TalentLMS reports completion, progress and assessment results, but has no visibility into attention within a piece of content. Emotuit adds content-level engagement data — dwell, focus, tab-switching and drop-off position — through a sub-50KB script, alongside existing reporting rather than replacing it.
What TalentLMS already gives you
TalentLMS reports cover course completion, test scores, time spent, and per-user timelines of activity.
What it does not
"Time spent" is the metric to be most careful with. It is elapsed wall-clock time with the course open — not focused time. A unit left open in a background tab during a two-hour meeting reports as two hours of engagement.
This is not a criticism of TalentLMS specifically — it is true of essentially every LMS on the market. Completion and navigation data is what these systems were built to record, and they record it well. Attention is a different measurement problem, solved in the content layer rather than the platform layer.
How Emotuit fits
Add through Account & Settings → Customisation → Custom JavaScript. Content positions map to TalentLMS unit IDs.
The SDK is under 50KB, adds one script tag, and requires no migration or infrastructure change. It runs alongside TalentLMS's own reporting rather than replacing it.
Details
The time-spent trap
Focus-adjusting elapsed time is usually the single biggest change to the picture on TalentLMS deployments. Expect reported engagement to fall once you measure it honestly — that fall is information, not a regression.
Works with
Native units, SCORM, and embedded video content.
What you get
| Metric | Detail |
|---|---|
| Content-level engagement | A score for every section, not one per course |
| Drop-off position | Where sessions actually end |
| Focus-adjusted dwell | Real attention, discounting background tabs |
| Tab-switch rate | The strongest single predictor of disengagement |
| Replay behaviour | Where learners went back — a confusion signal |
| Cohort comparison | A/B test content versions on real attention |
Deployment options
Emotuit runs in two configurations, and for LMS deployments in the EU the choice matters.
Signals uses behavioural telemetry only — no camera, no biometric data, no emotion inference. It sits outside the EU AI Act Article 5(1)(f) prohibition on inferring emotions in workplace and education contexts, which makes it the default recommendation for corporate L&D and education.
Learn adds a client-side facial expression layer. It should not be deployed to EU employees or students, and is intended for market research, UX and media testing contexts.
Frequently asked questions
Does this replace TalentLMS's built-in reporting?
Does it need a webcam?
How long does integration take?
Will it slow the platform down?
See it on your own TalentLMS content
We'll instrument one module and show you the engagement data before you commit to anything.