Jiayi Wu 0003

dblp:51/1096-3 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2023
0000-0001-9660-7066ORCID · verified

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Human-computer interaction and ubiquitous computing · 4 · 4 since 2021
YearPublicationVenuePosition
2023 Observe It, Draw It: Scaffolding Children's Observations of Plant Biodiversity with an Interactive Drawing Tool
abstract
Observation is common for children to connect with nature, increasing their knowledge and awareness of biodiversity. However, it is challenging for them to make and document their observations due to a lack of observation and drawing skills. Therefore, we designed an interactive drawing tool, Bio Sketchbook, which scaffolds children in systematic observation, observational drawing, and knowledge acquisition. It can recognize plant species and generate contour drawings from children’s photographs, guiding them to observe and draw multi-dimensional plant features with a digital magnifier and in-context biological information. Our in-situ user study with 19 children revealed that Bio Sketchbook provided an engaging experience and effectively supported children in recording and retaining biodiversity information and in balancing observations with screen time. Additionally, Bio Sketchbook intervened in children’s interaction with plants by prompting observational behaviors, encouraging them to directly touch and establish rapport with plants, and arousing their interest and knowledge of plants.
Chao Zhang 0082, Yajing Hu, Lanjing Liu, Jiayi Wu 0003, Yaping Shao, Hangyue Chen, Fangtian Ying
IDC5
2022 StoryDrawer: A Child-AI Collaborative Drawing System to Support Children's Creative Visual Storytelling
abstract
Visual storytelling is a new approach to creative expression based on verbal and figural creativity. The keys to visual storytelling are narrating and drawing over a period of time, which can be beneficial but also demanding on creativity for children. Informed by need-finding investigations, we developed StoryDrawer, a co-creative system that supports visual storytelling for children aged 6–10 years through collaborative drawing between children and artificial intelligence (AI). The system includes a context-based voice agent and two AI-driven collaborative strategies: the real-time transformation of children's telling into drawings, and the generation of abstract sketches with semantic similarity to existing story content. We conducted a 2 × 2 study with 64 children to evaluate the efficacy of StoryDrawer by varying the two strategies in four conditions. The results suggest that StoryDrawer provoked participants’ creative and elaborate ideas and contributed to their creative outcomes during an engaging visual storytelling experience.
Chao Zhang 0082, Jiayi Wu 0003, Weijia Lin, Ge Yan 0002, Fangtian Ying
CHI3
2022 A Tool to Facilitate the Cross-Cultural Design Process Using Deep Learning
abstract
Cross-cultural design requires designers to understand other foreign cultures, selecting suitable cultural elements, and finally incorporate them into product design. Traditionally, this process is time-consuming and relies to a significant extent on designers’ cultural awareness and design skills. This article proposes a new tool for designers to select and integrate cultural elements in the cross-cultural design process. The proposed approach utilizes state-of-the-art deep learning techniques, which begins by automatically selecting the most suitable style image from all cultural image candidates. Then, the deep-learning-based style transfer technique is introduced to automatically produce a design image that has the same content as the uploaded design content image, and also has the cultural style of the selected style image. To the best of our knowledge, this is the first work that extends deep learning techniques to facilitate cross-cultural design. The tool received positive feedback in a usability evaluation. The empirical results show that our approach can effectively increase designers’ cultural awareness in respect of four cultural element dimensions (color, material, pattern and form). It is an innovative and efficient tool to help designers with idea generation and fast prototyping, although some participants argued that the tool would only assist designers, rather than replace humans.
Leijing Zhou, Xu Sun 0002, Guannan Mu, Jiayi Wu 0003, Jiangping Zhou, Qiuning Wu, Yaorun Zhang, Yufan Xi, Nesrin Dilber Günes, Siyang Song
IEEE Trans. Hum. Mach. Syst.4
2021 Bio Sketchbook: an AI-assisted Sketching Partner for Children's Biodiversity Observational Learning
abstract
Observational sketching is a common method to facilitate repeated observations that increase individual knowledge and awareness of biodiversity. However, this method presents a high barrier of entry for some novices, particularly young children. In this paper, we introduce Bio Sketchbook, a novice AI-assisted sketching partner to help children draw from observation and guide them to repeatedly observe different biological features. We describe our design process and goals, the interaction design of Bio Sketchbook, and results from a preliminary user study with six children. Our findings reveal Bio Sketchbook as a promising AI partner to encourage children to sketch from observation and gain biodiversity science education.
Chao Zhang 0082, Jiayi Wu 0003, Yajing Hu, Yaping Shao, Fangtian Ying
IDC3