Professor

— Present

Purdue University • West Lafayette, IN

Teaching and researching in the Department of Psychological Sciences with a focus on factors predicting skilled performance.

Awards

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Fellow

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Early Career Award

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Fellow

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Rising Star

Requirements for Purdue University

Master Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:22
Reading
Required:22
Writing
Required:22
Speaking
Required:22
Total
Required:100
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
Duolingo
Overall Score
Required:135
Overall
Required:135
Prerequisites
Bachelor's degree in CS or related field Foundational concepts of computer science Data structures Computer architecture Operating systems Mathematics through differential equations Linear and matrix algebra
Application Checklist
  • Official Transcripts
  • Academic Statement of Purpose
  • Personal History Statement
  • Resume
  • Three Letters of Recommendation
  • CS Supplementary Form
Specialization Notes

GRE is not required.