An Exploratory Study of Cognition Involved in Chinese(Kanji) Data Entry Based on GOMS

• Main Authors: Liou Gwo Charng, 劉國常
• Other Authors: Kuo Feng Yang
• Format: Others
• Language: zh-TW
• Published: 1993
• Online Access: http://ndltd.ncl.edu.tw/handle/64632536264355158531

碩士 === 國立交通大學 === 資訊管理研究所 === 81 === One critical issue in adopting computers in Taiwan is to design interfaces that enable users to easily input Chinese characters( Kanji). Kanji is inherently different from English. To input Kanji, a user must decompose a word into radicals, and input them through a traditional English keyboard on which the radicals are marked. It appears that such Kanji entry involves susbstantial cognitive(e.g., momory, motor, and perceptual) effort. Previously, Card et al. have proposed GOMS(Goals, Operators, Methods and Selection rules) to model cognition involved in English data entry. GOMS is a way of describing what the user needs to know and to do in order to perform computer-based tasks. The METT(GOMS Model of Expert Transcription Typing), an extension of GOMS for modeling nonsequential component processes, has been shown useful for predicting the time to execute English typing tasks. The purpose of this thesis is to study if METT can be applied to predict the performance of Kanji entry. Through such analysis, we hope to understand cognition involved in Kanji entry. An experiment was performed to validate the applicability of METT to model Kanji data entry behavior model. The research findings indicate that METT can be used to predict performance with acceptable accuracy. In addition, based on the research finding, a new model, MECT (GOMS Model of Expert Chinese Typing), is proposed. A preliminary analysis shows that MECT can predict performance with better accuracy than METT. However, this difference between two model's predicting power is not indicative of their respective theoretical soundness. Instead, it shows that more studies are needed to understand the complexity of cognition involved in Kanji entry.