Design and evaluation of postural interactions between users and a listening virtual agent during a simulated job interview

Jáuregui, David Antonio Gómez; Giraud, Tatiana; Isableu, Brice; Martin, Jean‐Claude

doi:10.1002/cav.2029

Cited by 8 publications

(9 citation statements)

References 68 publications

(136 reference statements)

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“…In a study by Nunamaker et al ( 2011 ), the male agent was perceived as more powerful, whereas the female agent was perceived as more likable. Even when male and female agents wore the same clothes, exhibited the same verbal and non-verbal behaviors, and had their faces blurred (thus lacking salient indicators of gender), the female agent was rated higher for warmth than the male agent; however, they were rated similarly for dominance, a trait typically associated with men (Antonio Gómez-Jáuregui et al, 2021 ). In contrast, Kulms et al ( 2011 ), found in their main experiment that participants did not ascribe more masculine traits to the male agents nor more feminine traits to the female agents, unlike in their pretest with 14 participants using still pictures of the same virtual agents.…”

Section: Systematic Review Of Virtual Agents' Gender and Its Impact O...mentioning

confidence: 99%

The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review

Armando

Ochs

Régner

2022

Front. Artif. Intell.

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Virtual learning environments often use virtual characters to facilitate and improve the learning process. These characters, known as pedagogical agents, can take on different roles, such as tutors or companions. Research has highlighted the importance of various characteristics of virtual agents, including their voice or non-verbal behaviors. Little attention has been paid to the gender-specific design of pedagogical agents, although gender has an important influence on the educational process. In this article, we perform an extensive review of the literature regarding the impact of the gender of pedagogical agents on academic outcomes. Based on a detailed review of 59 articles, we analyze the influence of pedagogical agents' gender on students' academic self-evaluations and achievements to answer the following questions: (1) Do students perceive virtual agents differently depending on their own gender and the gender of the agent? (2) Does the gender of pedagogical agents influence students' academic performance and self-evaluations? (3) Are there tasks or academic situations to which a male virtual agent is better suited than a female virtual agent, and vice versa, according to empirical evidence? (4) How do a virtual agent's pedagogical roles impact these results? (5) How do a virtual agent's appearance and interactive capacities impact these results? (6) Are androgynous virtual agents a potential solution to combatting gender stereotypes? This review provides important insight to researchers on how to approach gender when designing pedagogical agents in virtual learning environments.

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Section: Systematic Review Of Virtual Agents' Gender and Its Impact O...mentioning

confidence: 99%

The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review

Armando

Ochs

Régner

2022

Front. Artif. Intell.

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“…Another reason could be that the avatar visualisation was too far from human-likeness, and therefore the participants had a harder time believing that it was a human that was moving. Listening behaviour is not only dependent on full-body motion, but it is also often combined with verbal feedback [38].…”

Section: Discussionmentioning

confidence: 99%

“…Poppe et al [37] developed rule-based strategies for generating listening behaviour based on the speaker's speech and gaze, including vocal back channelling. A similar approach in terms of selecting new listening behaviours and sequences can be found in [38]. They used a multi-modal corpus of interviews to generate listening behaviour in a virtual agent conducting interviews.…”

Section: Listening Behaviourmentioning

confidence: 99%

Exploring the Effectiveness of Evaluation Practices for Computer-Generated Nonverbal Behaviour

Wolfert,

Henter,

Belpaeme

2024

Applied Sciences

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This paper compares three methods for evaluating computer-generated motion behaviour for animated characters: two commonly used direct rating methods and a newly designed questionnaire. The questionnaire is specifically designed to measure the human-likeness, appropriateness, and intelligibility of the generated motion. Furthermore, this study investigates the suitability of these evaluation tools for assessing subtle forms of human behaviour, such as the subdued motion cues shown when listening to someone. This paper reports six user studies, namely studies that directly rate the appropriateness and human-likeness of a computer character’s motion, along with studies that instead rely on a questionnaire to measure the quality of the motion. As test data, we used the motion generated by two generative models and recorded human gestures, which served as a gold standard. Our findings indicate that when evaluating gesturing motion, the direct rating of human-likeness and appropriateness is to be preferred over a questionnaire. However, when assessing the subtle motion of a computer character, even the direct rating method yields less conclusive results. Despite demonstrating high internal consistency, our questionnaire proves to be less sensitive than directly rating the quality of the motion. The results provide insights into the evaluation of human motion behaviour and highlight the complexities involved in capturing subtle nuances in nonverbal communication. These findings have implications for the development and improvement of motion generation models and can guide researchers in selecting appropriate evaluation methodologies for specific aspects of human behaviour.

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“…Similarly, according to, [39], [46], [61] there is a segment of users who use these bots in Processes for personal assistance for various reasons. It was also found in [20], [28], [32], [33], [36], [38], [58], [59], [63], that chatbots are used in customer service processes. In this analysis, the application of chatbots in incident management processes has not been identified; however, it has been mentioned that the teaching process (student-delivered course), customer service process (customer-supplier), health process (patient-doctor), processes for personal assistance (assisted-assistant) and even the training of bots (trained-trainer), are carried out by conversational bots; in the case of the Incident Management Process (user-technician), its application is highly necessary and important to increase productivity in this process.…”

Section: Recent Work On the Types Of Conversational Chatbots That Existmentioning

confidence: 99%

“…In this analysis, the application of chatbots in incident management processes has not been identified; however, it has been mentioned that the teaching process (student-delivered course), customer service process (customer-supplier), health process (patient-doctor), processes for personal assistance (assisted-assistant) and even the training of bots (trained-trainer), are carried out by conversational bots; in the case of the Incident Management Process (user-technician), its application is highly necessary and important to increase productivity in this process. [37], [46]- [48], [53], [54], [59], [65] 3 Customer service processes 9 [23], [31], [35], [36], [39], [41], [61], [62], [66] 4 Health processes 11 [24], [25], [28], [29], [32]- [34], [43], [44], [56], [57] 5 Processes for personal assistance 3 [42], [49], […”

Section: Recent Work On the Types Of Conversational Chatbots That Existmentioning

confidence: 99%

Productivity of incident management with conversational bots-a review

Iparraguirre-Villanueva,

Obregon-Palomino,

Pujay-Iglesias

et al. 2023

IJ-AI

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<p>The use of conversational agents (bots) in information systems managed by company’s increases productivity in the development of activities focused on processes such as customer service, healthcare, and presentation. The present work is a systematic literature review that collects articles from 2019 to 2022 in the databases Scopus, Springer, Willey, Indexes-Csic, Taylor & Francis, Pubmed, and Ebsco Host. PRISMA methodology was used to systematize 47 relevant articles. As a result of the analysis, 2/19 very important benefits were obtained, which are: helping to obtain information and facilitating customer service; as for the types of conversational bots, a total of 9 types were found, of which conversational agents and chatbots with artificial intelligence (AI) are the most common; in the case of processes, 3/5 processes that optimize conversational bots were found, where the most prominent are: teaching process, health processes, and customer service processes. An architecture model for conversational bots in incident management is also proposed.</p>

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Design and evaluation of postural interactions between users and a listening virtual agent during a simulated job interview

Cited by 8 publications

References 68 publications

The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review

The Impact of Pedagogical Agents' Gender on Academic Learning: A Systematic Review

Exploring the Effectiveness of Evaluation Practices for Computer-Generated Nonverbal Behaviour

Productivity of incident management with conversational bots-a review

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