How environmental science graduate students acquire statistical computing skills

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 to acquire these computational skills in an applied statistics course. A gap 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 skills to apply statistics in their own research, thus informing how to improve instruction, both in and out of the formal classroom.