MSc Computational and Corpus Linguistics

This course is designed to equip students with foundational skills in reading, conducting and presenting linguistic research. It covers the relationship between empirical evidence and theoretical models, methods of data collection in different subdisciplines, ethical issues in working with and managing data from human subjects, and strategies of presenting and writing up linguistic research. It also provides training in use of tools including the programming language Python and typesetting language LaTeX.

The unit aims to:

• Enable students to understand the relationship between empirical evidence and theoretical models
• Introduce and provide practice in the writing conventions and main academic genres in linguistics
• Develop student competence with core digital tools of Computational and Corpus Linguistics  
• Enable students to design a research project compliant with ethical guidelines 

Week1. Conducting ethical research

Week2. Ethical and legal issues in NLP and AI research

Week3. Intro to preregistration and open science

Week4. Advanced Python programming for computational linguists 1

Week5. Advanced Python programming for computational linguists 2

Week6. Intro to LaTeX

Week7. Giving an effective poster presentation

Week8. Giving an effective oral presentation

Week9. Student oral presentations

Week10. Student oral presentations

Week11. Student oral presentations 

Students will attend weekly synchronous 90 minutes seminars. Five of these sessions will involve computer-based activities. The sessions focused on Python programming will be completed with Jupyter notebooks provided by the instructor. The session on Latex programming will be problem-focused with students working to create a simple document. The sessions on poster and oral presentations will involve students critiquing examples provided and coming up with a set of shared guidelines for the delivery of talks. They will then seek to follow these shared guidelines in their own oral presentations. 

Students will be able to: 

• demonstrate an understanding of principles of ethical research
• demonstrate an understanding of open science principles
• demonstrate an understanding of ethical and legal issues in computational linguistics 

Students will be able to: 

• Identify open questions in linguistics
• define linguistic research questions  
• present and justify research questions 
   

Students will be able to: 

• plan and preregister a research project
• follow academic writing conventions in linguistics
• write computer programs in Python
• employ generative AI in a skilled and appropriate fashion

Students will be able to:

• Reflect critically upon the social and ethical consequences of research and language technologies
• communicate their intellectual ideas to a general linguistics audience

Oral feedback from academics and peers on in-class programming tasks. 

Written feedback for Preregistration of Research Project, Programming task and Presentation.

Bauer, Laurie. 2007. The linguistic student's handbook. Edinburgh: Edinburgh University Press.

Litosseliti, Lia (ed). 2018. Research Methods in Linguistics, 2nd edition. London: Bloomsbury.

Macaulay, Monica. 2011. Surviving linguistics: a guide for graduate students, 2nd edition. Somerville, MA: Cascadilla Press.

Podesva, Robert J. & Devyani Sharma (eds). 2013. Research methods in linguistics. Cambridge: Cambridge University Press.

Rice, Keren. 2006. Ethical issues in linguistic fieldwork: An overview. Journal of Academic Ethics 4.123-155.

Severance, C. (2016). Python for Everybody: Exploring Data Using Python 3. https://www.py4e.com/