Fostering Undergraduate Data Science

GÖKALP YAVUZ F., Ward M. D.

AMERICAN STATISTICIAN, cilt.74, sa.1, ss.8-16, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 74 Sayı: 1
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1080/00031305.2017.1407360
  • Dergi Adı: AMERICAN STATISTICIAN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Business Source Elite, Business Source Premier, CAB Abstracts, EBSCO Education Source, EconLit, Education Abstracts, Public Affairs Index, zbMATH, DIALNET
  • Sayfa Sayıları: ss.8-16
  • Anahtar Kelimeler: Computation, Learning, Mentoring, Statistical projects, Teamwork
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Data Science is one of the newest interdisciplinary areas. It is transforming our lives unexpectedly fast. This transformation is also happening in our learning styles and practicing habits. We advocate an approach to data science training that uses several types of computational tools, including R, bash, awk, regular expressions, SQL, and XPath, often used in tandem. We discuss ways for undergraduate mentees to learn about data science topics, at an early point in their training. We give some intuition for researchers, professors, and practitioners about how to effectively embed real-life examples into data science learning environments. As a result, we have a unified program built on a foundation of team-oriented, data-driven projects.