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Record W4399917572 · doi:10.1145/3635636.3656191

ThermalPen: Investigating the Influence of Thermal Haptic Feedback for Creativity in 3D Sketching

2024· article· en· W4399917572 on OpenAlexaff
Philipp Pascal Hoffmann, Rina R. Wehbe, Max Mühlhäuser, Mayra Donaji Barrera Machuca

Bibliographic record

VenueCreativity and Cognition · 2024
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHaptic technologyCreativityComputer scienceHuman–computer interactionSimulationPsychology

Abstract

fetched live from OpenAlex

This paper presents ThermalPen, a novel device for 3D sketching that utilizes thermal feedback to allow users to feel the materiality of their sketches. The pen lets users draw using six colors and three textures mapped to different temperatures. Our goal is to investigate the influence of thermal feedback on user creativity for 3D sketching. In a user study with 24 participants, we asked them to draw with and without thermal feedback. Our results show that thermal feedback improved user creativity for specific tasks. Qualitative results also indicate an effect on the user experience. Our work contributes to understanding how thermal feedback can increase user satisfaction with 3D sketching and provide insights and directions for future work.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.354
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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