Emotionally Enriched Feedback via Generative AI
Omar Alsaiari, Nilufar Baghaei, Hatim Lahza, Jason Lodge, Marie Boden,, Hassan Khosravi

TL;DR
This study explores how emotionally enriched AI feedback affects student perceptions and emotions in higher education, showing benefits in emotional well-being but no significant impact on engagement or work quality.
Contribution
It introduces emotionally enriched AI feedback in education and evaluates its effects, highlighting emotional considerations in educational technology design.
Findings
Reduces negative emotions like anger
Perceived as more beneficial by students
No significant change in engagement or work quality
Abstract
This study investigates the impact of emotionally enriched AI feedback on student engagement and emotional responses in higher education. Leveraging the Control-Value Theory of Achievement Emotions, we conducted a randomized controlled experiment involving 425 participants where the experimental group received AI feedback enhanced with motivational elements, while the control group received neutral feedback. Our findings reveal that emotionally enriched feedback is perceived as more beneficial and helps reduce negative emotions, particularly anger, towards receiving feedback. However, it had no significant impact on the level of engagement with feedback or the quality of student work. These results suggest that incorporating emotional elements into AI-driven feedback can positively influence student perceptions and emotional well-being, without compromising work quality. Our study…
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Taxonomy
TopicsNeural Networks and Applications
