LO
English / Foreign languages
Trains you to work precisely in a second language — and, less obviously, to research an unfamiliar subject fast and explain it to someone who does not share your context.
Do one of the four verification actions above — properly, once. One finished artefact beats four half-started ones.
A single number for a whole major would hide the thing that matters: this degree trains several separate competencies, and they are not all moving in the same direction. Automation acts on tasks, so any assessment lives on the occupation pages below — not here.
Written for four-year language degrees in China and comparable programmes elsewhere. Interpreting-specific and teaching-track programmes differ.
What this degree actually trains#
Not the course list — the competencies underneath it, and whether each one is worth more or less than it was.
Precision in a second language
Worth less on its ownKnowing that two phrasings which look equivalent are not, and being able to say why.
Machine translation now handles the common case well on high-resource pairs, so precision alone no longer commands a price. It becomes valuable again when attached to a domain where being wrong is expensive.
Researching an unfamiliar subject fast
Worth more than beforeFour years of translating texts about things you did not study taught you to get to working competence in a new subject in days.
This is the skill most language graduates do not know they have, and it is exactly what research, product and consulting roles pay for. It is also the hardest thing to automate, because knowing which question to ask next is the whole job.
Explaining across contexts
Worth more than beforeRewriting the same content for an audience with different assumptions, and knowing which assumptions differ.
Models produce fluent target-language text but do not know what a specific audience already believes. Judging that requires having lived in both contexts.
Written discipline
HoldingProducing a lot of finished prose on a deadline, and editing your own work honestly.
Generation made drafts free, which shifted the value to editing. Knowing what to cut is still learned by writing a great deal.
Where it can lead#
4 directions, never one. Each is written out in full on its own page — what your training reuses, what graduates typically lack, the entry reality, and one thing to test this term.
What to add outside the classroom#
This is about what graduates commonly lack in practice — not a claim that your school failed to teach it.
A second domain, chosen deliberately. Language plus law, medicine, product or finance is a position; language alone increasingly is not.
Version control and a terminology tool. A week of effort that removes a whole category of rejection.
Post-editing practice with honest measurement: how long does it take you to find the confidently-wrong sentence in fluent machine output?
This term#
One or two actions, each producing something you can show someone. Not a reading list.
Do one of the four verification actions above — properly, once. One finished artefact beats four half-started ones.
Interview one person doing each of your top two paths. Ask what they underestimated, not what they like.
Common questions#
The part of the degree aimed at producing first-draft translations of routine text is the part being automated — that is real and worth saying plainly. But the degree also trains two things that got more valuable: getting to working competence in an unfamiliar subject fast, and judging what a specific audience will actually understand. Most graduates never learn to name those, which is why they compete for the one job that is shrinking. Pick a second domain and the training becomes a position rather than a liability.
Not as a reflex. The entry-level end of software is under its own pressure — the routine coding that used to pay juniors while they built judgement is the part being automated, so 'switch to programming' is not the safe move it was five years ago. If you are drawn to it, that is a reason; if you are fleeing translation, look first at localisation, research and international operations, which reuse what you already have instead of restarting from zero.
This site deliberately does not score majors, and the reason matters here: a degree is not a job. What varies is which occupations it feeds and how exposed those are — translation is one of the most exposed occupations we assess, while editing, teaching and communications roles sit very differently. Switch because the paths you would actually take have changed, not because the subject sounds vulnerable.
Ask what the extra years buy that the first degree did not. For routes that are licensed or credential-gated — teaching, some public-sector roles — the answer is concrete. For translation and content work it usually buys neither a licence nor a client, and two more years of tuition against a market that repriced is a poor trade. Write down the specific job the degree unlocks before committing.
Evidence that you can judge language, not produce it. A folder of before-and-after edits where you can explain each change is worth more to an employer than a portfolio of clean prose, because clean prose is now the cheap part. The same applies if you head for teaching or communications — the judgement is the transferable asset.
Method#
Assessments live on tasks, not on majors. Follow any direction above to its occupation page to see which tasks are changing, how strong the evidence is, and what it does not yet show.