• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.361-369
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• 2019

With the commercialization of the ADAS functions, the need for the experience of the autonomous driving system is increasing, and the role of the artificial intelligence agent is attracting attention. This study is an autonomous driving experience experiment that verifies the effect of self-efficacy and agent embodiment. Through a simulator experiment, we measured the effect of existence of self-efficacy and agent embodiment on social presence, perceived risk, and perceived ease of use. Results show that self-efficacy had a positive effect on social presence and perceived risk, and agent embodiment negatively affected perceived ease of use. Based on the results of the study, we proposed guidelines for agent design that can increase the acceptance of the semi-autonomous driving system.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.551-563
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• 2022

This study aims to identify the effect on the user experiences when the embodied agent in a self-driving car interacts with emotional expressions by using 'interjection'. An experimental study was designed with two conditions: the inclusion of injections in the agent's conversation feedbacks (with interjections vs. without interjections) and the type of conversation (task-oriented conversation vs. social-oriented conversation). The online experiment was conducted with the four video clips of conversation scenario treatments and measured intimacy, likability, trust, social presence, perceived anthropomorphism, and future intention to use. The result showed that when the agent used interjection, the main effect on social presence was found in both conversation types. When the agent did not use interjection in the task-oriented conversation, trust and future intention to use were higher than when the agent talked with emotional expressions. In the context of the conversation with the AI agent in a self-driving car, we found only the effect of adding emotional expression by using interjection on the enhancing social presence, but no effect on the other user experience factors.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.358-369
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• 2022

The purpose of this study is to verify the anthropomorphic design factors of pedagogical agents that can enhance user experience in learning foreign languages (English) through smartphones. In this study, when designing a pedagogical agent that delivers content, the presence or absence of the agent's image, the degree of human nature (HN), and role setting (leader vs. companion) among the anthropomorphic factors that influence facilitating learning, credibility, and engagement perception. As a result of the experiment, HN alone did not show a facilitating learning effect, and images and roles improved not only the facilitating learning effect but also other user experience factors. When HN factors were designed in combination with image and role factors, they were effective in overall user experience effects such as facilitating learning, credibility, and engagement.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.92-101
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• 2018

As the interactive AI speaker becomes popular, voice recognition is regarded as an important vehicle-driver interaction method in case of autonomous driving situation. The purpose of this study is to confirm whether multimodal interaction in which feedback is transmitted by auditory and visual mode of AI characters on screen is more effective in user experience optimization than auditory mode only. We performed the interaction tasks for the music selection and adjustment through the AI speaker while driving to the experiment participant and measured the information and system quality, presence, the perceived usefulness and ease of use, and the continuance intention. As a result of analysis, the multimodal effect of visual characters was not shown in most user experience factors, and the effect was not shown in the intention of continuous use. Rather, it was found that auditory single mode was more effective than multimodal in information quality factor. In the semi-autonomous driving stage, which requires driver 's cognitive effort, multimodal interaction is not effective in optimizing user experience as compared to single mode interaction.