Exploring the Role of User Comments Throughout the Stages of Video-Based Task-Learning
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917337802735616 |
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| author | Kim, Nayoung Sechayk, Yotam Zhou, Zhongyi Igarashi, Takeo |
| author_facet | Kim, Nayoung Sechayk, Yotam Zhou, Zhongyi Igarashi, Takeo |
| contents | Learning tasks through videos is a dynamic way to acquire skills by witnessing entire processes. However, compared to in-person demonstrations, videos may omit tacit knowledge, including subtle details and contextual nuances. Users' unique circumstances, like missing ingredients in a recipe, may also require adaptation beyond the video content. To fill these gaps, many users turn to the comment section, seeking additional guidance and interactions with creators or peers to personalize their experience. Despite their importance, there is limited understanding of how users engage with and apply comments in task-learning scenarios. In our study, we explore the role of comments in video-based task-learning through interviews with 14 users, and co-watching sessions with eight. Our findings show that while comments are critical for learning, they are poorly integrated into all stages of the learning process. Based on our findings, we outline design opportunities to better utilize comments in video-based task-learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_12509 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Exploring the Role of User Comments Throughout the Stages of Video-Based Task-Learning Kim, Nayoung Sechayk, Yotam Zhou, Zhongyi Igarashi, Takeo Human-Computer Interaction Learning tasks through videos is a dynamic way to acquire skills by witnessing entire processes. However, compared to in-person demonstrations, videos may omit tacit knowledge, including subtle details and contextual nuances. Users' unique circumstances, like missing ingredients in a recipe, may also require adaptation beyond the video content. To fill these gaps, many users turn to the comment section, seeking additional guidance and interactions with creators or peers to personalize their experience. Despite their importance, there is limited understanding of how users engage with and apply comments in task-learning scenarios. In our study, we explore the role of comments in video-based task-learning through interviews with 14 users, and co-watching sessions with eight. Our findings show that while comments are critical for learning, they are poorly integrated into all stages of the learning process. Based on our findings, we outline design opportunities to better utilize comments in video-based task-learning. |
| title | Exploring the Role of User Comments Throughout the Stages of Video-Based Task-Learning |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2603.12509 |