Sketchnoting is the process of creating a visual record with combined text and imagery of an event or presentation. Although analogue tools are still the most common method for sketchnoting, the use of digital tools is increasing. We conducted a study to better understand the current practices, techniques, compromises and opportunities of creating both pen&paper and digital sketchnotes. Our research combines insights from semi-structured interviews with the findings from a within-subjects observational study where ten participants created real time sketchnotes of two video presentations on both paper and digital tablet. We report our key findings, categorised into six themes: insights into sense of space; trade-offs with flexibility; choice paradox and cognitive load; matters of perception, accuracy and texture; issues around confidence; and practicalities. We discuss those findings, the potential and limitations of different methods, and implications for the design of future digital sketchnoting tools.
Storyboarding is an important ideation technique that uses sequential art to depict important scenarios of user experience. Existing data-driven support for storyboarding focuses on constructing user stories, but fail to address its benefit as a graphic narrative device. Instead, we propose to develop a data-driven design support tool that increases the expressiveness of user stories by facilitating sketching storyboards. To explore this, we focus on supporting the sketching of emotional expressions of characters in storyboards. In this paper, we present EmoG, an interactive system that generates sketches of characters with emotional expressions based on input strokes from the user. We evaluated EmoG with 21 participants in a controlled user study. The results showed that our tool has significantly better performance in usefulness, ease of use, and quality of results than the baseline system.
Co-creative systems have been widely explored in the field of computational creativity. However, existing AI partners of these systems are mostly virtual agents. As sketching on paper with embodied robots could be more engaging for designers' early-stage ideation and collaborative practices, we envision the possibility of Cobbie, a mobile robot that ideates iteratively with designers by generating creative and diverse sketches. To evaluate the differences in co-creativity and user experience between the co-creative robots and virtual agents, we conducted a comparative experiment and analyzed the data collected from quantitative scales, observation, and semi-structured interview. The results reveal that Cobbie is more satisfying in motivating exploration, provoking unexpected ideas and engaging designers in the collaborative ideation process. Based on these findings, we discussed the prospects of co-creative robots for future developments of human-AI collaborative systems.
Substantial HCI research investigated the relationship between webpage complexity and aesthetics, but without a definitive conclusion. Some research showed an inverse linear correlation, some other showed an inverted u-shaped curve, while the rest showed no relationship at all. Such a lack of clarity complicates hypothesis formulation and result interpretation for future research, and lowers the reliability and generalizability of potential advice for Web design practice. We re-collected complexity and aesthetics ratings for five datasets previously used in webpage aesthetics and complexity research. The results were mixed, but suggested an inverse linear relationship with a weaker u-shaped sub-component. A subsequent visual inspection of revealed several confounding factors that may have led to the mixed results, including some webpages looking broken or archaic. The second data collection showed that accounting for these factors generally eliminates the u-shaped tendency of the complexity-aesthetics relationship, at least, for a relatively homogeneous sample of English-speaking participants.