Integrating Generative AI Into an Undergraduate Research Methods Course: Evaluating Student Perceptions, AI Competency, and Intention to Use

Abstract

College students increasingly use generative AI, yet formal undergraduate classroom implementation remains limited. This study evaluated a structured generative AI training in an undergraduate research methods course, examining its impact on students’ perceptions, self-rated competency, and future intention to use. Early in the semester, students received a lecture on generative AI tools, applications, and ethical issues, including bias, plagiarism, and data privacy. Two optional assignments provided hands-on practice using AI for literature searching and academic writing. After the course, 24 of 195 enrolled students completed a survey. Respondents reported low-to-moderate initial AI familiarity and competency. The lecture was well received and led to confidence in citing and disclosing AI use. Students expressed moderately positive intentions to use AI for future studying and research activities, while reporting concerns about accuracy and academic integrity. Findings suggest that structured, evidence-based AI training may support responsible use in undergraduates while addressing persistent ethical and practical concerns.