Graduate Students at the Frontier of GenAI: Emerging Trends from a Southwest Borderland University
DOI:
https://doi.org/10.24059/olj.v30i2.5529Keywords:
Generative Artificial Intelligence (GenAI), higher education, graduate students, connectivism, Concerns-Based Adoption Model (CBAM), AI literacyAbstract
The rapid emergence of generative AI (GenAI) is reshaping higher education, offering both opportunities and challenges. In this context, graduate students are a critical population for examining adoption as they tend to experience both advanced academic work and professional preparation. This study explored graduate students’ awareness, uses, perceptions, and future intentions regarding GenAI within the context of taking one or more educational technology courses at a Southwest borderland university. A qualitative descriptive, cross-sectional design was employed. Data were collected via an online survey (N = 24) including multiple choice, Likert-scale, and open-ended items. Connectivism served as the primary theoretical perspective, with the Concerns-Based Adoption Model (CBAM) Stages of Concern providing a complementary framework for interpreting adoption patterns. Findings indicated that students moved from limited prior exposure to more deliberate integration of GenAI. Three key thematic trends emerged: (1) promise, productivity, and partnership, where GenAI was framed as a collaborative partnership that augments rather than replaces human agency; (2) boundaries and ethics, including strong concerns about academic integrity, accuracy, equity, and over-reliance; and (3) navigating uncertainty, marked by inconsistent institutional policies and discipline-specific variation. Overall, graduate students are navigating GenAI adoption with enthusiasm tempered by boundary consciousness. They viewed GenAI literacy as increasingly essential for academic and career competitiveness yet stressed the importance of policies and practices that emphasize appropriate augmentation, ethics, and equity in higher education.
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