| Summary: | 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.
|
|---|
