AI-Supported Literature Review Tools and Their Influence on Graduate Student Experiences: A Usability Study (Poster 33)

• In Event: AERA Poster Session Sunday 1:30 p.m.
  In Poster Session: Artificial Intelligence in Education and Learning Technologies

Abstract

This study explores the impact of AI-supported literature review tools on the research experiences of graduate students, focusing on usability, efficiency, depth of literature exploration and enhancement of critical thinking and analytical skills. Using Ihde's Embodiment Theory, we analyzed reflections from two doctoral students and one faculty member on four AI tools: Elicit, Consensus, Scite, and Semantic Scholar. Findings indicated that while these tools can shorten the review process and provide useful features, they also create points of “hesitation” due to non-transparent design and logic. We offer instructional design recommendations to enhance user-friendliness and discuss strategies to foster a positive research culture in an AI-supported, accelerated academic context.

Authors

• Merve Basdogan, Texas Tech University

• Burcu Stone, Texas Tech University

• Fatemeh Marzban, Texas Tech University