  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.
