Name
Abstract | ||
|---|---|---|
Rationales of measuring mental models In the field of human-computer interaction (HCI), research on mental models has produced a body of literature in the past twenty years. Despite differences in perspectives and terminologies surrounding mental models, the core of the topic concerns the understanding of the cognitive structures and processes underlying the behaviors of human beings performing computer based tasks. It is clear that interaction with a computer is often a subtask during the completion of some main tasks. The main tasks may include finding information, sending a message, producing a report, and testing a statistical hypothesis. In fact, some tasks can be done without a computer (but generally more efficiently with a computer software tool). Knowing nothing about system structure and mechanisms beyond the system's display could be frustrating when interacting with a computer system. End users must possess a mental representation of the system before they feel comfortable with it. In this article, mental model refers to users' conceptual/internal representation of the system. Mental models are incomplete, limited, naive (unscientific), unstable, fuzzy, but vitally important. Mental models enable users to interact with and learn by trial and error about systems. Our goal for understanding mental models is three-fold: (1) systems should help users build appropriate mental models by providing meaningful and context-sensitive clues. (2) we need to design congruent interfaces that can anticipate users' next moves in order to provide adequate support. (3) we need to develop learning tools to help users move from novice to advanced levels. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1002/meet.14504201270 | ASIST |
Keywords | Field | DocType |
mental representation,search engines,information architecture,interfaces,human computer interaction | Search engine,Computer science,Information architecture,Human–computer interaction | Conference |
Volume | Issue | Citations |
42 | 1 | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Zhang | 1 | 191 | 18.20 |
| Peiling Wang | 2 | 38 | 4.05 |