Project Description

Data-oriented Methods in Linguistics

This course will take place online.

Module content

  • Get to know statistical and computational tools for linguistic analysis to visualise processes and results
  • Study methods for collecting and analysing larger sets of data for linguistic research
  • Discuss corpus and experimental methods to study questions in grammar and language interpretation
  • Programme – The course is taught in English (4 ECTS)
  • Requirements – The modules are open to all interested students. They are particularly useful for students of disciplines in which language plays an essential role, such as Linguistics, Philology, Literary Studies, Media Studies, Gender Studies, Ethnology, (Foreign) Language Teaching
  • Programme fee online – EUR 500.00 (includes all study materials, transcript of records).
  • Application deadline – 30 April 2021

Course description

Traditional linguistic research was based on laborious manual data collection, or, especially in the second half of the 20th century, on the introspective evaluation of artificially created examples by individual researchers. This has radically changed with the advent of large electronic resources and the adaptation or development of statistical and computational tools for linguistic analysis.

This course will focus on methods for collecting and analyzing larger sets of data for linguistic research.  We will discuss corpus and experimental methods to study questions in grammar and language interpretation, and we will use various techniques from the computational toolkit of modern linguistics to visualize processes and results.  Students will have the opportunity to work with corpus linguistic and statistical tools to study language use, language change, and translation.  The course will comprise lectures, group work and problem sets.

The course comprises 28 contact hours (8*3.5 hours). Upon successful completion, 4 ECTS (European Credit Transfer System) points will be awarded for the module. A single ECTS point is defined as the equivalent of 25 to 30 hours of student workload. This includes class hours, additional preparations for class activities, readings, assignments as well as final assessments.

Attendance: Participants have to attend at least 80 % of the classes.

Instructors

Prof. Dr. Manfred Sailer

PhD Janina Radò

Apl. Prof. Dr. Frank Richter

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