QA for eLearning: The Exact Checks That Catch 90% of Errors Before Launch
Most eLearning problems are not “big.” They’re small defects that slip through because nobody owned QA, nobody followed a consistent test flow, or everyone assumed someone else would catch it. A typo in a safety step. A Next button that doesn’t trigger on one slide. A variable that resets when you revisit a scene. A quiz that reports completion in preview but not in the LMS. None of these issues are hard to fix—what’s hard is discovering them after launch, when learners are blocked, stakeholders are frustrated, and your team is in emergency mode.
Good QA isn’t a long, painful phase. It’s a repeatable system. When you run QA in lanes and follow the same checks every time, you catch the majority of errors quickly and consistently before they reach learners.
Why eLearning QA fails
QA usually fails for three simple reasons.
First, teams don’t use a checklist. They “click around” and hope they notice issues. That approach depends on memory and attention, which means defects slip through unpredictably.
Second, there’s no clear ownership. If QA is everyone’s responsibility, it becomes nobody’s responsibility. People assume the developer tested it. The developer assumes the instructional designer reviewed it. The ID assumes the SME will catch accuracy. The SME assumes QA is technical. Meanwhile, the course ships with obvious issues.
Third, teams don’t have a test flow. They test randomly, out of order, and inconsistently. The result is that critical paths—resume behavior, completion, score reporting—sometimes aren’t tested at all until the day the course goes live.
If you fix those three things, you catch most errors before launch.
QA lanes: Content QA → Functional QA → LMS QA
The fastest way to make QA reliable is to separate it into three lanes that match how eLearning fails in the real world.
Content QA answers: Is it correct, clear, consistent, and readable?
Functional QA answers: Does everything work as designed inside the course?
LMS QA answers: Does it launch, resume, complete, and report correctly in the LMS environment?
If you run these lanes in order, you avoid wasting time. You don’t spend hours debugging LMS tracking when the real problem is that a button state never triggered because a layer name changed.
Content QA (fast, brutal, effective)
Content QA is where you catch the errors that damage credibility fastest. It should be quick and systematic, not perfectionist and endless.
Start by scanning for typos, punctuation errors, and formatting inconsistencies that break trust. Then check terminology and naming. If the course says “lockout/tagout” in one place and “LOTO” in another, or refers to the same tool using different names, learners assume the content is sloppy—even if the procedure is correct.
Next, validate clarity. Instructions should not require interpretation. If a learner can misunderstand what to click, what to do next, or what a correct response looks like, you will see support tickets and rework. Finally, confirm consistency across screens. Titles should match objectives, objectives should match what is taught, and what is taught should match what is assessed.
Content QA is not about making writing “nice.” It is about removing ambiguity that causes mistakes.
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Functional QA: does the course behave correctly?
Functional QA is where most “it works on my machine” issues are born. It’s not enough that the course generally plays. The question is whether it behaves correctly across every learner path.
You test navigation first because it is the highest-impact failure. Every Next, Back, menu item, and scene jump must work. Then you test states and triggers: when a learner clicks something, does it change state properly? If they revisit a scene, do completed items stay completed? If you have gating logic, does it unlock at the correct moment and never earlier?
If your course uses layers, variables, or conditional logic, this is where you verify it. You want to intentionally break it by trying unexpected learner behavior: skipping around, clicking fast, revisiting screens, failing a question, retrying, closing and reopening. Real learners do all of this. If the logic can’t survive it, the course will fail in the field.
Accessibility behaviors should be checked here as well. That doesn’t mean you need a full formal audit to catch the biggest failures. It means confirming that keyboard navigation behaves reasonably, focus order isn’t chaotic, and interactive elements aren’t invisible to assistive tech expectations where required.
Media QA: audio, captions, and performance
Media problems are some of the most common launch-day complaints because they are immediately noticeable and hard for learners to work around.
Audio should be checked for sync with on-screen action, clean starts and ends, and consistent volume from clip to clip. If narration volume jumps between slides, learners interpret the entire course as unprofessional even if the content is excellent.
Captions should be checked for timing and accuracy. Even small caption errors are credibility killers in compliance or safety content, and poor timing frustrates users who rely on them. Finally, check video compression artifacts and playback performance. If a video stutters, looks degraded, or takes too long to load, learners disengage and skip. Media should support performance, not slow it down.
Assessment QA: accuracy, feedback, and reporting logic
Assessment QA is where teams often lose trust after launch, because incorrect answers or wrong feedback makes learners question the entire program.
You verify that correct answers are actually marked correct. You verify that distractors behave as expected. You verify that feedback matches the logic and teaches something useful rather than simply saying “incorrect.”
Then you check scoring rules. If passing score is 80%, does the course enforce that consistently? If retries are allowed, does it reset correctly? If the learner fails, does remediation route them properly? If the course includes multiple quizzes, which one is the reporting quiz?
Assessment QA isn’t about “does the quiz exist.” It’s about ensuring that the assessment is defensible, consistent, and technically aligned with reporting.
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LMS QA: completion, resume, scoring, bookmarking
LMS QA is where teams often discover painful surprises, because the course behaves differently in the LMS than it does in preview.
The first check is completion triggers. The course must trigger completion exactly the way you intended. Then verify resume behavior. Exit mid-course, relaunch, and confirm that the learner returns where expected with the correct states preserved. Next, verify scoring and reporting. Complete the course, confirm that the LMS shows status, score, attempts, and time as expected. If there’s any mismatch between course settings and LMS settings, this is where it appears.
This lane should always be done in a real staging environment, not just in a review link. “Preview works” is not an LMS test.
The single decision that prevents launch-day disasters
Most launch-day disasters happen because teams never aligned on one thing:
What is our definition of DONE for this course?
If “done” means “content is approved,” you will launch with functional defects.
If “done” means “it plays in preview,” you will launch with LMS issues.
If “done” means “it looks good,” you will launch with broken scoring, unclear instructions, or inconsistent terminology.
A strong definition of done includes content accuracy, functional stability across paths, and confirmed LMS reporting behavior. When that definition is explicit, QA stops being optional and becomes the final gate that protects the rollout.
Make it visible: the QA operating system that keeps quality consistent
QA becomes reliable when it is visible and structured.
A simple QA tracker makes defects concrete: what was found, where it is, severity, owner, and status. A sign-off chain prevents ambiguity: who approves content, who approves functionality, who approves LMS behavior. Defect severity buckets help teams prioritize so critical issues are fixed first and cosmetic polish doesn’t delay launch unnecessarily. Retest rules prevent false confidence by ensuring every fix is rechecked and nothing is marked resolved without verification.
When these elements exist, QA becomes predictable instead of chaotic.