Can Older Adults’ Acceptance Toward Robots Be Enhanced by Observational Learning?

Autor: Su-Ling Yeh, Li-Chen Fu, Jen-Chi Liu, Ching-Ju Yu, Sung-En Chien, Yueh-Yi Lai
Rok vydání: 2020
Předmět:
Zdroj: Cross-Cultural Design. User Experience of Products, Services, and Intelligent Environments ISBN: 9783030497873
HCI (12)
Popis: It has been shown that older adults’ negative attitudes toward robots are stronger than those of younger adults, which presumably causes older adults to lack motivation in interacting with robots. We examined the possibility to improve older adults’ attitudes toward robots through observational learning. 40 younger and 40 older adults watched one of two video clips introducing features of an assistive robot. Within each age group, half watched a video clip containing human-robot interaction scenarios (the observational-learning group) and the other half watched a video clip without human-robot interactions (the control group). After watching the video, participants decided if they would like to interact with the actual robot. Participants’ explicit attitudes were measured by questionnaires, and implicit attitudes were measured by the implicit association test (IAT) and the name-shape association task (NSAT). Results showed that (1) for those who chose to interact with the robot, the observational-learning group reported higher perceived safety of the robot; (2) implicit negative attitudes toward the robot as measured by the IAT and the NAST was updated after watching video clips. Our results suggest that direct human-robot interaction cannot be overlooked. Furthermore, contrary to conventional assumptions, implicit attitudes toward robots can be rapidly shaped.
Databáze: OpenAIRE