Keywords: computational thinking, computational abilities, ecology
With the emphasis on STEM education throughout the nation, a larger number of undergraduate students are considering Master's degrees prior to entering the workforce. Ecology and Land Resources and Environmental Sciences are among the fields that require researchers and practitioners to possess a Master's degree, in order to obtain permanent positions with either the state or federal government. This presentation will focus on graduate students enrolled at Montana State university, where Statistics 511 and 512 are courses required for the completion of a Master's degree in Ecology and Land Resources and Environmental Sciences (LRES), among other degrees of study. These terminal statistics courses intend to prepare graduate students for the statistical and computational problems they may face as researchers and practitioners. With the growth in complexity of ecology models, the computational, mathematical, and statistical expectations of researcher's abilities have multiplied. With these complexities in mind, this presentation aims to describe and understand Ecology and LRES graduate student's abilities to transfer their classroom knowledge to more complex field applications.