Identification of Educational Gaps in Data Science Training Across Agricultural Genomics

Abstract

The objectives of this study were to identify gaps in educational training for undergraduate and graduate students in agricultural data science, propose paths for filling these gaps, and provide an annotated list of resources currently available to different training levels. Data in this study was collected through three voluntary surveys catered to undergraduate students, graduate students, and faculty or professionals in fields of agricultural data analytics. Resources were identified through search engines and annotated based on cost, target audience, and topic. Undergraduate students were found to be inexperienced in statistics, data analysis, and coding. Graduate students were better trained than undergraduate students but did not find university curriculum to be the primary source of education. Faculty and professionals indicated that interest in their field is high but the number of qualified applicants for positions is low. Additionally, there was interest by faculty and professionals to fund training programs for employees but low access to resources for these programs. Education resources identified through the search were limited and many had high cost to students. All resources identified were published in an online catalog (https://agdata.cahnr.uconn.edu/).