As more and more countries pay attention to the quality of university education in recent years, the number of students and mentors in schools has grown rapidly. In the higher education scenario, the communication between mentors and students has long been a focal point of research. Within the communication between students and mentors, understanding information in non-face-to-face interactions often poses a challenge to communication efficiency. When using instant messaging tools for text exchanges, recipients often find themselves needing to infer the sender's intentions. With the recent rapid development of large language models (LLMs) in text comprehension capabilities, we propose to use LLMs to encode information states of the sending message, aiming to achieve a more accurate understanding of the states between mentors and students. Through experiments, we have found that using LLMs for encoding information states can assist mentors and students in better understanding responses to each other and avoid misunderstandings.

Icicles and sunbursts are two commonly-used visual representations of trees. While icicle trees can map data values faithfully to rectangles of different sizes, often some rectangles are too narrow to be noticed easily. When an icicle tree is transformed into a sunburst tree, the width of each rectangle becomes the length of an annular sector that is usually longer than the original width. While sunburst trees alleviate the problem of narrow rectangles in icicle trees, it no longer maintains the consistency of size encoding. At different tree depths, nodes of the same data values are displayed in annular sections of different sizes in a sunburst tree, though they are represented by rectangles of the same size in an icicle tree. Furthermore, two nodes from different subtrees could sometimes appear as a single node in both icicle trees and sunburst trees. In this paper, we propose a new visual representation, referred to as radial icicle tree (RIT), which transforms the rectangular bounding box of an icicle tree into a circle, circular sector, or annular sector while introducing gaps between nodes and maintaining area constancy for nodes of the same size. We applied the new visual design to several datasets. Both the analytical design process and user-centered evaluation have confirmed that this new design has improved the design of icicles and sunburst trees without introducing any relative demerit.