Toward a Language of Blended Causality for Transforming Behavioral Data into Reflective User Experiences

Chow, Kenny K. N.

doi:10.1145/3325480.3325490

Cited by 6 publications

(1 citation statement)

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“…The basin can be designed to align the shape of a plant pot. The growth of virtual plants is a result of a compression of several direct cause-effect links (shaking off more water, thus using less paper to dry hands, cutting fewer trees, and finally seeing more trees) into what is called "blended causality" (Chow, 2019). One can immediately "grasp the essential whole" (Fauconnier & Turner, 2002, p. 76) that shaking off water brings more trees.…”

Section: Introductionmentioning

confidence: 99%

Crafting animated parables: an embodied approach to representing lifestyle behaviours for reflection

Chow

2020

Digital Creativity

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Related work in personal informatics, gamification, and feedback suggests that visualizing behavioral data for daily reflection should consider dynamic representations in metaphorical visual narratives with positively or negatively valued outcomes blended in daily life. The causal link between a behavior and its virtual outcomes should be easy to understand. Grounded in embodied cognition, this article proposes a framework guiding the generation of animated parables to meet the above criteria. The guidelines include metaphorical mapping and blending the behavior with a direct cause-effect scenario with similarities in embodied experiences. Application of the guidelines in a series of design workshops generates 47 parables. To evaluate the parables, metrics include naturalness of integrating with life routines, aesthetics of blending into environments, and ease of interpreting the causality. Evaluation results show that more embodied mapping and blending are more likely to result in understandable behavior-outcome links. Designers can follow the guidelines and metrics to generate and compare ideas. Recommendations for crafting better parables are also provided.

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Section: Introductionmentioning

confidence: 99%