Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks
Self-confidence is a crucial trait that significantly influences performance across various life domains, leading to positive outcomes by enabling quick decision-making and prompt action. Estimating self-confidence in video-based learning is essential as it provides personalized feedback, thereby en...
Saved in:
| Main Authors: | Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10792912/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EyeUnderstand: Dashboard for Gaze and Deep-Learning Driven Comprehension Estimation in Online Lectures
by: Ko Watanabe, et al.
Published: (2025-01-01) -
Gaze-Driven Adaptive Learning System With ChatGPT-Generated Summaries
by: Jayasankar Santhosh, et al.
Published: (2024-01-01) -
Validation of an Eye-Tracking Algorithm Based on Smartphone Videos: A Pilot Study
by: Wanzi Su, et al.
Published: (2025-06-01) -
Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking"
by: Béatrice Hasler, et al.
Published: (2024-06-01) -
Automatic Classification of Difficulty of Texts From Eye Gaze and Physiological Measures of L2 English Speakers
by: Javier Melo, et al.
Published: (2025-01-01)