Articulate Storyline 360 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 Articulate Storyline 360 already gives you
Storyline tracks slide progress, interaction states, variables and quiz results, reporting to the LMS via SCORM or xAPI.
What it does not
Storyline has excellent interaction data — it knows exactly which buttons were clicked. It has no attention data. A slide showing for four minutes with the window minimised looks the same as four minutes of study.
This is not a criticism of Storyline specifically — it is true of essentially every authoring tool 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 via a JavaScript trigger on the first slide. Slide and scene IDs become content positions, so engagement lands against your existing project structure. Emits xAPI statements alongside Storyline's own.
The SDK is under 50KB, adds one script tag, and requires no migration or infrastructure change. It runs alongside Storyline's own reporting rather than replacing it.
Details
Pairs well with variables
Storyline variables can receive the engagement score, letting you branch on attention — for example routing a disengaged learner to a shorter reinforcement path.
Works with
Slides, layers, scenes, interactive objects and embedded video.
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 authoring tool 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 Storyline'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 Storyline content
We'll instrument one module and show you the engagement data before you commit to anything.