Feel–Play–Imagine: Structured introduction and imagination of haptics with storytellers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Haptic technology offers new opportunities for interaction, yet remains inaccessible to people unfamiliar with the technology due to challenges in rapid prototyping and the absence of a widely understood vocabulary, making early-stage design communication difficult. To address these challenges, we developed Feel-Play-Imagine (FPI), a method for haptics experts to involve team members and stakeholders in the early stages of design, and explored its use in the context of storytelling. FPI involves introducing people to haptics through experiencing polished haptic experiences in context (Feel) and experimenting with alternative modalities (Play), then engaging in discussions using stories to imagine designed experiences (Imagine). We report on the results of using FPI in an ongoing co-design project and a lab study with 10 expert storytellers from various backgrounds. Our findings include the value of hands-on and playful experiences to learn about haptic technologies, the ability of FPI to support design decisions, the ability of our developed Worksheet to structure discussion in some contexts, and the need to support multimodal and gestural communication when discussing haptic and tangible interaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it