This thesis explores the enhancement of active reading experiences through a human-machine co-creation process, focusing on visualized narratives. The project addresses the limitations of traditional reading materials that often neglect the individuality of readers in visualizing narratives. To bridge this gap, the project adopts a modified ZEN design approach, emphasizing user rituals and the integration of AI tools for visualizing mental models. By integrating artificial intelligence (AI) and generative technologies, the project combines human creativity with machine efficiency, aiming to create personalized digital reading experiences that cater to individual cognitive abilities and preferences.
The project begins with a comprehensive literature review that establishes the theoretical foundation for understanding narrative books and active reading. Realizing each one's active reading process and mental images regarding the same contents are different, the core of this project is to create a personalized active reading journey. Then, design vision is proposed to identify design goals and value delivery. To understand the actual user ritual, qualitative user research is conducted to study the reading activities and mental models of active readers. Then, through competitive products research, mental image visualization is found to be the active reading function currently missing in the reading products on the market. Thanks to the emerging AIGC technology, it becomes possible to generate desired visual images for people with different mental imagery abilities with high efficiency and quality. By strategically synthesizing the user requirements with image generation workflow, design round 1 focuses on content personalization. 2 solution flow was designed and tested by 10 participants with different mental imagery abilities (results from VVIQ test). After iterating the solution flow of mental image visualization function, design round 2 is conducted to realize toolkit personalization. Scenebites as an integrated active reading platform is introduced, empowering diverse user rituals of active processes. The value proposition of design vision and key user needs are validated through focus group research.
The final design output of this project is a human-machine collaborative system flow for personalized digital reading experience on knowledge construction, together with business model propositions for future libraries. The results demonstrate that personalized visualizations significantly enhance active reading experiences by reducing cognitive load and increasing engagement. And the assistance of visual options and editable mood boards in the user journey can positively match the requirements from users with diverse visual imagery abilities.
The project also suggests improvements in AI models to enhance precision and control in generating visuals. It also recommends strategies for libraries and educational institutions to integrate personalized reading services, thereby transforming the digital reading landscape into a more interactive and user-centered journey.