Abstract
This poster presents an innovative exploration of AI tools designed to enhance Course-based Undergraduate Research Experiences (CUREs). The presenter has co-taught a two-credit undergraduate research course in the field of AI and Computer Vision in the College of Engineering at Purdue University during both the spring and fall semesters since 2020. Computer Vision domain focuses on enabling machines to interpret and understand the visual world. By collecting, processing, organizing, analyzing, and making sense of visual data such as video and image, AI systems in computer vision can perform a wide range of tasks such as image recognition and generation, object detection, facial recognition, and more. This study highlights the integration of AI tools for research such as Scholar GPT, Scite, and Research Rabbit to enhance learning and research opportunities for undergraduate students. Student projects are shared on how these tools have been effectively and ethically used to streamline literature reviews, validate citations, and uncover new research trajectories. Additionally, the study explores the pedagogical adjustments necessary to incorporate these tools into academic curriculums, thereby fostering a more innovative and supportive learning environment that encourages critical thinking and independent research skills among undergraduates.
Presenters
Wei ZakharovAssociate Professor, Libraries and School of Information Studies, Purdue University, Indiana, United States
Details
Presentation Type
Theme
KEYWORDS
AI Tools, Undergraduate Research, Computer Vision
