ROCOR – The Impact of Refined AI Prompt among Students: An Experimental Study

Abstract: The integration of artificial intelligence (AI) in education has transformed student learning and interaction with information. However, the quality of AI-generated responses significantly impacts student outcomes. This study investigates the impact of the ROCOR (Relevance, Objectivity, Clarity, Organization, Responsiveness) framework on the effectiveness of AI-powered learning tools among college students. The ROCOR framework provides a structured guide for developing high-quality AI prompts tailored to student needs. Using a quantitative approach, this study examines the influence of the ROCOR framework on student engagement, learning outcomes, and perceptions of AI-powered tools. Results indicate that implementing the ROCOR framework significantly improves student writing skills and their ability to effectively utilize AI tools. The findings suggest that ROCOR enhances educational experiences by providing more targeted and timely feedback, leading to increased student motivation and perseverance. Additionally, AI integration in education can generate valuable data to inform broader educational strategies and develop critical thinking and problem-solving skills. Recommendations for future research include expanding the sample size, conducting longitudinal studies, and exploring the application of refined AI prompts across various courses and subjects.