Promptology: Enhancing Human–AI Interaction in Large Language Models

Abstract

This study investigates the integration of generative AI in higher education and the development of the SPARRO framework, a structured approach to improving human–AI interaction in academic settings. This ethnographic study explores the integration of generative AI in healthcare and nursing education, detailing the development of the SPARRO framework based on observations of student and faculty interactions with AI tools across five courses. The study identifies key challenges such as AI hallucination, mistrust of AI-generated summaries, and the difficulty in formulating effective prompts. The SPARRO framework addresses these challenges, offering a step-by-step guide for planning, prompt design, reviewing, and refining AI outputs. While the framework shows promise in improving AI integration, future research is needed to validate its applicability across other academic disciplines and assess its long-term impact on critical thinking and academic integrity. This study contributes to the growing body of research on AI in education, offering practical solutions for ethically and effectively integrating AI tools in academic settings.

Keywords

• autoethnography
• artificial intelligence
• AI in education
• prompt design
• SPARRO
• promptology