Integration of Generative AI in Research Methodology: Graduate Students' Perspectives

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Abstract

Graduate students arrive at methodology classes with computers loaded with artificial intelligence tools, while their professors debate whether to adopt or resist this emerging reality. We worked with 312 graduate students to unravel how they navigate the intersection between methodological traditions and generative AI technologies. Through multinomial logistic regression, we identified four central predictors: AI familiarity, institutional support, research experience, and methodological self-efficacy (χ²(18) = 127.84, p < .001). The findings reveal three distinct profiles: students who avoid these technologies (34.6%), cautious experimenters (48.7%), and systematic integrators (16.7%). The main concerns revolve around academic integrity and the absence of institutional guidance. These findings inform how methodological education can bridge traditional approaches and emerging technologies to prepare future researchers.

Authors

• Miluska Jackeline Madelaine Pajuelo Abanto, Universidad Nacional de Trujillo

• Aurea Elizabeth Rafael Sánchez, National University of Trujillo

• José Ismael Castillo Navarro, National University of Trujillo

• Cecilia Del Pilar Vasquez Mondragón, National University of Trujillo

• ANTHONY Joel GONZALES PACHECO, National University of Trujillo

• Víctor Yury Bazán Pajuelo, National University of Trujillo