This course explores how we can advance our understanding of human language. The basic way we do this is by coming up with new theoretical ideas and then collecting data to test whether these new theoretical ideas can account for the data or not. If they do account for the data, then we test them further against a wider range of data to see how much they can account for. If they don't account for the data, then we have to think of other ideas. This dialogue between data and ideas is central to advancing knowledge. Students will learn and practise scientific methods on how to collect original data, and on how to analyse and test ideas. Students will expand their own communication skills by gaining a deeper understanding of how human language works.
Not currently offered.
On successful completion of the course students will be able to:
1. Describe key concepts and principles for linguistic data analysis in the core disciplinary fields.
2. Apply principles for the systematic collection of language data.
3. Apply principles for the ethical collection of original data.
4. Present, discuss, and evaluate analyses of original data.
The course explores the relationship between data collection and the testing of theories. Topics include:
- How to select the kind of data collection exercise that will be appropriate to testing each particular theory.
- How to satisfy discipline ethical standards.
- How to ensure that data collected will satisfy basic statistical requirements.
- Principles of linguistic analysis
Written Assignment: Written Assignments
Case Study / Problem Based Learning: Case Study
Presentation: Oral Presentation