The research on English for Specific Purposes (ESP) has been thriving for decades. However, Chinese for Specific Purposes (CSP) has not yet received much attention. With the increasing number of students learning Chinese for Academic purposes, CAP-related teaching and learning materials should be developed. To more effectively construct a corpus for the investigation of Chinese academic language, the present study thus adopted a new corpus compiling methods called Web Boot Cat (Bootstrap Corpora And Terms from the Web), a tool that allows users to retrieve texts from web pages automatically based on a set of self-selected seed words. Based on a list of high-frequency Chinese academic words and the application of the Web Boot Cat, this study developed a 43-million-word web-based Chinese academic corpus. The large Chinese academic corpus was then loaded onto the Intelligent Collocation Engine (ICE), which is a search engine allowing users to retrieve various academic collocates and example sentences from the corpus. The tool also allows users to specifically search for collocates of different parts-of-speech. In order to examine the effectiveness of the tool in retrieving academic collocates, the search results generated by the ICE tool and the well-known Academia Sinica concordancer, which is based on a large general corpus, were further compared. The comparison of the search results between the ICE tool and Academia Sinica concordancer revealed that more useful academic collocates can be retrieved by the ICE tool while the collocates retrieved by the Academic Sinica concordancer are mostly for general use. This result indicates the very different characteristics between academic texts and general texts, further suggesting the importance and necessity that Chinese for Specific purposes should be further explored in addition to Chinese for general purposes. Moreover, that more academic-related collocates were retrieved by the ICE tool indicates that the texts included in the Chinese academic corpus are quite academically relevant. This finding suggests the feasibility of applying Web Boot Cat for corpus development. Furthermore, this study also provides pedagogical suggestions regarding the use of the ICE tool on teaching and learning of Chinese for academic purposes. The ICE tool provides abundant academic collocation information and a large number of authentic example sentences in academic context. Thus, it can serve as a useful tool for teachers to provide supplementary materials regarding academic collocational knowledge for learners. As for learners, this tool can help them conduct self-directed learning or serve as a reference tool for academic writing whenever they encounter problems regarding collocation usage. With the rich academic collocation information provided by the tool, it can also be of help for material writers as they design activities for collocation learning. Finally, the present study provides various suggestions about other possible applications of various CSP corpora. It is expected that the empirical findings of the present study can help to draw more Chinese language teachers' and learners' attention to Chinese academic collocates and pedagogical applications.
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