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TR

RUSSIAN-I

Course
RUSN101 - RUSSIAN-I
Department
School of Foreign Languages
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
4
T+P+L
3 + 0 + 0
Course Coordinator(s)
-
Prerequisite
-
Keywords

Course Description

This course is an introduction to the Russian language with basic grammar and sentence structures. The aim of this course is to motivate students to increase their interest in the Russian language to achieve language skills which are listening, reading, speaking and writing. The students are introduced to the sounds and letters of the Russian alphabet, the personal pronouns, different types of nouns and adjectives, possessive adjectives, the Present Continuous tense through affirmative sentences, negative sentences and questions, days of the week, numbers, wh- question words, interrogative pronouns and their usage. The course also aims to enable students to acquire necessary vocabulary, to understand the gist of what is being said and to make sense of connected speech at basic levels.

RUSSIAN-I

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

  1. 01 Students will be able to process necessary vocabulary for daily use and explain their daily routines
  2. 02 recognize the main point in short clear messages and transmit the messages in their own words.
  3. 03 construct sentences about their families and friends based on eveyday materials.
  4. 04 describe themselves and express their ideas
  5. 05 write a paragraph about themselves and family members.

Course Syllabus

Week Topic
Week 1 Introduction to the course.
Week 2 The Alphabet. Feminine, masculine and neutral differentiation.
Week 3 Introducing yourself and object names. Days of the week, Numbers.
Week 4 Subject pronouns and possessive pronouns, Interrogative pronouns.
Week 5 Affirmative, Negative and Questions sentences, jobs, Wh questions.
Week 6 Affirmative, Negative and Questions sentences, jobs, Nouns and adjectives.
Week 7 Family, classroom object, general vocabulary.
Week 8 Midterm Exams (9-20 November 2024)
Week 9 Midterm Exams (9-20 November 2024)
Week 10 Plurals and Reading, writing and speaking exercises.
Week 11 Countries, Nationalities
Week 12 Verb conjugation and the present continuous tense.
Week 13 Verb conjugation and the present continuous tense.
Week 14 Revision
Week 15 FINAL EXAMINATIONS (4-14 January, 2025)

Reference Books & Course Materials

  1. 01 A basic modern Russian grammar. Eugenia Nekrasova, 1997
  2. 02 Русский язык как иностранный: элементарный уровень: учебное пособие.Михалева Е.В., Майер А.К.,Фрицлер А.А.,Ярица Л.И.,Шевелева С.И., Рустамова А.,2011
  3. 03 Русский язык=Russian: вводный фонетический курс для иностранцев: Introductary Phonetics Course for foreighners: учебно-методическое пособие/Смирнова Т.И.,2003
  4. 04 Проект РКИ and other supplementary materials

Learning Outcomes

  1. L01 LO1- intergrate necessary vocabulay for daily use and classify the vocabulary.
  2. L02 LO2- differenciate, select and interpret appropriate gender for the word forms of everyday vocabulary, pronouns, possessive adjectives
  3. L03 LO3- examine short, simple texts and distinguish specific, predictable information from eveyday materials.
  4. L04 LO4- express themselves and discuss about their personal information and family.
  5. L05 LO5- write a paragraph about themselves and family members.

Program Outcomes

  1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
  2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
  3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
  4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
  5. P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
  6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
  7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
  8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
  9. P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
  10. P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 Average
L01 - - - - - - - - - - -
L02 - - - - - - - - - - -
L03 - - - - - - - - - - -
L04 - - - - - - - - - - -
L05 - - - - - - - - - - -