Human-Centred Principles for the Design of Shape-Changing Tangible User Interfaces
Bibliographic record
Abstract
Shape changing interfaces (SCI) are interactive Tangible User Interfaces (TUI) that change materiality or shape as input and/or output (Alexander et al., 2018). While these represent novel technologies, there remain problems in understanding how to design, use or evaluate these. One reason behind such problems might be the lack of guidelines or frameworks that are developed specifically for SCI. Another reason can be the lack of theory of human performance to inform design decisions. In this paper, we review frameworks that have been proposed for SCI and relate these to a theory of affordance. While HCI has used the concept of affordance for many years (Norman, 1988), there is a tendency to assume that it relates solely to the physical properties of an object. To this end, it has been assumed that form (physical appearance of the object) permits function (a particular action with that object). However, the concept of affordance is much richer than this implies and takes into account the capabilities of the person performing the action, the goal that the person is seeking to achieve, the environment in which the interaction between person and object occurs, as well as the properties of the object. Further, as the object could be designed to have sensing and acting capabilities of its own, then there is a progression of interactions in which the object responds to person as much as the person responds to the object. To explore the concept of affordance, Baber (2018) developed Forms of Engagement (including environmental, morphological, motor, perceptual, cognitive, cultural). This reflects the ways in which people engage with artefacts and how different Forms of Engagement can serve to support and constrain each other. SCI design frameworks have focused on the type of shape change (Rasmussen et al., 2012; Roudaut et al., 2013; Kim et al., 2018) or purpose of different shapes (Alexander et al., 2018; Rasmussen et al., 2012). In this paper, the aim is to relate the type of shape change with the purpose of SCI. Such a framework will combine Forms of Engagement with properties and behaviours of SCI. This can simplify the application of affordance in SCI design, as it details different levels of affordance for each affording situation. Relating the shape change type with the function in a framework together with the affordance evaluation methodology would serve as a useful tool that will improve the usability of upcoming SCI. Moreover, this research will serve as a base for future studies that facilitate applying affordance concept to tangible user interfaces. The evaluation methodology can help SCI designers to assess their interfaces’ affordance or even provide the designer the ability to consider the criteria in the early stage of design to assist them create affording situations. ReferencesAlexander, J., Roudaut, A., Steimle, J., Hornbæk, K., Alonso, M. B., Follmer, S., & Merritt, T. (2018). Grand Challenges in Shape-Changing Interface Research Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada. https://doi.org/10.1145/3173574.3173873Baber, C. (2018). Designing Smart Objects to Support Affording Situations: Exploiting Affordance Through an Understanding of Forms of Engagement. Frontiers in Psychology, 9, 292. https://doi.org/10.3389/fpsyg.2018.00292 Kim, H., Coutrix, C., & Roudaut, A. (2018). Morphees+: Studying Everyday Reconfigurable Objects for the Design and Taxonomy of Reconfigurable UIs Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Montreal QC, Canada. https://doi.org/10.1145/3173574.3174193Norman, D. A. (1988). The psychology of everyday things. Basic Books. Rasmussen, M. K., Pedersen, E. W., Petersen, M. G., & Hornbæk, K. (2012). Shape-changing interfaces: a review of the design space and open research questions Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Austin, Texas, USA. https://doi.org/10.1145/2207676.2207781Roudaut, A., Karnik, A., Löchtefeld, M., & Subramanian, S. (2013). Morphees: toward high "shape resolution" in self-actuated flexible mobile devices Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France. https://doi.org/10.1145/2470654.2470738
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".