pie title Grade Distribution
"Assignments" : 40
"Midterm Exam" : 15
"Final Exam" : 15
"Class Discussion" : 15
"Attendance" : 15
Syllabus
CHU0387: Language, Society and Literature with Corpus and Modern Technology
📅 Course Schedule
| Week | Topic | Reading Material | Homework / Due |
|---|---|---|---|
| 1 | Introductory week | Read material for Week 2 | |
| 2 | What is a corpus, and their role to understand language and literature | RHCL For language: Chapter 15, Chapter 40 For literature: Chapter 17, Chapter 37 |
Read material for Week 3 |
| 3 | Types of corpora: Selecting or building a corpus? | RHCL, Chapter 2, Chapter 8 PHCL, Chapter 15 |
Read material for Week 4 |
| Week | Topic | Reading Material | Homework / Due |
|---|---|---|---|
| 4 | Installation of R and computer set-up | Slides R for data science, Introduction, Chapter 2, Chapter 6, Chapter 28 |
Make sure the computer is prepared for the next weeks |
| 5 | Presentation of R and its basic functions | Slides R for data science, Introduction, Chapter 2, Chapter 6, Chapter 28 |
Exercises for next week |
| 6 | How to create better scripts | Slides | Exercises for next week |
| 7 | Building a corpus from media platforms (1/2) | Slides R for data science, Chapter 24 |
Exercises for next week |
| 8 | Building a corpus from media platforms (2/2) | Slides R for data science, Chapter 24 |
Exercises for next week |
| 9 | Group and individual meetings in the classroom | ||
| 10 | Midterm presentations |
| Week | Topic | Reading Material | Homework / Due |
|---|---|---|---|
| 11 | Data preprocessing: Tidying data | R for data science, Chapter 3, Chapter 5 | Exercises for next week |
| 12 | Data analysis | R for data science, Chapter 9, Chapter 10 | Exercises for next week |
| 13 | Data visualization | R for data science, Chapter 10, Chapter 11 | Prepare a document of the analyses and visualization of your own data (a preliminary version is enough) |
| 14 | Presenting a corpus-based study | PHCL, Chapter 26 | |
| 15 | Group and individual meetings in the classroom | Assistance for handling the results of the individual/group projects | |
| 16 | Student’s presentations of individual/group projects |
⚖️ Grading & evaluation
The final grade is distributed as follows:
???? Assessment details
- Assignments (40%): Regular homework
- Note: 4% will be deducted for each failure to submit homework on time.
- Final project (30%):
- Oral presentation: 15%
- Written report: 15%
- Class discussion (15%): Active participation
- Attendance (15%): Regular presence is required
📚 Resources & software
Online Resources & Software
- Course Website: https://aymeric-collart.github.io/CHU0387/
- Software: R Project (freely downloadable) | RStudio Interface (freely downloadable)
Key References
- O’Keeffe, A., & McCarthy, M. J. (2022). The Routledge handbook of corpus linguistics (2nd edition). London/New York: Routledge. [RHCL]
- Paquot, M., & Gries, S. T. (2020). A practical handbook of corpus linguistics. Cham: Springer. [PHCL]
- R for data science handbook: https://r4ds.hadley.nz/ (freely downloadable)