"We Are Always the Last to Get a Bit of It": Generative AI Insights From a Quantitative Ethnography Study of Mississippi Undergraduates

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: SIG-Advanced Technologies for Learning Virtual Poster Session

Abstract

This study explores the application and perceptions of generative AI (GenAI) tools among undergraduate students from the Mississippi Delta, a region with socioeconomic challenges. Using a two-phase design with structured interviews before and after a semester-long engagement with GenAI, with Quantitative Ethnography and Epistemic Network Analysis, the findings reveal initial resistance due to low self-efficacy and unfamiliarity, which gradually shifted to recognizing GenAI’s academic and professional benefits. The study stresses the need for structured training and support to enhance GenAI adoption, while addressing ethical and technological barriers. It advocates for more research on the unique challenges faced by students in low SES regions, while emphasizing tailored educational strategies and policies to bridge the digital divide and ensure equitable access.

Authors

• Tianshi Hao, Pepperdine University

• Ying Wang, Mississippi Valley State University