Course syllabus

2018, Semester 2 (30.00 points)


Course convenor:

Dr Vanessa Enriquez Raído



Dr Vanessa Enriquez Raído


Office hour: TBA

Class time:

Please check timetable and room details on Student Services Online for latest information.

Course description and objectives:

This course provides students with a wide range of computer skills and resources for professional translators, covering a number of translation-related IT topics from word processing to information research and management. Students will also gain knowledge on computer-assisted terminology management (e.g. SDL MultiTerm 2019); obtain hands-on experience in the use of proprietary computer-aided translation tools (e.g. SDL Trados Studio 2019); and develop critical thinking by, for example, preparing thorough presentations that examine the functionality and impact of various desktop translation memory tools (e.g. OmegaT and Across) and cloud-based translation memory systems (e.g. Wordfast Anywhere, Memsource Cloud, Wordbee and XTM Cloud) on translators and translations. Both proprietary and free, i.e. open-source translation memory systems support common features such as project management, translation memory maintenance, terminology management, machine translation, statistical reports, automated quality assurance, etc. This course is the perfect introduction to modern electronic translation environments, providing students with practical advice on how information research, terminology management, and translation memory systems can best be integrated into the translation process.

Main topics:

  • The Translator’s Workstation
  • Translation Tools and Information (Re)sources
  • Terminology Management and Web Search Strategies
  • Machine Translation and Post-Editing
  • Desktop and Cloud-based CAT Tools

Class content schedule:

Week 1
  • Course overview
  • The global translation context
  • The translator's workstation
  • Features and principles of CAT technology
Week 2
  • Principles of terminology management
  • SDL MultiTerm 2019
    • Searching termbases
    • Editing and adding entries
    • Importing glossaries
    • Creating termbases from scratch
Week 3
  • Web search strategies for translators
  • Typology of linguistic resources
  • Search engines, query types and query syntax
  • Machine-assisted Translation
    • Guidelines
    • Data
    • Resources

Assignment 1 (machine-assisted translation) handed-out

Week 4

SDL Trados Studio 2019

  • Overview of the user interface
  • Creating a translation memory from scratch 
  • Translating single files
Week 5

SDL Trados Studio 2019

  • Working with projects and project packages
  • Creating analysis reports and preparing quotes
  • Aligning files
  • Leveraging resources
  • Overview of other CAT tools for group presentations (sign-up sheet)

Assignment 1 (machine-assisted translation) handed in

 Week 6

SDL Trados Studio 2019

  • Processing multiple files with projects
  • Project statistics and reports
  • Translating the project files
  • Finalising the project
  • Guidelines for group presentations
Week 7

SDL Trados Studio 2019

  • Merging project files
  • Segment verification
  • Translating merged files
  • Reviewing files
Week 8

SDL Trados Studio 2019

  • Automated quality assurance
  • Finalising projects
  • Translation memory maintenance
Week 9

SDL Trados Studio 2019

  • Alignment and other leveraging resources
  • Q&A session: preparing for Assignment 2
  • Group work for oral presentations

Week 10

  • Assignment 2 (translation project) carried out in class
  • Group work for oral presentations

Weeks 11 & 12

  • Assignment 03 - Group presentations
    • Across, Wordfast Anywhere, MateCat, MemSource Cloud, XTM Cloud, et

Course materials:

Topic-related materials will be provided in class in the form of course-packs (i.e. training books). These will include theoretical explanations and practical exercises for each topic discussed. Course materials will also include PowerPoint presentations and other digital materials uploaded onto Canvas.

Teaching format and methods:

Course contents will be taught through lectures, guided group discussions and individual as well as collective practice. Teaching methods will promote both individual work and teamwork for students to develop their own specialised knowledge, intellectual skills and interpersonal qualities. Students will also have opportunities to actively participate in their own learning processes, structure their own learning experiences and relate them to the course syllabus, and gradually become independent learners.

Expectations of students:

Students are expected to read the contents in every course-pack, carry out multiple exercises on each topic discussed and demonstrate theoretical and technical knowledge regarding the use of various computer-aided translation tools. Students are also expected to actively participate in class, be involved in their own learning process and cross-evaluate peer work as required.

Student assessment:

All assessment is internal. The final grade will be composed of two assignments and one group presentation (see below) involving a series of practical and reflective activities and tasks aimed at applying the skills acquired in the course. Detailed instructions on each assignment will be provided and discussed in class.

Assignment 1 (worth 20%): Machine-assisted translation (Systran and Google Translate)

Assignment 2 (worth 45%): Translating with SDL Trados Studio 2019

Group presentation (worth 35%): Working in a group to introduce and assess a specific translation memory tool (desktop or cloud-based) and simulate a translation work environment.

Requirements for presentation and submission of work:

Assignments will be prepared electronically, uploaded onto Canvas and submitted in electronic format via e-mail.

File names

Please name your files in the following way: "FamilyName_StudentID_Assignment1#.doc"

Example: "Enriquez_ 234567_assignment1.doc"

Assignments policy:


In serious circumstances* beyond the student’s control (see below), s/he may request an extension from the course coordinator. The request should:

  • be made by email at least 2-3 days BEFORE the due date for the assignment
  • provide an explanation of the circumstances
  • be supported by a satisfactory medical certificate or other documentation

If an extension is granted, you will be given a new due date. Only ONE extension can be granted to a student per assignment. Only in extreme circumstances will late requests for extensions be considered.

*Serious circumstances means sudden illness (in the case of in-class tests etc.) or long-term illness (for essays etc. done over a week or more).  It does NOT mean time management difficulties, wanting to go on holiday, relatives visiting from overseas, computer breakdowns, etc.  

Deadlines and penalties for lateness

Any work submitted after the due date and without an extension form or permission in writing from the course convenor will be treated as overdue and penalties will apply (see below). 

The mark given to an overdue assignment will be reduced by up to 10 percent (at the discretion of the course convenor) of the total possible marks for that assignment for each day that it is late up to 5 days (e.g. for an assignment marked out of 20, deduct up to 2 marks per day up to a total of 10 marks). Assignments which are due on Friday, or the day before a university holiday, but are not received until the next working day will be counted as TWO days late.

Overdue assignments that are submitted more than five days late will not be marked; nor will assignments be marked if submitted after the assignment has been marked and returned.  Unmarked assignments will be held by the marker until the end of the semester, and in cases where the final grade for the student is borderline (D+), the marker may choose to award a minimal completion mark. For this reason, it is better to hand in an assignment late than not at all.

Plagiarism and use of information and communication technologies:


The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offense. The work that a student submits for grading must be the student's own work, reflecting his or her learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the world-wide web. A student's assessed work may be reviewed against electronic source material using computerized detection mechanisms. Upon reasonable request, students may be required to provide an electronic version of their work for computerized review.

The penalties for plagiarism are severe and can range from gaining no marks for the assignment to disciplinary action under the terms of the Examination Regulations. For further information and advice on University regulations and how to reference appropriately, see

All students entering the University are required to complete the Academic Integrity Module. For further information on this module please see

Information about third-party assistance in postgraduate coursework can be found here:

Information and communication technologies

If students in any course wish to set up a Facebook page for the course or to use any other form of ICT, they need to be aware that the  University of Auckland Information and Communications Technology (ICT) Statute sets out rules governing the use of any ICT hardware or software at or for University activities. It forbids using ICT “to store, display or communicate … files containing any text, image that is deceptive or misleading, is abusive or defamatory, contravenes anyone’s privacy… or that reproduces all or part of any work in breach of the Copyright Act 1994”. The Statute refers students to the relevant University Disciplinary Statute and the penalties that may apply. It can be found at

Inclusive learning:

Students are urged to discuss privately any impairment-related requirements face-to-face and/or in written form with the course convenor and course lecturers.

Complaint procedures:

The University of Auckland seeks to encourage the prompt and informal resolution of all students’ learning and research grievances as they arise. Students should be aware that support is available through either their class or faculty representative, the Student Advocacy Network or their Students' Association. For detailed information on academic disputes and complaints, see

Course summary:

Date Details