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PROGRAM STUDI BAHASA DAN SASTRA INGGRIS JURUSAN PENDIDIKAN BAHASA INGGRIS

FAKULTAS PENDIDIKAN BAHASA DAN SENI UNIVERSITAS PENDIDIKAN INDONESIA

Course : Corpus Linguistics

Code : IG569

Chs : 4

Semester : 5 Prerequisite :

-Lecturers : Dr. Dadang Sudana, MA

R. Dian D. Muniroh, S.Pd., M.Hum.

1. Objectives

Upon the completion of this course, students are expected to:

a) understand basic concepts of corpus linguistics, its history, as well as its development,

b) be able to use programming language and its application in linguistics analysis, and

c) get practical experiences of using computer to do some linguistic processing of a corpus.

2. Course Description

This course introduces students to Corpus Linguistics, its history, as well as its development. It also introduces students to the analysis of corpus, a large body of text prepared for linguistic processing, using Python, an open source programming language that comes with a sophisticated module for Natural Language Processing (NLP) called Natural Language Toolkit (NLTK). The course provides students with practical experiences of using computer in the analysis of a corpus.

3. Learning Activities

Lecturing, practical text analysis using computer, and discussions will be the major modes for learning activities.

4. Media

Media are an LCD projector, a blackboard, computers, and corpus linguistics softwares.

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Assessment will be based on the following aspects: Class Participation : 15%

Research Project : 30% Presentation : 30% Final Test : 25%

6. Course Outline

Sessions Topics Sources

1 Syllabus overview Syllabus

2 Introduction to Corpus Linguistics [1] [5] [4]

3 History of Corpus Linguistics [4] [5]

4 Development of Corpus Linguistics [4] [5] 5 Introduction to software of corpus processing [2]

6 Language processing and Phyton [2] [3]

7 Variables, Expressions and Statements [2] [3]

8 Data Types in Python: String [2] [3]

9 Data Types in Python: List [2] [3]

10-11 Functions in Python [2] [3]

12 Conditionals and Looping Python [3]

13 Corpus in Natural Language Toolkit (NLTK) [3]

14 NLTK's Corpus Functions [2]

15 Processing NLTK's built-in corpus [2] 16 Processing Raw Text from Local File [2] 17-18 Projects’ discussions

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7. References

[1] Baker, Paul, Andrew Hardie and Tony Mcenery. Glossary of Corpus Linguistics. Edinburgh: Edinburgh University Press, 2006.

[2] Bird, Steven, Ewan Klein and Edward Loper. Natural Language Processing with Python and NLTK. California: O'reilly Media, Inc, 2009.

[3] Downey, Allen B. Python for Software design. Cambridge: Cambridge University Press, 2009.

[4] Meyer, Charles F. English Corpus Linguistics. Edinburgh: Edinburgh University Press, 2006.

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Session s

Topics Specific Objectives Learning Activities Evaluation Sources

1 Syllabus overview Introduction to the subject: a) Welcoming remarks

b) About the subject and its re-quirements

c) Overview of corpus linguistics

The lecturer overview the syllabus

Syllabus

2 Introduction to Corpus Linguistics

Students are able to define what corpus linguistics is

The lecturer introduces students to corpus linguistics

Question & answer

[1] [5] [4]

3 History of Corpus Linguistics

Students are able to mention the history of corpus linguistics

The lecturer explains the history of corpus linguistics

Question & answer

[4] [5]

4 Development of Corpus Linguistics

Students are able to mention the development of corpus linguistics

The lecturer mentions the development of corpus linguistics

Question & answer

[4] [5]

5 Introduction to software of corpus processing

Students are able to:

a) compare variety softwares for corpus processing

b) identify the characteristics of corpus softwares

The lecturer introduces students to software of corpus processing

Question & answer

[2]

6 Language processing and Python

Students are able to identify text processing by Python

The lecturer demonstrates text processing using Python

Question & answer

[2] [3]

7 Variables, Expressions and

Students are able to differentiate between variables, expression, and

The lecturer explains variables, expressions, and statements;

Question & answer

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Statements statements Students practice using variables, expressions, and statements

8 Data Types in Python: String

Students are able to specify data types in Python particularly string

The lecturer explains data types in Python; Students practice using the data types (string)

Question & answer

[2] [3]

9 Data Types in

Python: List Students are able to specify data types in Python particularly list The lecturer explains data types in Python; Students practice using the data types (list)

Question &

answer [2] [3]

10-11 Functions in Python Students are able to define and use the concepts of functions in Python

The lecturer explains functions in Pyhton; Students practice using the functions in Python

Question & answer

[2] [3]

12 Conditionals and Looping Python

Students are able to define and use the concepts of conditionals and looping Python

The lecturer explains conditionals and looping Python; Students practice using the functions in Python

Question & answer

[3]

13 Corpus in Natural Language Toolkit (NLTK)

Students are able to define and use

the corpus in NLTK The lecturer explains corpus in NLTK; Students practice using corpus in NLTK

Question &

answer [3]

14 NLTK's Corpus Functions

Students are able to define and use the NLTK’s Corpus Functions

The lecturer explains NLTK’s corpus functions; Students practice using NLTK’s corpus functions

Question & answer

[2]

15 Processing NLTK's built-in corpora

Students are able to define and use NLTK’s built-in corpora

The lecturer explains processing NLTK’s built-in corpora; Students practice using the processing NLTK’s built-in corpora

Question & answer

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16 Processing Raw Text from Local File

Students are able to define and process raw text from local file

The lecturer explains

processing raw text from local file; Students practice

processing raw text from local file

Question & answer

[2]

17-18 Projects’ discussions Students are able to explain problems they find during the projects

Students discuss their research projects with the lecturer

Question & answer

19-26 Presentations Students are able to present their research projects

Students present their research projects

Referensi

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