The objective of this project is to design an adaptive learning interface that adjusts content difficulty, pacing, and presentation style based on real-time emotional feedback. The interface should respond dynamically to learner frustration, boredom, or engagement levels.
Research affective computing and emotion-detection technologies.
Define personas representing different learner personality types.
Map adaptive interaction flows triggered by emotional states.
Design low-fidelity wireframes showing dynamic content adjustment panels.
Create UI variations for calm, stressed, and highly engaged states.
Develop high-fidelity prototypes simulating emotional state changes.
Incorporate transparency indicators explaining adaptation logic.
Conduct usability testing focusing on comfort and personalization acceptance.
Refine transitions to avoid abrupt UI shifts.
Document ethical implications and emotional UX guidelines.
