Type of Presentation
Individual paper/presentation
Conference Strand
Outreach and Partnership
Target Audience
Higher Education
Second Target Audience
K-12
Location
Ballroom C
Relevance
This proposal is highly relevant to teaching and learning of information literacy as it explores how generative AI tools like ChatGPT can enhance students’ ability to develop focused research topics - a core skill in the ACRL Framework. By integrating prompt engineering and critical inquiry within a collaborative librarian-faculty model, the study supports strategic searching, ethical use of information, and increased research confidence.
Proposal
As generative AI tools like ChatGPT become increasingly embedded in academic and everyday contexts, educators have a timely opportunity to leverage these technologies to support foundational research skills. In general education writing courses, students participate in library sessions with librarians to support their research projects. A central challenge is formulating a focused and relevant research topic, as many struggle to identify and develop ideas and refine them into viable research topics that are suitable for college-level writing and align with assignment requirements. This study explores how generative AI tools - specifically ChatGPT - can be integrated into library instruction to support students in generating, narrowing, and refining research topics.
Academic librarians and writing faculty collaboratively design a new instruction model to provide step-by-step guidance on utilizing Gen AI prompts to develop a viable research topic. The module builds on foundational skills introduced in an institution-developed GenAI 101 course, where students learn the basics of generative AI and prompt engineering. During the library session, students apply prompt engineering skills and critical thinking skills to generate potential research topics individually and then engage in group discussions to critically evaluate AI-generated suggestions for relevance, feasibility, and originality and come up with suggestions to narrow and refine research topics as a group. This instruction model aligns with the “Research as Inquiry” frame of the ACRL Framework for Information Literacy, emphasizing the ability to determine an appropriate scope of study. To assess the effectiveness of this approach, we collect data through pre- and post-session surveys, analysis of student-generated topics, and informal feedback from students and faculty.
The study investigates several key questions: To what extent can AI prompts help students brainstorm and refine research ideas? How does AI influence their ability to develop focused and relevant research topics? In what ways can students apply critical thinking and information literacy skills to use AI tools ethically and effectively? How can AI-integrated instruction enhance students’ confidence in the research process?
Findings from this study will inform future instructional strategies that blend traditional research methods with emerging technologies. The project highlights the evolving role of librarians in AI-integrated instruction and the value of faculty-librarian collaboration in designing innovative and student-centered learning experiences. By leveraging generative AI in library instruction, educators can better support students in overcoming common research challenges and foster deeper engagement with the research process.
Short Description
This study examines how generative AI tools like ChatGPT support first-year writing students in crafting and refining research topics. Using a collaborative instruction model, librarians and faculty guide students in applying prompt engineering and critical inquiry. Anchored in the ACRL Framework, the study evaluates AI’s influence on topic focus, research confidence, and ethical engagement, with implications for future library instruction.
Keywords
AI literacy; Writing; Generative AI; Research Topic Development; Prompt Engineering; Library Instruction; Faculty-Librarian Collaboration.
Publication Type and Release Option
Presentation (Open Access)
Recommended Citation
Liu, Yanling and He, Yan, "Empowering Research Topic Development with Generative AI Prompts - a Pilot study for First-Year Writing Students" (2026). Georgia International Conference on Information Literacy. 34.
https://digitalcommons.georgiasouthern.edu/gaintlit/2026/2026/34
Empowering Research Topic Development with Generative AI Prompts - a Pilot study for First-Year Writing Students
Ballroom C
As generative AI tools like ChatGPT become increasingly embedded in academic and everyday contexts, educators have a timely opportunity to leverage these technologies to support foundational research skills. In general education writing courses, students participate in library sessions with librarians to support their research projects. A central challenge is formulating a focused and relevant research topic, as many struggle to identify and develop ideas and refine them into viable research topics that are suitable for college-level writing and align with assignment requirements. This study explores how generative AI tools - specifically ChatGPT - can be integrated into library instruction to support students in generating, narrowing, and refining research topics.
Academic librarians and writing faculty collaboratively design a new instruction model to provide step-by-step guidance on utilizing Gen AI prompts to develop a viable research topic. The module builds on foundational skills introduced in an institution-developed GenAI 101 course, where students learn the basics of generative AI and prompt engineering. During the library session, students apply prompt engineering skills and critical thinking skills to generate potential research topics individually and then engage in group discussions to critically evaluate AI-generated suggestions for relevance, feasibility, and originality and come up with suggestions to narrow and refine research topics as a group. This instruction model aligns with the “Research as Inquiry” frame of the ACRL Framework for Information Literacy, emphasizing the ability to determine an appropriate scope of study. To assess the effectiveness of this approach, we collect data through pre- and post-session surveys, analysis of student-generated topics, and informal feedback from students and faculty.
The study investigates several key questions: To what extent can AI prompts help students brainstorm and refine research ideas? How does AI influence their ability to develop focused and relevant research topics? In what ways can students apply critical thinking and information literacy skills to use AI tools ethically and effectively? How can AI-integrated instruction enhance students’ confidence in the research process?
Findings from this study will inform future instructional strategies that blend traditional research methods with emerging technologies. The project highlights the evolving role of librarians in AI-integrated instruction and the value of faculty-librarian collaboration in designing innovative and student-centered learning experiences. By leveraging generative AI in library instruction, educators can better support students in overcoming common research challenges and foster deeper engagement with the research process.
