Author
Listed:
- Hongbo Zhang
(Department of Engineering Technology, Middle Tennessee State University, Murfreesboro, TN 37132, USA
These authors contributed equally to this work.)
- Benjamin Li
(Department of Data Science, Middle Tennessee State University, Murfreesboro, TN 37132, USA
These authors contributed equally to this work.)
- Gregory Rushton
(Tennessee STEM Education Center, Middle Tennessee State University, Murfreesboro, TN 37132, USA
These authors contributed equally to this work.)
Abstract
Embodied learning involves the use of the physical embodiment of hands-on experiences, including gestures, body language, and gaze, during the instructional process for facilitation of the learning outcomes of robotics technology. Understanding the embodiment process is however challenging. In this research, large language model-based video understanding was used for the study of the effectiveness of embodied learning of robotics technology. Embodied and conventional videos were randomly selected, and the user comments were correlated with the transcript and summary of the videos. Results showed that there were higher numbers of user comments correlated with video content for the embodied learning-centered robotics instructional videos than the conventional learning-centered approach in terms of user sentiment and logical reasoning. The sentiment analysis of the video comments showed that the use of embodied learning was effective in achieving engagement in learning robotics, yielding fewer numbers of negative comments in comparison to the conventional learning videos. The embodied learning-centered videos were also helpful to enhance the logical reasoning of students. This user study shows that embodied learning is effective in engaging students, granting more positive sentiments toward the videos. Similarly, the logical reasoning of the students was also enhanced through the use of embodied learning for learning robotics technology.
Suggested Citation
Hongbo Zhang & Benjamin Li & Gregory Rushton, 2026.
"Novel Video Understanding Approach for Embodied Learning of Robotics Technology,"
Future Internet, MDPI, vol. 18(2), pages 1-20, February.
Handle:
RePEc:gam:jftint:v:18:y:2026:i:2:p:108-:d:1868009
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