Abstract
Aim/Background: Recently, Artificial Intelligence (AI) has rapidly revolutionized many demanding engineering applications, including transforming academic research practices. This paper proposes a comprehensive, step-by-step framework designed to enhance the practice of researchers using available generative AI chatbots. The targeted contribution is to introduce a framework that provides a clear roadmap, guiding postgraduates and researchers through five sequential phases: preparation, formulation, simulation, experimentation, and finalization.
Methods: This study employs a mixed-method approach to assess the proposed workflow phases on an engineering research postgraduate focus group during second semester 2025. Each phase includes a sequence of steps, with specific guided prompt examples, related to “Industrial Power Conversion Systems”, as a selected course subject. Subsequently, three quantitative questionnaires were used to evaluate the presented lecture, the proposal framework, and its effectiveness via a creative research proposal task. Additionally, the necessity of encouraging human integration with AI in research has been highlighted through qualitative feedback perspectives.
Results: The effectiveness of the proposed framework in assisting researchers with various tasks has been revealed. The quantitative data demonstrated positive feedback perspectives, while the value of integrating human expertise with AI tools to achieve more responsible and robust research outcomes has been emphasized through the qualitative insights. A list of recommended best practices of “Don’t” and “Do” advice, to promote responsible and effective use of the proposed framework in research contexts, is finally demonstrated.
Conclusion: The proposed framework provides a methodological and practical guide for the responsible use of AI-powered chatbots and tools to enhance engineering academic research.

Key words: Academic Education, Generative AI, List of advice, Research Workflow, Responsible AI, Prompt Examples.