Presentation
Integrating Generative AI into an Undergraduate Research Methods Course: Evaluating Student Perceptions, AI Competency, and Intention to Use
SessionThursday Poster Session
DescriptionGenerative AI tools are increasingly used by college students for academic purposes, yet formal classroom integrations remain limited, particularly at the undergraduate level. This study evaluated a structured generative AI education integration in an undergraduate research methods course, assessing its impact on students' perceptions, self-rated AI competency, and intention to use generative AI for future academic and research purposes. Early in the semester, students received a structured lecture covering common AI tools, their research applications, and ethical considerations, including bias, plagiarism, and data privacy. Two optional AI-integrated assignments gave students hands-on experience using generative AI for literature search and academic writing tasks. Following course completion, a survey was administered to assess students' experiences and outcomes. Of 195 enrolled students, 24 responded. Results indicated that students entered the course with low to moderate AI familiarity and competency. The lecture was positively received, and students reported increased confidence in citing and disclosing AI use. Students reported moderately positive intentions to use AI for future studying, but not for research, reflecting reported concerns about accuracy and academic integrity. These findings highlight both the potential and challenges of integrating generative AI into undergraduate education and support the need for structured, evidence-based training approaches.
Contributor
Event Type
Poster
TimeThursday, October 22nd5:30pm - 6:30pm PDT
Location