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comments to selected short videos and developed two new classification schemes: comment characteristics (information, feedback, opinion, general conversation) and commenters’ attitudes (constructive and positive, judgmental and negative, and irrelevant). The statistics show that that less users are actually participating knowledge-related activities (30%) while viewing drawing videos in these platforms by leaving information and feedback types of comments [Table 3]. We also found that those users are more likely to show a constructive and positive knowledge learning and sharing attitude and focused them as a main target group. While our design recommendation for comment categorization targets at this specific group of active users, there are far more passive users who browse and watch videos but rarely leave any comment (i.e., Content Browser). Personalized search and archival of videos and setting and tracking learning goals could lower the barrier of creating and sharing skill-practicing videos in these platforms. This study further tracked and analyzed public data from Bilibili and TikTok users that can reflect knowledge-related activities. Using regression analysis, we uncovered that as Bilibili supports creating and uploading multi-media file formats, users who post more videos are more likely to post more images as well. Users prefer to post their drawing creations in image format versus video format since sharing drawings by images is easier. Another result showed that TikTok is a decentralized UGC community, where users receive reactions and feedback based on the quality and quantity of their work, regardless of the number of followers they have. These findings are further discussed above as design strategies to facilitate user creation and interaction in short-video platforms. This study also finds three major user groups through the patterns of users’ data by dendrogram: Content Browser group, Learner Creator group and Creator group. The percentage of Creator group (19.5%) on TikTok is greater than on Bilibili (5%), showing that more TikTok users create and share their work as diverse posts are revealed to public regardless of the popularity of creators. Based on the user group categories synthesized by the quantitative research, this study also conducted pilot interviews with 12 TikTok users via direct messages to further understand experience of knowledge learning and sharing through the platform. The results are synthesized into five distinct types of personas and user journey and experience phases for each persona, concluding with three design recommendations: 1) promote creative practice through social interaction, 2) provide video previews and comment categories, and 3) support for personal tracking, assessing, and guiding creative practice. In summary, the findings of this study imply the potential of new learning models with short videos and social media platforms. The five personas and their user journey maps will provide a constructive foundation to design new platform services and experiences for collaborative learning of creative skills. The methods used for analyzing and identifying distinct user groups could be applied to other online user experience research in the future. Still, this study has access to only public user data and it is hard to generalize the findings. Also, we do not have a concrete understanding about the expectations and behaviors of passive users who only watch videos for personal practice but do not engage in any online activities. Broader user recruiting and face-to-face interview could lead to in-depth conversations regarding users’ expectations and suggestions for improving their learning experience in short video sharing platforms. In future work, the personas and user journey maps could be validated with more comprehensive data from a larger sample and also applied for ideating and developing new short video platform services to support creative practice.PDF Image | Learning and Sharing Creative Skills with Short Videos
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