106學年第1學期課程綱要

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一、課程基本資料
開課序號 1551 課程學制
科目代碼 ENC2036 課程名稱 語料庫語言學
英文名稱 Corpus Linguistics
全/半年 必/選修 選修
學分數 3.0 每週授課時數 正課時數: 3 小時
開課系級 英語系(碩)碩博合開
先修課程
課程簡介 This course aims to introduce theories and practices of Corpus Linguistics as a scientific discipline of its own. Corpus Linguistics has now been considered an interdisciplinary subject, requiring knowledge of linguistic theories, quantitative statistics and data processing. Therefore, this course will provide not only the necessary theoretical foundation but also practical computational skills for students who are interested in conducting corpus-based linguistic research or language-related research. This course is extremely hands-on and will lead the students through classic examples of these corpus-based applications via in-class theme-based tutorial sessions. Unlike most of the corpus linguistic courses offered in other universities, we do not introduce you to ready-made applications or software packages (e.g., Wordsmith, AntConc, Sketch Engine, LancBox, etc.). We hope to point you to the power of coding in computational text analytics. By the end of this course, students should be expected to have achieved the necessary computational proficiency and be able to perform comparable corpus-based analyses on their own data or research questions. In particular, the weekly tutorials will stress the issues of computational text analytics (e.g., web crawling, regular expression, tokenization, segmentation, concordances, collocations, keyword analysis) and statistical processing (e.g., parametric statistical analyses) via hands-on implementation with the language. This course will be a prerequisite for more advanced courses such as ENC2045 Computational Linguistics and ENC2056 Topics on Quantitative Corpus Linguistics.
課程目標 對應系所核心能力
1. This course offers an introduction of corpus linguistics for graduate students, including the necessary tools and techniques for doing corpus-based studies and annotation projects. 碩士:
 1-1 具備深化專業知識範疇及其學術研究之能力
 2-1 能有效運用英語於專業領域及相關職場上的溝通
 2-3 具有運用多媒體及資訊科技之能力
 3-2 具有獨立思考、發掘問題及批判之能力
博士:
 1-1 獨立從事專業學術研究的能力
 2-1 有效應用英語於專業領域及相關職場之能力
 2-2 以專業擷取新知,加以整合創新及運用之能力
 3-2 具有獨立思考、發掘問題及批判之能力

二、教學大綱
授課教師 陳正賢
教學進度與主題

This course aims to introducetheories and practices of Corpus Linguistics as a scientific discipline of itsown. That being said, Corpus Linguistics itself is an interdisciplinarysubject, requiring knowledge of linguistic theories, quantitative statisticsand data programming. Therefore, this course aims to provide the necessary foundation as well as skills for students who are interestedin this method to conduct a corpus-based linguistic research orlanguage-related research. Students are expected to learn:

 

n  the methodological foundationsof Corpus Linguistics

n  the theoretical bases of CorpusLinguistics

n  the technical designs andconfiguration of standard corpora

n  how to adopt corpuslinguistics as a scientific method in terms of :

l  operationalization

l  data retrieval

l  quantifying research questions

l  significance testing

n  the applications of corpus-linguisticmethodology

 

The objective of thiscourse is two-fold. On the one hand, it will introduce the theoreticalconstructs behind corpus linguistics as well as the theoretical foundationsthat motivates such a scientific method in linguistics. On the other hand, itwill provide specific hands-on tutorials to equip students with the capabilityof necessary statistical knowledge, as well as programming skills. This coursewill be a prerequisite for more advanced courses such as ComputationalLinguistics. Throughout the semester, the tutorial will use the programminglanguage R for demonstration and practices.


Week

Topics

Readings

1.         

Orientation

 

2.         

Corpus Linguistics: Fundamentals

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 1: The need for corpus data]

[Chapter 2: What is corpus linguistics?]

3.         

Scientific Method and Hypothesis formulating

 

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 3: Corpus Linguistics as a Scientific Method]

[Chapter 4: Operationalization]

4.         

Data Retrieval and Coding

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 3: Corpus Linguistics as a Scientific Method]

[Chapter 4: Operationalization]

 

5.         

Central Corpus Linguistics Methods

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 5: Retrieval and Coding]

 

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 2: The Four Central Corpus-Linguistic Methods]

6.         

Statistics for Corpus Linguistics (I)

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 6: Quantifying Research Questions]

[Chapter 7: Significance Testing]

7.         

Statistics for Corpus Linguistics (II)

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 6: Quantifying Research Questions]

[Chapter 7: Significance Testing]

8.         

Programming 101 for Linguists (I)

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 3: An Introduction to R]

9.         

Midterm Exam

 

10.       

Programming 101 for Linguists (II)

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 3: An Introduction to R]

11.       

Programming 101 for Linguistics (III)

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 3: An Introduction to R]

12.       

Statistical Programming for Linguists (I)

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 4: Some Basic Statistical Notions and Tests]

13.       

Statistical Programming for Linguistics (II)

Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Routledge.

[Chapter 4: Some Basic Statistical Notions and Tests]

14.       

Application: Collocation

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 9: Collocations]

15.       

Application: Grammar

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 9: Grammar]

16.       

Application: Text

Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.

[Chapter 12: Text]

17.       

Presentation

 

18.       

Final Exam

 

教學方法
方式 說明
講述法  
討論法  
合作學習  
媒體融入教學  
評量方法
方式 百分比 說明
作業 20 %  
期中考 30 %  
期末考 40 %  
課堂討論參與 10 %  
參考書目
1.Stefanowitsch, A. (2017). Corpus Linguistics: A Guide to the Methodology.
2.Gries, Stefan T. (2017) Quantitative Corpus Linguistics with R: A Practical Introduction. Second Edition. Routledge.

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