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Summary

This pilot study evaluated AI chatbots for nursing education and program evaluation. Custom prompts did not improve chatbot performance, and outputs were found to be unreliable.

Keywords:
ChatbotEthical designGenerative artificial intelligenceGrant evaluationLarge language modelNursing educationProgram evaluationPrompt engineeringResponsible useValues-based development

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Area of Science:

  • Nursing Education
  • Artificial Intelligence
  • Program Evaluation

Background:

  • Artificial intelligence (AI), particularly chatbots, shows potential to transform nursing education and program evaluation.
  • A pilot study examined key chatbot features: persona/system prompts, task-specific prompts, and an improvement mechanism.

Purpose of the Study:

  • To evaluate the effectiveness of custom system prompts and an AI-based improvement mechanism in chatbot-assisted program evaluation for nursing.
  • To compare AI-generated outputs and ratings with human assessments.

Main Methods:

  • Developed a chatbot system with a persona prompt ('Future-FLO') and a task prompt for program evaluation.
  • Created an 'ImproverBot' for structured assessment of chatbot outputs.
  • Human raters and the ImproverBot evaluated AI outputs for accuracy, completeness, and usefulness, with statistical comparisons.

Main Results:

  • Custom system prompts offered no significant advantage over standard models, according to both human raters and the ImproverBot.
  • The ImproverBot assigned significantly higher ratings than human raters.
  • Qualitative feedback highlighted that AI-generated outputs were frequently error-filled and unreliable.

Conclusions:

  • Current AI chatbots, despite custom prompting, demonstrate limitations in reliability and accuracy for program evaluation tasks in nursing.
  • Further development and rigorous evaluation are essential for effectively integrating AI tools into grant and program evaluation processes.