Dr. Nana Clemensen

Associate Professor

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Biography

Nana Clemensen is an Associate Professor at the Danish School of Education, Aarhus University, specializing in Educational Anthropology. Her research focuses on the sociolinguistic dynamics of education and language use in various contexts, particularly within rural Zambian communities. She completed her Ph.D. with a dissertation on children's experiences and the complexities of language learning in multicultural settings. Clemensen has participated in multiple research projects, including investigating language barriers affecting Danish social healthcare education and academic literacy among university students. She is also actively engaged in consultancy activities, offering her expertise in primary reading programs and the integration of educational strategies within multilingual classrooms. Through her work, she strives to address the challenges faced by learners and educators in diverse environments, using her background in Danish philology and sociology to inform her research practices. Her contributions to public discussions on educational issues demonstrate her commitment to improving learning experiences and outcomes for children in both Denmark and Zambia.

Research Interests

Experience

Associate Professor

2006-01-01 — Present

Danish School of Education, Aarhus University • København

Teaching and research in Educational Anthropology focusing on language socialization and educational practices in multicultural settings.

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.