@inproceedings{0e14d14d174449188f1f429eedd8c724,
title = "Mirror Hearts: Exploring the (Mis-)Alignment between AI-Recognized and Self-Reported Emotions",
abstract = "Previous research has found that learners' reflections on their own emotions can improve their learning experience, and AI-based technologies can be used to automatically recognize learners' emotions. We conducted user studies involving 32 participants to investigate the relationship between AI-recognized emotions and their self-reported emotions using emojis and text comments. We found that, even though AI recognized a similar amount of positive-high-arousal and negative-low-arousal emotions, participants self-reported more positive-high-arousal emojis. Participants explained the causality and temporality of the self-reported emojis using text comments. Our findings suggest ways of using AI to capture learners' emotions and support their reflections.",
keywords = "Emoji, Facial Recognition, Reflection, Self-Regulated Learning",
author = "Si Chen and Haocong Cheng and Jason Situ and Yun Huang",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 ; Conference date: 23-04-2023 Through 28-04-2023",
year = "2023",
month = apr,
day = "19",
doi = "10.1145/3544549.3585607",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems",
address = "United States",
}