Manipulation, Learning, and Recall with Tangible Pen-Like Input

Elkin, Lisa; Beau, Jean-Baptiste; Casiez, Géry; Vogel, Daniel

Document type :

Communication dans un congrès avec actes

DOI :

10.1145/3313831.3376772

Title :

Manipulation, Learning, and Recall with Tangible Pen-Like Input

Author(s) :

Elkin, Lisa [Auteur]
Paul G. Allen School of Computer Science and Engineering [Seattle]
David R. Cheriton School of Computer Science
Beau, Jean-Baptiste [Auteur]
David R. Cheriton School of Computer Science
Casiez, Géry [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut universitaire de France [IUF]
Technology and knowledge for interaction [LOKI]
Université de Lille
Vogel, Daniel [Auteur]
David R. Cheriton School of Computer Science

Conference title :

CHI 2020 - ACM Conference on Human Factors in Computing Systems

City :

Honolulu

Country :

Etats-Unis d'Amérique

Start date of the conference :

2020-04-25

Publisher :

ACM

English keyword(s) :

pen input
tangible interfaces
learning
command selection
Human-Computer Interaction

HAL domain(s) :

Informatique [cs]/Interface homme-machine [cs.HC]

English abstract : [en]

We examine two key human performance characteristics of a pen-like tangible input device that executes a different command depending on which corner, edge, or side contacts a surface. The manipulation time when transitioning ...
Show more >We examine two key human performance characteristics of a pen-like tangible input device that executes a different command depending on which corner, edge, or side contacts a surface. The manipulation time when transitioning between contacts is examined using physical mock-ups of three representative device sizes and a baseline pen mock-up. Results show the largest device is fastest overall and minimal differences with a pen for equivalent transitions. Using a hardware prototype able to sense all 26 different contacts, a second experiment evaluates learning and recall. Results show almost all 26 contacts can be learned in a two-hour session with an average of 94% recall after 24 hours. The results provide empirical evidence for the practicality, design, and utility for this type of tangible pen-like input.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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