880258 :Cognitive Models of Language Learning (HAIT/CSAI/CD)

General info

Instruction language English
Type of Instruction 14 x 2 hour lectures and 7 online contact hours (Lecture schedule)
Type of exams Individual written assignments and a final exam (Examination schedule)
Course load:6 ECTS credits
Registration:Enrollment via Blackboard before start of lectures
Blackboard InfoLink to Blackboard (When you see 'Guest are not allowed in this course', please login at Blackboard itself)


dr. A. Alishahi (coordinator)


After taking this course, the students will be able to

  • describe, characterize and compare probabilistic and structural frameworks for representing language;
  • characterize and discuss the relationship between the language representation frameworks and the cognitive processes involved in various aspects of language acquisition (such as word learning or speech segmentation);
  • evaluate and analyze computational models of language learning.


We will discuss using formal models for studying human language learning. In the first part of the course, we will focus on the high-level objectives of studying human language, the general properties of computational models of language learning, and the most common frameworks for developing them. In the second half of the course, we will focus on the cognitive processes involved in human language acquisition including speech segmentation, the association of words to meanings, learning language structure, and formation of linguistic categories, and analyze a number of computational models of each of these aspects.


The final grade of the course will be based on two related assignments (40%) and a final written exam (60%).

Compulsory Reading

  1. Research articles and book chapters, announced through Blackboard.

Recommended Reading

  1. Alishahi, A. (2010). Computational Modeling of Human Language Acquisition.Synthesis Lectures on Human Language Technologies, 3(1), Morgan & Claypool (get a copy from the UvT Library).

Required Prerequisites


Recommended option for

  • Master Business Communication and Digital Media ( 2016, 2017 )
  • Master Communication Design ( 2016, 2017 )
  • Master Human Aspects of Information Technology ( 2016 )
  • Master Data Journalism ( 2016 )
  • Master Communication and Information Sciences ( 2016, 2017 )
  • Cognitive Science and Artificial Intelligence ( 2017 )