Singapore University of Social Sciences

English in Singapore (ELG355)

Applications Open: 01 October 2019

Applications Close: 15 December 2019

Next Available Intake: January 2020

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1378 View More Details on Fees

Area of Interest: Linguistics and Languages

Schemes: Lifelong Learning Credit (L2C)

Funding: To be confirmed


Synopsis

What is Singapore English? What are its features and status in Singapore and in the region? This course aims to give students a substantial overview of Singapore English, as well as the ability to analyse and describe data from an interview with a Singaporean speaker of English. Students will be expected to make a recording of an interview with a speaker and then transcribe and describe in detail the pronunciation, grammar, lexis and discourse features found in that recording, based on the example analysis of the data of Hui Min presented in the textbook Singapore English (EUP, 2007).**Note: The ECA for this course may consist of a project that builds on data gathered in TMA01 and/or TMA02. Although RESIT students have already passed OCAS and will not submit new TMA work as part of their RESIT, these students may need to gather new data for the RESIT ECA, as specified in the guidelines of the new TMA(s). Any questions about this matter should be directed to the course AF or the programme team.**

Level: 3
Credit Units: 5
Presentation Pattern: Every January

Topics

  • World Englishes; Language Planning in Singapore
  • Variation in Singapore
  • Consonants and Vowels
  • Rythm, Stress, Intonation and Grammar
  • Discourse and Lexis
  • Current Status and Approaches to Variation

Learning Outcome

  • Appraise the status of Singapore English and the range of attitudes towards Singapore English
  • Illustrate the variability in varieties of English in Singapore
  • Propose how the demonstrated variability in Singapore Englishes might be modelled
  • Collect naturally occurring speech samples
  • Use computer software to transcribe naturally occurring speech
  • Analyze the speech in detail
  • Develop analytical skills for the description of real data
  • Analyze quantitative data
  • Assemble findings into a substantial project
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