Dr. Alejandra Zaragoza Scherman

Assistant Professor

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Biography

Alejandra Zaragoza Scherman is an Assistant Professor in the Department of Psychology and Behavioural Sciences at Aarhus University. She earned her Ph.D. in Psychology from Aarhus University in 2014, following a Master’s degree in Psychology from the University of Manitoba in 2010, and a Bachelor’s degree from the University of Guadalajara in 2005. Her research interests encompass various aspects of nostalgia, particularly how nostalgic advertising can evoke autobiographical memories and influence consumer behavior and decision-making. She has investigated how nostalgia can be harnessed to promote positive behavioral changes, such as choosing sustainable products and engaging in pro-social behavior. Furthermore, she has examined how individuals from different age groups and cultures remember highly emotional autobiographical memories and the impact these memories have on psychological functioning and mental health. Her active projects include research on the role of nostalgia in food communication and strategies to reduce food waste through innovative business practices. Through her teaching and workshops, Alejandra aims to bridge theoretical psychology with practical applications in consumer behavior and marketing strategies.

Research Interests

Experience

Assistant Professor

2014-08-29 — Present

Aarhus University • Aarhus C, Denmark

Teaching and conducting research in psychology, focusing on nostalgia and consumer behavior.

Requirements for Aarhus University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Overall
Required:6.5
TOEFL
Total
Required:83
Prerequisites
Bachelor's degree in a relevant field Specific credit requirements in programming, algorithms, and computer systems
Application Checklist
  • Official Bachelor's degree certificate
  • Official transcripts of records
  • Course descriptions
  • Curriculum Vitae (CV)
  • Documentation of English language proficiency
Specialization Notes

Department of Computer Science offers tracks in Software Efficiency, Cryptography, and Data Science.