TR5060 - Translation Tools and Technologies (2026/27)
| Module specification | Module approved to run in 2026/27, but may be subject to modification | ||||||||||
| Module title | Translation Tools and Technologies | ||||||||||
| Module level | Intermediate (05) | ||||||||||
| Credit rating for module | 15 | ||||||||||
| School | Guildhall School of Business and Law | ||||||||||
| Total study hours | 150 | ||||||||||
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| Assessment components |
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| Running in 2026/27(Please note that module timeslots are subject to change) |
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Module summary
Building on foundational translation technology modules at level 4, this module expands your understanding of the wide range of translation technologies available today. It introduces the principles and methods behind automatic, computer-assisted, and human-assisted translation systems, enabling you to compare and evaluate these technologies for their relevance to modern translation practice. After laying this groundwork, you will focus on machine translation (MT), MT pre- and post-editing (PrE and MTPE), MTPE evaluation, and their integration within Computer-Aided Translation (CAT) tools.
The module also explores AI-driven translation tools and their transformative effects on the industry. You will engage with various software programs and systems both theoretically and practically through hands-on sessions. These include troubleshooting workflow issues, comparing tool features, and reflecting on their impact on translators’ workflows and roles in professional settings. Ethical considerations such as data security, confidentiality, authorship, and responsible AI use are integral to these reflections.
In this module, you will therefore:
• Deepen your understanding of translation technologies, including automatic, computer-assisted, and human-assisted systems.
• Evaluate machine translation, post-editing, and their integration in CAT tools.
• Develop practical skills through hands-on engagement with industry software.
• Reflect on the ethical and professional implications of AI-driven tools in translation workflows.
This supports the integration of these technologies in other modules at this level.
Syllabus
The module introduces key CAT tools, focusing on their components and workflows to build foundational technical skills (LO1, LO4). You will then explore machine translation and post-editing, applying these tools in practical tasks while evaluating their effectiveness (LO3, LO4). A comparative study of translation memory systems follows, with emphasis on troubleshooting and workflow optimisation (LO2, LO3). Finally, you will examine AI-driven translation tools, assessing their impact on professional practice and their limitations (LO1, LO3, LO4).
Balance of independent study and scheduled teaching activity
This module is structured as a flipped classroom: you will perform all or most practical activities in class, under the supervision of the tutor, after engaging with instructional material at home. These activities attract regular formative feedback, which allows you to reflect on your progress and improve your performance as you go along.
Learning outcomes
By the end of this module, you will be able to:
1. Understand and critically evaluate a range of translation technologies, including automatic, computer-assisted, and human-assisted systems, understanding their principles, workflows, advantages, and limitations in professional contexts.
2. Apply and deploy machine translation and post-editing techniques effectively, critically assessing and differentiating the strengths and limitations of AI-driven tools across various translation scenarios.
3. Identify, troubleshoot and propose solutions to issues arising from the use of translation technologies in professional workflows.
4. Develop confidence, adaptability, and resilience in using translation tools to meet industry standards and expectations, effectively communicating detailed analysis and decisions where appropriate.