Component Training and Process-oriented Approach as an Advantage in Internalizing Consecutive Note-taking

• Main Authors: Kai Sung, 宋鍇
• Other Authors: Jeffrey E. Denton
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/41472960855990499064

碩士 === 國立高雄第一科技大學 === 口筆譯研究所 === 100 === Abstract The main focus of this thesis is to highlight the importance of note-taking in the operation of consecutive interpretation so that it will be brought to the front in related training programs. In the operation of consecutive interpretation, it is very critical for interpreters to manage their mental energy consumption. If interpreters can have good note-taking skills internalized, the quality of their performance will be greatly improved. This thesis suggests a workable proposal for training note-taking in related programs so that both teachers and students can benefit from the result of this study. Consecutive note-taking is considered necessary because memory alone is not always able to handle the amount of information contained in a chunk. However, in the training programs, note-taking does not get enough attention as it deserves. In point of fact, the importance of note-taking should never be overlooked. Besides serving as memory triggers to ease the workload on short-term memory, if well practiced, notes are able to show the logic of the speaker and the structure of the speech. Note-taking is indispensible to consecutive interpreters but should be carried out with as little mental energy as possible. Component training and process-oriented approach have been proved to be very efficient in training for complex tasks and should be applied to the training for developing consecutive note-taking. The present study suggests that consecutive note-taking should be internalized through component training and process-oriented approaches. With good note-taking skills internalized, mental energy consumption in consecutive interpretation is greatly reduced and the performance of interpreters is improved.