This paper begins with a theoretical exploration of the rise of large language models (LLMs) in Human-Computer Interaction (HCI), their impact on user experience (HX), and related challenges. It then discusses the benefits of Human-Centered Design (HCD) principles and the possibility of their application within LLMs, subsequently deriving six specific HCD guidelines for LLMs. Following this, a preliminary experiment is presented as an example to demonstrate how HCD principles can be employed to enhance user experience within GPT by using a single document input to GPT's Knowledge base as a new knowledge resource to control the interactions between GPT and users, aiming to meet the diverse needs of hypothetical software learners as much as possible. The experimental results demonstrate the effect of different elements' forms and organizational methods in the document, as well as GPT's relevant configurations, on the interaction effectiveness between GPT and software learners. A series of trials are conducted to explore better methods to realize text and image displaying, and jump action. Two template documents are compared in the aspects of the performances of the four interaction modes. Through continuous optimization, an improved version of the document was obtained to serve as a template for future use and research.

翻译：本文首先从理论层面探讨了大型语言模型在人机交互领域的兴起、其对用户体验的影响及相关挑战。随后论述了人本设计原则的优势及其在LLM中应用的可能性，并由此推导出六项针对LLM的HCD具体准则。接着，通过一项初步实验作为案例，展示如何利用人本设计原则提升GPT中的用户体验——将单一文档输入至GPT知识库作为新知识资源，以此控制GPT与用户间的交互，尽可能满足假设的软件学习者的多样化需求。实验结果表明，文档中不同元素的形式与组织方式，以及GPT的相关配置，对GPT与软件学习者之间的交互效果具有影响。通过一系列试验探索了实现文本与图像显示及跳转功能的更优方法，并对两种模板文档在四种交互模式下的表现进行了对比。经过持续优化，最终获得改进版文档，可作为未来应用与研究的模板。