HOW ENVIRONMENTAL SCIENCE GRADUATE STUDENTS ACQUIRE STATISTICAL COMPUTING SKILLS

Authors

  • ALLISON THEOBOLD Montana State University
  • STACEY HANCOCK Montana State University

DOI:

https://doi.org/10.52041/serj.v18i2.141

Keywords:

Statistics education research, Data science education, Environmental sciences

Abstract

Modern environmental science research increasingly requires computational ability to apply statistics to environmental science problems, but graduate students in these scientific fields typically lack these integral skills. Many scientific graduate degree programs expect students toacquire these computational skills in an applied statistics course. Agap remains, however, between the computational skills required for the implementation of statistics in scientific research and those taught in statistics courses. This qualitative study examines how five environmental science graduate students at one institution experience the phenomenon of acquiring the computational skills necessary to implement statistics in their research and the factors that foster or inhibit learning. In-depth interviews revealed three themes in these students’ paths towards computational knowledge acquisition: use of peer support, seeking out a singular “consultant,” and learning through independent research experiences. These themes provide rich descriptions of graduate student experiences and strategies used while developing computational skillsto apply statistics in their own research, thus informing how to improve instruction, both in and out of the formal classroom.

First published November 2019 at Statistics Education Research Journal Archives

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Published

2019-11-30

Issue

Section

Regular Articles