Research output per year
Research output per year
Si Chen, Haocong Cheng, Yun Huang
Research output: Chapter in Book/Report/Conference proceeding › Chapter
Metacognition, understood as the awareness of one’s own learning processes, plays a pivotal role in achieving effective learning outcomes. Recent work has shown the potential of AI-based emotion recognition technology to enhance learners’ metacognitive abilities during post-learning reflections. In this article, we present a novel interaction design that seamlessly integrates emotion recognition technology into the reflection process. The proposed solution captures and visualizes learners’ emotional states during self-regulated video-based learning activities, thereby facilitating deeper metacognition by offering insights into learners’ own emotions and those of their peers. We discuss the theoretical foundations of the proposed approach, its benefits, and ethical considerations for future research.
Original language | English (US) |
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Title of host publication | Trust and Inclusion in AI-Mediated Education |
Subtitle of host publication | Where Human Learning Meets Learning Machines |
Editors | Doura Kourkoulou, Anastasia Olga Tzirides, Bill Cope, Mary Kalantzis |
Publisher | Springer |
Pages | 185-212 |
Number of pages | 28 |
ISBN (Electronic) | 9783031644870 |
ISBN (Print) | 9783031644863, 9783031644894 |
DOIs | |
State | Published - Sep 28 2024 |
Name | Postdigital Science and Education |
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Volume | Part F3835 |
ISSN (Print) | 2662-5326 |
ISSN (Electronic) | 2662-5334 |
Research output: Book/Report/Conference proceeding › Book