Exploring Gesture and Gaze Proxies to Communicate Instructor's Nonverbal Cues in Lecture Videos
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Teaching via lecture video has become the defacto standard for remote education, but videos make it difficult to interpret instructors' nonverbal referencing to the content. This is problematic, as nonverbal cues are essential for students to follow and understand a lecture. As remedy, we explored different proxies representing instructors' pointing gestures and gaze to provide students a point of reference in a lecture video: no proxy, gesture proxy, gaze proxy, alternating proxy, and concurrent proxies. In an online study with 100 students, we evaluated the proxies' effects on mental effort, cognitive load, learning performance, and user experience. Our results show that the proxies had no significant effect on learning-directed aspects and that the gesture and alternating proxy achieved the highest pragmatic quality. Furthermore, we found that alternating between proxies is a promising approach providing students with information about instructors' pointing and gaze position in a lecture video.
Original language | English |
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Title of host publication | CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems |
Number of pages | 7 |
Publisher | Association for Computing Machinery, Inc. |
Publication date | 2023 |
Article number | 113 |
ISBN (Electronic) | 9781450394222 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany Duration: 23 Apr 2023 → 28 Apr 2023 |
Conference
Conference | 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 |
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Land | Germany |
By | Hamburg |
Periode | 23/04/2023 → 28/04/2023 |
Sponsor | ACM SIGCHI, Apple, Bloomberg, Google, NSF, Siemens |
Bibliographical note
Publisher Copyright:
© 2023 Owner/Author.
- Education, Eye-tracking, Gaze, Gesture, Lecture video
Research areas
ID: 347300683