Publications

Capturing Experts’ Mental Models to Organize a Collection of Haptic Devices: Affordances Outweigh Attributes.
To appear in Proc. Conf. Human Factors in Computing Systems (CHI), 2020

Hasti SeifiMichael Oppermann, Julia BullardKaron MacLean, and Katherine J. Kuchenbecker

Humans rely on categories to mentally organize and understand sets of complex objects. One such set, haptic devices, has myriad technical attributes that affect user experience in complex ways. Seeking an effective navigation structure for a large online collection, we elicited expert mental categories for grounded force-feedback haptic devices: 18 experts (9 device creators, 9 interaction designers) reviewed, grouped, and described 75 devices according to their similarity in a custom card-sorting study. From the resulting quantitative and qualitative data, we identify prominent patterns of tagging versus binning, and we report 6 uber-attributes that the experts used to group the devices, favoring affordances over device specifications. Finally, we derive 7 device categories and 9 subcategories that reflect the imperfect yet semantic nature of the expert mental models. We visualize these device categories and similarities in the online haptic collection, and we offer insights for studying expert understanding of other human-centered technology.

Pre-print PDF


Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design.
Proc. Conf. Human Factors in Computing Systems (CHI), 2019

Hasti Seifi, Farimah Fazlollahi, Michael Oppermann, John Andrew Sastrillo, Jessica Ip, Ashutosh Agrawal, Gunhyuk Park, Katherine J. Kuchenbecker, and Karon MacLean

Creating haptic experiences often entails inventing, modifying, or selecting specialized hardware. However, interaction designers are rarely engineers, and 30 years of haptic inventions are buried in a fragmented literature that describes devices mechanically rather than by potential purpose. We conceived of Haptipedia to unlock this trove of examples: Haptipedia presents a device corpus for exploration through metadata that matter to both device and interaction designers. It is a taxonomy of device attributes that go beyond physical description to capture potential utility, applied to a growing database of 105 grounded force-feedback devices, and accessed through a public visualization that links utility to morphology. Haptipedia’s design was driven by both systematic review of the haptic device literature and rich input from diverse haptic designers. We describe Haptipedia’s reception (including hopes it will redefine device reporting standards) and our plans for its sustainability through community participation.

Pre-print PDF