Exploring the Role of Generative AI as a Research Assistant in Undergraduate Sociology Research Methods

Abstract

The rapid evolution of artificial intelligence (AI) technologies has introduced new opportunities and challenges in higher education, particularly in meeting the needs of Generation Z students—digital natives who expect technology to be integrated into their learning experiences. This exploratory study investigates how undergraduate students perceived Microsoft Copilot, a generative AI (GenAI) tool, as a research assistant in completing a multistage research proposal in a sociology research methods course. Drawing on the expectation-confirmation model, the study examined the link between students’ preuse expectations of Copilot and their postuse evaluations across six key research tasks: developing research questions, formulating testable hypotheses, developing literature review outlines, identifying measurement tools, selecting a sampling technique, and completing the research proposal. Students completed pre- and postsurveys measuring expectations, perceived usefulness, overall satisfaction with use, and intentions for future use. Results show that students entered the course with high expectations of Copilot’s usefulness, which were largely confirmed or exceeded after use, especially for research-related tasks. Satisfaction and continuance intention outcomes aligned with this confirmation: 87% rated their experience as good or excellent, and 57% of students stated they would continue use. These findings suggest that GenAI, when integrated into scaffolded research tasks, can have a positive impact on students’ learning experiences. The study contributes to existing research on GenAI in higher education by highlighting how expectation confirmation can shape student satisfaction and inform integration strategies in technology-enhanced instruction.