This study examines the impact of Generative Artificial Intelligence (GenAI) on academic research, focusing on its application to qualitative and quantitative data analysis. As GenAI tools evolve rapidly, they offer new possibilities for enhancing research productivity and democratising complex analytical processes. However, their integration into academic practice raises significant questions regarding research integrity and security, authorship, and the changing nature of scholarly work. Through an examination of current capabilities and potential future applications, this study provides insights into how researchers may utilise GenAI tools responsibly and ethically. We present case studies that demonstrate the application of GenAI in various research methodologies, discuss the challenges of replicability and consistency in AI-assisted research, and consider the ethical implications of increased AI integration in academia. This study explores both qualitative and quantitative applications of GenAI, highlighting tools for transcription, coding, thematic analysis, visual analytics, and statistical analysis. By addressing these issues, we aim to contribute to the ongoing discourse on the role of AI in shaping the future of academic research and provide guidance for researchers exploring the rapidly evolving landscape of AI-assisted research tools and research.

翻译：本研究探讨了生成式人工智能（GenAI）对学术研究的影响，重点关注其在定性与定量数据分析中的应用。随着GenAI工具的快速发展，它们为提升研究效率、简化复杂分析流程提供了新的可能性。然而，这些工具融入学术实践也引发了关于研究诚信与安全性、作者身份认定以及学术工作本质演变的重要问题。通过分析当前技术能力与未来潜在应用，本研究深入探讨了研究者如何负责任且合乎伦理地使用GenAI工具。我们通过案例研究展示了GenAI在不同研究方法中的实际应用，讨论了AI辅助研究中可重复性与一致性的挑战，并思考了AI在学术界日益深入融合所带来的伦理影响。本研究涵盖了GenAI在定性与定量研究中的双重应用，重点介绍了其在转录、编码、主题分析、可视化分析及统计分析等方面的工具。通过探讨这些问题，我们旨在为AI如何塑造学术研究未来的相关讨论提供参考，并为探索快速发展的AI辅助研究工具的研究者提供实践指导。