How to translate a SCORM file, step by step

A SCORM file is a zip containing a small website: HTML pages, JavaScript, media, and an imsmanifest.xml that tells your LMS how to launch it. Translating one well means replacing every learner-facing string while leaving the machinery alone. Here is the whole workflow with Lokalizeit, plus the advice that applies no matter what tool you use.

Step 1: Export a fresh SCORM zip

Publish or export the course from your authoring tool — Articulate Storyline, Rise 360, or anything else that produces a SCORM package. Export fresh rather than digging up an old zip: stale exports have a way of missing recent content edits, and you want the translation to match what learners currently see. Do not unzip and re-zip the package by hand along the way; folder-depth mistakes during manual re-zipping are one of the most common reasons an LMS rejects a package.

Step 2: Upload the zip

Upload the package to Lokalizeit. The pipeline walks the archive, identifies the translatable text in the HTML and course data files, and counts the words. Code, styles, media, and the manifest structure are set aside to be copied through untouched.

Step 3: Pick a target language and quality tier

Choose one of 13 target languages and one of three quality tiers — Lite for fast drafts, Standard for everyday quality, Pro for the highest quality with an extra refinement pass. Tiers are priced per word, so the choice is per course, not per contract.

Step 4: Review the quote

Before anything runs, you see the exact credit cost: word count times the tier multiplier. Translation memory discounts apply automatically — segments that repeat exactly are billed at 10% of the per-word rate, fuzzy matches at 70%. Courses repeat themselves constantly (think of every "Continue" button), so real quotes routinely come in below the naive word count.

Step 5: Review segments, guided by fidelity

When the run finishes, each file carries a 0–100 fidelity score and a warning list. Do not read every segment — read the flagged ones. A high score means spot-check names and terminology and move on; a lower score points you at the exact segments where formatting, numbers, or completeness tripped a check. Edits recompute the score, so you can watch it climb as you fix things.

Step 6: Download the translated package

Export produces a new SCORM zip with the original folder structure and a manifest patched to declare the target language. The runtime code that reports completion to your LMS ships unchanged.

Step 7: Re-import and test

Import the package into your LMS the same way you imported the original. Then run through it once as a learner: launch it, answer a quiz question, and confirm completion registers. This takes ten minutes and catches the problems that only surface inside a real LMS.

Advice that applies to any tool

• Text in images will not auto-translate. Screenshots, diagrams, and buttons drawn as graphics keep their English text in every workflow that starts from an exported package. Inventory them early — Lokalizeit surfaces embedded images with AI-written descriptions to make that inventory fast — and budget designer time for the ones that matter.
• Keep one source of truth. Fix content bugs in the English source and re-translate, rather than patching each language by hand. Hand-patched languages drift apart within two release cycles.
• Test completion, not just rendering. A package can look perfect and still fail to report a score. Always verify tracking in a test environment before assigning the course to learners.
• Going right-to-left? Read up first. Arabic output has its own set of traps — seven RTL localization problems covers them, and the Arabic & RTL page explains how Lokalizeit handles them.

For a deeper look at what goes wrong when this workflow is done badly, see 7 things that break when you translate a SCORM package, or start from the SCORM translation overview and pricing.