Year: 2026
Type: article
Abstract: This study reports the results of an experiment conducted to measure the potential for generative AI to serve as an autonomous replacement for Bloomberg terminal information literacy instruction with a business librarian. The author of the study compared the performance and completion time on an assessment between a control group receiving traditional in-person Bloomberg instruction from a librarian against an experimental group taking an assessment with the assistance of Google Gemini in the absence of human instruction. Additional grounded theory thematic analysis was applied by the author to the transcripts of AI prompts and responses generated by the AI cohort for the identification of trends in subject interactions with the AI. Results showed better performance on the assessment by the control group, and a lack of strong statistical evidence supporting the hypothesis that current generative AI could effectively replace traditional human information literacy instruction for Bloomberg.
Author: Michael Deike
Institutions: University of Notre Dame, Hesburgh Libraries
Language: English
Subfield: Library and Information Sciences
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7133891234