2024 | VT Graduate Student Perspectives on Data Analysis Skills and Training

IGC Capstone Project | Interfaces of Global Change

VT Graduate Student Perspectives on Data Analysis Skills and Training

Student Members:

• Meghan Albritton, Geography
• Katie Hoffman, Biological Sciences
• Megan Gaesser, Biological Sciences 

Faculty Mentors:

• Dr. Kendra Sewall, Biological Sciences
• Dr. Leah Johnson, Statistics

The aim of this project was to assess perceptions and skills surrounding basic statistics, qualitative and quantitative data analysis, coding and other software used for research by graduate students at Virginia Tech. Specifically, their aim was to answer the research question: "What are the knowledge gaps and barriers surrounding data analysis and their methods among graduate students at VT?"

This was assessed via a survey that was distributed to all graduate students at VT via email (e.g., from deans, department heads, and listservs). Questions included themes such as, "Which software or methods are used?," Where were these methods learned?," "Were these skills required for admission into their current graduate programs?," and so on. 

Survey results were quantitatively and qualitatively analyzed. They evaluated whether perceptions suggested the possibility of a lack of perceived proficiency in these skills, and if this may be a symptom of the Hidden Curriculum, i.e. expected but not explicitly taught skills.

Deliverables included the survey questionnaire approved by the VT IRB, survey analysis, and suggestions based on identified data analysis needs of graduate students. As an additional resource, they provided Quarto documents (i.e., code cheat sheets) rendered as HTML with analysis results that can be exported and distributed as a PDF and used by students to learn code such as R and Python, etc. Additionally, they provided a qualitative learning resource based on the needs identified in the results of the survey.