Valence and arousal are the two axes of the circumplex model of affect: valence runs from unpleasant to pleasant, arousal from calm to activated. Together they place emotional state in a continuous two-dimensional space.
What it is
The model, associated with James Russell, is an alternative to discrete-category approaches like the Ekman seven. Rather than classifying an expression as 'anger' or 'sadness', it locates it by pleasantness and activation.
Boredom sits low-arousal and mildly negative; frustration sits high-arousal and negative. Both would be lumped together by a coarse categorical model.
Why it matters
For engagement specifically, arousal is often more informative than valence. A learner who is negative but activated is still engaged and possibly about to learn something; one who is neutral and deactivated has checked out.
A common confusion
Dimensional models are frequently presented as more scientifically robust than categorical ones. They avoid some problems with discrete categories but rest on the same underlying question of whether internal states can be reliably read from external signals.
Related
See also affective computing, emotion ai and facial action coding system (facs). See the full glossary for the rest, or the limits of facial emotion recognition for the wider context.
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