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Using the analytic hierarchy process methods to construct the assessment indicators weight system of digital business Chinese materials
  • Qiao-Yu Cai
Qiao-Yu Cai
National Taichung University of Education

Corresponding Author:[email protected]

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Abstract

China’s rapid economic growth has lead foreigners would to increasingly become interested learning Chinese as a foreign language. Hence, not only in Taiwan but also in other countries, various business Chinese courses are being offered by universities, and international companies. Due to this increase in the need to provide to provide exceptional instruction, designing suitable business Chinese materials has become significance. To meet this need, this study aims to construct assessment indicators of digital Chinese materials toward non-native Chinese speaking businessmen and women (NNCSB). The preliminary “PC2U” assessment indicators are constructed on the basis of cognitive load theory, characteristics of adult learners learning Chinese, review on digital business Chinese materials, and previous empirical findings. The “PC2U” assessment indicators, which include 4 dimensions, 11 criteria, and 63 indicators, followed by the analysis hierarchy process (AHP) are used to construct the weight system for the “PC2U” assessment indicators. This study found that priorities, with respect to 4 dimensions (production, content, usage, and usefulness), to access digital business Chinese, that “content”, which consists of credibility, data update, and learning needs, is foremost. Moreover, it will be proven here that of 3 criteria in the “content” dimension to assess digital business Chinese, that “learning needs” is equally as important as “credibility”, and both are the former two are more crucial than “data update”. The constructed assessment indicators weight system of digital business Chinese materials is not only beneficial to fill the knowledge gap on business Chinese research, but also help publishers and teachers compile and select high quality digital business Chinese.