Emotion Based Prediction in the Context of Optimized Trajectory Planning for Immersive Learning
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866911785190162432 |
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| author | Sungheetha, Akey R, Rajesh Sharma R, Chinnaiyan |
| author_facet | Sungheetha, Akey R, Rajesh Sharma R, Chinnaiyan |
| contents | In the virtual elements of immersive learning, the use of Google Expedition and touch-screen-based emotion are examined. The objective is to investigate possible ways to combine these technologies to enhance virtual learning environments and learners emotional engagement. Pedagogical application, affordances, and cognitive load are the corresponding measures that are involved. Students will gain insight into the reason behind their significantly higher post-assessment Prediction Systems scores compared to preassessment scores through this work that leverages technology. This suggests that it is effective to include emotional elements in immersive learning scenarios. The results of this study may help develop new strategies by leveraging the features of immersive learning technology in educational technologies to improve virtual reality and augmented reality experiences. Furthermore, the effectiveness of immersive learning environments can be raised by utilizing magnetic, optical, or hybrid trackers that considerably improve object tracking. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_11576 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Emotion Based Prediction in the Context of Optimized Trajectory Planning for Immersive Learning Sungheetha, Akey R, Rajesh Sharma R, Chinnaiyan Human-Computer Interaction Computer Vision and Pattern Recognition Multimedia In the virtual elements of immersive learning, the use of Google Expedition and touch-screen-based emotion are examined. The objective is to investigate possible ways to combine these technologies to enhance virtual learning environments and learners emotional engagement. Pedagogical application, affordances, and cognitive load are the corresponding measures that are involved. Students will gain insight into the reason behind their significantly higher post-assessment Prediction Systems scores compared to preassessment scores through this work that leverages technology. This suggests that it is effective to include emotional elements in immersive learning scenarios. The results of this study may help develop new strategies by leveraging the features of immersive learning technology in educational technologies to improve virtual reality and augmented reality experiences. Furthermore, the effectiveness of immersive learning environments can be raised by utilizing magnetic, optical, or hybrid trackers that considerably improve object tracking. |
| title | Emotion Based Prediction in the Context of Optimized Trajectory Planning for Immersive Learning |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition Multimedia |
| url | https://arxiv.org/abs/2312.11576 |