English Studies

G R A D U A T E D E G R E E P R O G R A M M E : E N G L I S H S T U D I E S
Prerequisites
Course contents
Recommended
reading
Supplementary
reading
Teaching
methods
Assessment
methods
Language of
instruction
Quality
assurance
methods
to apply statistical methods to the analysis of linguistic properties and
corpus generation.
Competences and skills acquired upon the completion of Introduction to
linguistics and other undergraduate courses in linguistics.
The growing amount of natural language corpora and the widening use of
computers in the analysis, education, and study of language have a profound
influence on the way we perform natural language research and organize
studies and teaching of languages.
In this course we will go behind the scenes of natural language tools for
analysing corpora like concordance and keyword-in-context tools, the
structure and annotations of natural language corpora, internet resources and
interactive systems for language teaching. We will run our own experiments
and projects; generate corpora and natural language resources, as well as
quantitative results from analyses.
We will learn how statistical analysis is used to gain deeper insights into the
properties of natural language, and how it is applied to natural language
technologies.
1. Teacher-generated materials: script, web page and slides.
2. Manning, C. D., and Schütze, H. (1999). Foundations of statistical
natural language processing. Cambridge, Mass.: MIT Press.
Jurafsky, D., and Martin, J. H. (2000). Speech and language processing: an
introduction to natural language processing, computational linguistics,
and speech recognition. Prentice Hall series in artificial intelligence.
Upper Saddle River, N.J.: Prentice Hall.
Lectures (traditional / student-participation-encouraged / on-line) / Tutorials
/ Practical sessions / Advisory hours / Research project / Independent
research / Independent study.
Student participation is encouraged through various tasks and activities,
such as: problem-solving tasks, group work, pair work, online grammar
development and testing tools, language games (etc.).
The assessment of student knowledge/performance will be based on the
following:
1. Continuous assessment (diagnostic tests, independent homework/project
tasks, achievement tests).
2. Exam: written.
Croatian/English.
1. Anonymous student feedback via questionnaires and surveys (permanent
online anonymous commenting facility and via paper questionnaires).
2. Lecturers responsible for the same subject area collaborate closely and
monitor each other’s work.
3. Occasional class observations and assessment by departmental
colleagues.
4. Occasional open and public lectures for all students and colleagues also
via live online technology (camera and microphone).
5. Recording of lectures via web/digital cam for later analysis and offline
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