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Related Experiment Video

Updated: Apr 2, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
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Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

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Blinded But Biased: Students Prefer Chatbot Until They Know It Is One.

Joshua Lambert1, Bailey E Martin1, Robyn Stamm1

  • 1College of Nursing, University of Cincinnati, Cincinnati, Ohio.

The Journal of Nursing Education
|March 31, 2026
PubMed
Summary

Doctor of Nursing Practice (DNP) students preferred AI chatbot responses for statistical help when blinded. However, they showed bias against artificial intelligence (AI) when the source was suspected, impacting AI adoption in education.

Related Experiment Videos

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Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
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Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

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Area of Science:

  • Nursing Education
  • Artificial Intelligence in Education
  • Statistical Support

Background:

  • The integration of artificial intelligence (AI) into educational settings necessitates understanding student perceptions of AI-generated academic support.
  • This pilot study focuses on evaluating Doctor of Nursing Practice (DNP) students' views on statistical assistance from various sources.

Purpose of the Study:

  • To investigate how DNP students perceive and rate statistical help provided by different sources, including a large language model (LLM) chatbot.
  • To explore potential biases in student evaluations of AI-generated academic support.

Main Methods:

  • Seven DNP students submitted capstone project-related statistical questions.
  • Responses were generated by a custom-trained LLM chatbot, a graduate assistant, and a professor, presented blindly.
  • Students rated responses on helpfulness, satisfaction, and likelihood of use, and attempted to identify the AI source.

Main Results:

  • The LLM chatbot received the highest average ratings for helpfulness and satisfaction when responses were evaluated blindly.
  • Students consistently assigned lower ratings to responses they believed were AI-generated, indicating a potential bias against AI.

Conclusions:

  • DNP students preferred AI chatbot responses for statistical assistance when the source was unknown.
  • A bias against AI was observed when students suspected the source, which could impede the adoption of AI tools in academic support settings.
  • Further research is needed to understand and address AI bias in educational contexts.