Avatar Design Research Articles

Does Who You Are or Appear to Be Matter?: Understanding Identity-Based Harassment in Social VR Through the Lens of (Mis)Perceived Identity Revelation

The popularity of social virtual reality (VR) platforms such as VRChat has led to growing concerns about new and more severe forms of online harassment targeting one's identity characteristics (i.e., identity-based harassment ). Social VR users with marginalized identities (e.g., women, LGBTQIA+ individuals, and racial/ethnic minorities) have been reported as particularly vulnerable to such harassment. This is mainly because social VR can make one's offline identity known to others (i.e., what we term identity revelation in this work) through a unique combination of avatar design, voice use, and immersive full- or partial-body tracking. To address these safety concerns, there is an urgent need to unpack the complex dynamics surrounding how one's offline identity is (mis)perceived by others, and how these (mis)perceptions may affect identity-based harassment in social VR. This study thus utilizes a large-scale survey with 223 social VR users across six continents/regions of the world with varying social VR experiences and identities to investigate (1) the relationship between identity-based harassment in social VR and (mis)perceptions of selective identity revelation practices, (2) how embodying one's identity in social VR might actually be less risky than once thought, and (3) how who you are does still matter when it comes to identity-based harassment in social VR. It also highlights the need to better account for understudied aspects of identity-based harassment in social VR and to better educate social VR users on the interplay between harassment and (mis)perceived identity revelation in these spaces.

Enhancing Student Engagement in Learning Management Systems through Exploration of Avatars in Virtual Classrooms: A Systematic Review

The rise of online education has highlighted the crucial need to comprehend student participation in virtual learning environments. With the evolution of online learning platforms, understanding the impact of technological components, especially interactive avatars, on student engagement has become imperative. This study aims to investigate the influence of avatars on student participation in virtual classrooms. Specifically, it seeks to understand the impact of avatars on student interactions, engagement, and involvement within online learning environments. Three primary research questions guide the inquiry: the impact of avatars on student participation, the extent of technology-mediated interaction's effect on engagement, and the nuanced ways in which avatars contribute to or hinder student involvement. The study conducts a comprehensive review of existing literature, delving into the design, integration, and influence of avatars in virtual learning environments. It critically assesses technological advancements, focusing on interactive avatars, and their implications for student engagement. The methodology involves an in-depth analysis of scholarly works, educational platforms, and user experiences to gather valuable insights. The study uncovers the multifaceted impact of avatars in virtual classrooms. Interactive avatars significantly enhance student engagement and participation, fostering interactions between students and teachers as well as among peers. The customization and interactivity of avatars create a more immersive learning experience, positively influencing student involvement. Future research endeavours could explore the integration of avatars with emerging technologies like augmented reality and artificial intelligence, enhancing the depth and scope of virtual classroom interactions. Continued research in this area is essential for refining virtual learning environments and ensuring optimal student participation in the digital educational landscape.

MV‐QUAL: A tool for understanding decisions to purchase virtual products in the metaverse

AbstractThis paper develops the metaverse quality (MV‐Qual) scale and explores the various factors that may impact consumers' perceptions of quality and value when purchasing virtual products in a metaverse world. Utilizing Flow Theory and SERVQUAL as theoretical lenses to conduct our research, a framework was developed and tested, demonstrating how various factors are interconnected and impact consumers' shopping experiences in the metaverse. Data were collected from a national sample of 322 metaverse users in the United States and analyzed using partial least squares structural equation modeling in SmartPLS, complemented by a neural network causal analysis in Neusrel. The results demonstrated that several factors impact metaverse store quality and perceived virtual product value, including control, vividness, avatar design, rarity, and resale value. Subsequently, metaverse store quality and perceived virtual product value positively impact the intention to purchase virtual products in metaverse. This research contributes to the advancement of understanding consumer behavior in the metaverse and adds to the emerging marketing literature on the metaverse. Furthermore, the MV‐QUAL scale developed serves as a practical tool that both marketing researchers and practitioners can use to enhance understanding and discover new ways to improve the metaverse consumer experience.

From script to screen

In an age of ‘deepfakes’, designing learning media and video intentionally and ethically becomes more important than ever. Emerging educational research focuses on generative large language models, which use neural networks to produce human-like text based on prompts. Yet the educational design of synthetic media, particularly AI-generated avatars, which are also currently produced from text prompts, remains less explored. This paper share insights from an ongoing evaluation of realistic, AI-generated avatars as educational presenters at a large Australian metropolitan university. Using commercially available software, we created a suite of AI-generated avatars and accompanying interactives to explore the topic of ethics in business intelligence which was delivered to approximately 1200 students across two semesters in 2022 and 2023. The aim was to provoke critical discussion around ethical decision-making with AI by immersing students in text-to-video technology as part of their learning experience. To better understand students’ perceptions of synthetic media as a stimulus for learning, we conducted four focus groups over two iterations of the course. Our multidisciplinary team also documented the design, development, and implementation challenges of AI-generated avatars. Preliminary findings suggest that clarifying design intentions is key to the effective and ethical application of AI-generated avatars. Automating video content with synthetic media to simplify certain types of educational content could be a catalyst for increased sharing and collaboration. While traditional video formats may prove a simpler choice in the short-term, this study indicates the potential of more hybrid human and nonhuman representation in certain contexts. Students were comfortable with synthetic media use and blending humans and nonhuman elements, expressing a desire for greater interaction with both. We propose a posthuman perspective on AI-generated avatars, one which acknowledges the messy and entangled nature of learning and teaching with technology, that often surfaces issues of ethics and power. To assist educators, ‘VIEW’ is outlined, a brief educational design guide for AI-generated avatars that considers aspects such as the intentions or purpose of the video, the suitability of video as a medium, implementation, and ethical questions. Finally, we suggest more critical and ethical studies on the emergence of synthetic media applications in higher education are needed.

User-centric avatar design: A cognitive walkthrough approach for metaverse in virtual education

Metaverse, once a concept confined to science fiction, has emerged as a transformative reality during the digital era. As this immersive virtual world gains prominence, the role of avatars and the digital representations of users in shaping educational experiences within a metaverse becomes increasingly crucial. This study examined the design of avatars and their effectiveness in virtual education. Using the cognitive walkthrough (CW) method, a well-established user-centric assessment approach, this study examined how users engage in avatar design in virtual educational settings, highlighting their cognitive processes. Through the CW approach, this study identified usability issues and learning challenges, providing valuable insights into the user experience. The investigation focuses on the VRoid platform for avatar design, selected for its user-friendly interface and robust customization features. Participants (n ​= ​12; six men and six women) from diverse educational backgrounds were carefully selected to offer a comprehensive range of perspectives. They performed avatar design tasks that closely mirrored the learning environment of the metaverse, followed by in-depth post-exercise interviews. The findings of this study highlight the essential role of avatar design in enhancing user engagement and improving the learning outcomes of virtual education. Furthermore, we provide practical recommendations for educators and designers to effectively leverage avatar innovation. In a continuously evolving era of metaverse, this research contributes significantly to the ongoing discourse on user-centered design in educational settings, thereby influencing the future trajectory of virtual education.

Academic Augmentation: Analyzing Avatar Design in Educational Metaverse

Academic Augmentation: Analyzing Avatar Design in Educational Metaverse

How do avatar characteristics affect applicants' interactional justice perceptions in artificial intelligence‐based job interviews?

AbstractArtificial intelligence (AI)‐based job interviews are increasingly adopted in organizations' recruitment activities. Despite their standardization and flexibility, concerns about fairness for applicants remain a critical challenge. Taking a perspective on interface design, this research examines the role of avatar characteristics in shaping perceptions of interactional justice in AI‐based job interviews. Through a scenario‐based study involving 465 participants, the impact of avatar characteristics—specifically, appearance, linguistic style, and feedback informativeness—on applicants' perceptions of interpersonal justice and informational justice was investigated. The findings indicate that avatars characterized by a warm and cheerful appearance, coupled with an affective expression style and informative feedback, significantly enhance perceptions of interpersonal justice and informational justice. These insights offer valuable practical guidance for avatar design in AI‐based job interview systems.

What is beautiful is good: attractive avatars for healthier dining and satisfaction

PurposeAs technology increasingly integrates into the restaurant industry, avatar servers present a promising avenue for promoting healthier dining habits. Grounded in the halo effect theory and social comparison theory, this study aims to delve into the influence of avatars' appearance, humor and persuasion on healthier choices and customer satisfaction.Design/methodology/approachThis paper comprises three experimental studies. Study 1 manipulates avatar appearance (supermodel-looking vs normal-looking) to examine its effects on perceived attractiveness, warmth and relatability. These factors influence customer satisfaction and healthy food choices through the psychological mechanisms of social comparison and aspirational appeal. Studies 2 and 3 further refine this theoretical model by assessing the interplay of appearance with humor (presence vs absence) and persuasion (health-oriented vs beauty-oriented), respectively.FindingsResults suggest that avatars resembling supermodels evoke stronger aspirational appeal and positive social comparison due to their attractiveness, thus bolstering healthier choices and customer satisfaction. Moreover, humor moderates the relationship between appearance and attractiveness, while persuasion moderates the effects of appearance on social comparison and aspirational appeal.Research limitations/implicationsThis research bridges the halo effect theory and social comparison theory, offering insights enriching the academic discourse on technology’s role in hospitality.Practical implicationsThe findings provide actionable insights for managers, tech developers and health advocates.Originality/valueDespite its significance, avatar design research in the hospitality sector has been overlooked. This study addresses this gap, offering a guideline for crafting attractive and persuasive avatars.

A stimulus exposure of 50 ms elicits the uncanny valley effect

The uncanny valley (UV) effect captures the observation that artificial entities with near-human appearances tend to create feelings of eeriness. Researchers have proposed many hypotheses to explain the UV effect, but the visual processing mechanisms of the UV have yet to be fully understood. In the present study, we examined if the UV effect is as accessible in brief stimulus exposures compared to long stimulus exposures (Experiment 1). Forty-one participants, aged 21–31, rated each human-robot face presented for either a brief (50 ms) or long duration (3 s) in terms of attractiveness, eeriness, and humanness (UV indices) in a 7-point Likert scale. We found that brief and long exposures to stimuli generated a similar UV effect. This suggests that the UV effect is accessible at early visual processing. We then examined the effect of exposure duration on the categorisation of visual stimuli in Experiment 2. Thirty-three participants, aged 21–31, categorised faces as either human or robot in a two-alternative forced choice task. Their response accuracy and variance were recorded. We found that brief stimulus exposures generated significantly higher response variation and errors than the long exposure condition. This indicated that participants were more uncertain in categorising faces in the brief exposure condition due to insufficient time. Further comparisons between Experiment 1 and 2 revealed that the eeriest faces were not the hardest to categorise. Overall, these findings indicate (1) that both the UV effect and categorical uncertainty can be elicited through brief stimulus exposure, but (2) that categorical uncertainty is unlikely to cause the UV effect. These findings provide insights towards the perception of robotic faces and implications for the design of robots, androids, avatars, and artificial intelligence agents.

Cuteness in avatar design: a cross-cultural study on the influence of baby schema features and other visual characteristics

AbstractThe concept of cuteness, which can evoke positive emotions in people, is an essential aspect to consider in artificial intelligence design. This study aimed to investigate whether the use of baby schema designed avatars in computer-mediated communication elicits higher positive attitudes than neutral avatars and whether the ethnicity of the cute avatars influences individuals' perceived level of cuteness. 485 participants from Israel and Japan viewed six avatar images, including three baby schema avatars of different visual characteristics and ethnicities (Caucasian, Asian, and Black) and three neutral avatars. Participants rated their attitudes on each avatar, and the results revealed that the baby schema designed avatars were rated cuter, more likable, approachable, and pleasant than the neutral mature avatars. Cultural differences were also evident, as the Caucasian baby schema avatar was rated cuter among Japanese participants, while the Asian and Black baby schema avatars were rated cuter among Israeli respondents. The study findings suggest that cute avatar design can serve as a powerful tool for promoting positive interactions in computer-mediated communication, especially in cultures that highly value cuteness, such as Japan. However, the subjective nature of cuteness is evident as attitudes toward cuteness varied significantly across cultures and individuals. This research highlights the significance of cultural diversity and emphasizes the importance of considering cuteness as a crucial aspect of artificial intelligence design, particularly when creating avatars intended to elicit positive emotions from users. Therefore, designers should be mindful of potential cultural and individual differences in the perception of cuteness while developing avatars for various applications.

Design and Evaluation of Abstract Aggregated Avatars in VR Workspaces

Avatars are commonly used in digital platforms to provide a visual representation of individual users to each other. Generally, avatar design in the past has focused on achieving visual fidelity and realism of social interactions. In this paper, we broaden the concept of avatars to incorporate displays using an abstract visual language and conveying information on aggregated, interpersonal information from the perspective of the digital platform as a whole. We propose a general design methodology for such aggregated avatars, and also introduce and experimentally evaluate an aggregated avatar which we have developed on the MaxWhere VR platform. Results are promising in that users were able to discern several key states of the avatar and correctly associate them with the correct virtual reality scenarios in a statistically meaningful way.

Avatar Design in Education: Realistic vs. Cartoonish Representation and Acceptability

This paper examines the variations in attitudes towards avatars across different age groups. The study reveals that middle-aged individuals prioritize the economic advantages of avatars but express dissatisfaction with their lack of authenticity and emotional communication capabilities. In contrast, the younger generation gravitates towards interacting with real people as they offer a more genuine and personalized communication experience. Real individuals can convey information through facial expressions, voice, and body language, meeting the youth's desire for effective and sensory communication. Furthermore, real people can adapt and respond flexibly to user feedback and contextual cues, aligning with the youth's expectations for customization and individuality. Opinions within the teenage group differ, with some acknowledging the potential of avatars to provide a wealth of knowledge and customization. They appreciate the ability to tailor the avatar's characteristics and services to their specific needs. Conversely, another portion of the teenage group perceives avatars as lacking authenticity and the ability to share personal experiences. They value the human element in communication and find avatars unable to replicate the depth of emotional connection that real individuals offer. Overall, the attitudes towards avatars among different age groups are influenced by various factors such as economic considerations, human nature, sensory experiences, and effectiveness. These differences reflect the diverse needs and values of each age group. Understanding these nuanced perspectives can inform the design and implementation of avatar technologies to better cater to the expectations and preferences of different age demographics.

Avatar design in Metaverse: the effect of avatar-user similarity in procedural and creative tasks

PurposeThrough the lens of self-perception theory, this paper investigates how avatar design (i.e. avatar user similarity) affects users' self-awareness and shapes their task engagement and performance in the Metaverse.Design/methodology/approachThe authors conducted a 2 (avatar user similarity: high vs low) × 2 (task type: procedural vs creative) lab experiment and collected data from questionnaires, the recording of users' behavior during tasks and their actual task performance.FindingsThe results show that higher avatar user similarity leads to higher task engagement in general. Furthermore, while a similar avatar promotes users to regulate their behaviors and achieve better performance in a procedural task, high similarity also inhibits users' creativity by invoking habitual thinking, resulting in worse performance in generating original ideas in a creative task.Originality/valueThis study is expected to contribute to the information systems literature by revealing the value of avatar design and providing new perspectives on improving users' experiences in the Metaverse.

Evaluating Avatar Designs for On-Person Screening in Aviation Security

In aviation security, on-person screening quality is dependent on security screeners accurately translating the location of a digital 2D alarm to a 3D passenger using mental spatial scaling. Currently, security screeners are shown an alarm on a generic human figure (avatar) designed to protect passenger privacy. The problem is that the avatar may be overly generic and it can be challenging for security screeners to quickly and confidently locate the threat. To compensate, security screeners may increase their search area to guarantee that the threat is found. In prior work, an avatar design with relevant landmarks improved location accuracy. For this study, we compared the redesigned avatar to three other avatar designs that are used by on-person screening vendors. The results of the study showed that screeners had significantly smaller search areas (30% smaller) and were closer to the true target location (15% closer) when using the redesigned avatar.

SocialInteractionGAN: Multi-Person Interaction Sequence Generation

Prediction of human actions in social interactions has important applications in the design of social robots or artificial avatars. In this paper, we focus on a unimodal representation of interactions and propose to tackle interaction generation in a data-driven fashion. In particular, we model human interaction generation as a discrete multi-sequence generation problem and present SocialInteractionGAN, a novel adversarial architecture for conditional interaction generation. Our model builds on a recurrent encoder-decoder generator network and a dual-stream discriminator, that jointly evaluates the realism of interactions and individual action sequences and operates at different time scales. Crucially, contextual information on interacting participants is shared among agents and reinjected in both the generation and the discriminator evaluation processes. Experiments show that albeit dealing with low dimensional data, SocialInteractionGAN succeeds in producing high realism action sequences of interacting people, comparing favorably to a diversity of recurrent and convolutional discriminator baselines, and we argue that this work will constitute a first stone towards higher dimensional and multimodal interaction generation. Evaluations are conducted using classical GAN metrics, that we specifically adapt for discrete sequential data. Our model is shown to properly learn the dynamics of interaction sequences, while exploiting the full range of available actions.

Understanding the Importance of Cultural Appropriateness for User Interface Design: An Avatar Study

While previous research established that culture plays an important role in technology adoption, there is only limited work on the role of cultural appropriateness in user interface design for users from a specific background. In this study, we focus on the case of avatar design as a user interface element for facilitating positive user experience. Building on the theoretical lenses of social response theory and the “Computers Are Social Actors” paradigm, we develop a research model to investigate how cultural appropriateness of avatar design is a vital driver for users’ trust. We evaluate our research model by means of an online experiment ( n = 313) in the context of online health advice for users from Saudi Arabia. The avatars differed in appearance (Arab, non-Arab), gender (male, female), and clothing (athletic, medical, everyday). Our results show that Arab avatars exhibited significantly higher cultural appropriateness than non-Arab avatars. Furthermore, participants were more inclined to select an Arab avatar (88.2%) that matched their gender (77.3%). Confirming the critical role of cultural appropriateness, our study demonstrates the importance of carefully considering the target audience in designing user interfaces.

Avatar design types and user engagement in digital educational games during evaluation phase

<span lang="EN-US">Avatar design types can range from human representations to abstract representations. In digital educational games (DEGs), avatars are frequently used to encourage users to play the game. However, the role of avatar design types and their engagement in digital games are still unclear and empirically under research. Therefore, a bespoke digital educational game in geography was developed and validated by six expert users. Then forty-five users participated in the evaluation phase to investigate engagement and avatar types on digital educational games using the user engagement scale (UES). The results reported aesthetics and satisfaction factors somehow influenced the avatar design types, but none of the UES subscales was influenced by preferred avatar design types. Moreover, the human-cartoon avatar, which was not entirely human and cartoonish, was the most popular avatar design type among young adults. Other issues discussed for future developers and research included incorporating more avatar design selections into the study, integrating social interaction features into the game, using the same drawing style for avatars and provide easy access to the bespoke game during data collection.</span>

Jogging in Your Avatar’s Footsteps: The Effects of Avatar Customization and Control Intuitiveness

This study examined the effects of customization and intuitiveness of control on the feeling of identification and embodiment, and the actual running performance of game players after playing a digital runner game developed for this research. A 2 (avatar design: customized vs. not customized) × 2 (avatar controls: intuitive vs. not intuitive) within-subjects experiment (N = 44) found that playing the game with a customized avatar increased identification with and embodiment in the avatar. However, using unintuitive controls with a customized avatar diminished the feeling of identification. Customizing an avatar increased identification with and embodiment in the avatar. However, using unintuitive controls with a customized avatar diminished the feeling of identification. Further, participants’ running performance was significantly hindered in the customized avatar and unintuitive controls condition, compared to the other conditions. The expectation that identification and embodiment would mediate the effect of avatar customization and control intuitiveness on physical activity was not supported. Together, these results suggest that avatar customization and control intuitiveness should be prioritized when designers intend to use video games to promote post-game physical activity.

Leveraging Structural Health Monitoring Data Through Avatars to Extend the Service Life of Mass Timber Buildings

Mass timber construction systems, incorporating engineered wood products as structural elements, are gaining acceptance as a sustainable alternative to multi-story concrete or steel-frame structures. The relative novelty of these systems brings uncertainties on whether these buildings perform long-term as expected. Consequently, several structural health monitoring (SHM) projects have recently emerged to document their behavior. A wide and systematic use of this data by the mass timber industry is currently hindered by limitations of SHM programs. These limitations include scalability, difficulty of data integration, diverse strategies for data collection, scarcity of relevant data, complexity of data analysis, and limited usability of predictive tools. This perspective paper envisions the use of avatars as a Web-based layer on top of sensing devices to support SHM data and protocol interoperability, analysis, and reasoning capability and to improve life cycle management of mass timber buildings. The proposed approach supports robustness, high level and large-scale interoperability and data processing by leveraging the Web protocol stack, overcoming many limitations of conventional centralized SHM systems. The design of avatars is applied in an exemplary scenario of hygrothermal data reconstruction, and use of this data to compare different mold growth prediction models. The proposed approach demonstrates the ability of avatars to efficiently filter and enrich data from heterogeneous sensors, thus overcoming problems due to data gaps or insufficient spatial distribution of sensors. In addition, the designed avatars can provide prediction or reasoning capability about the building, thus acting as a digital twin solution to support building lifecycle management.

Negotiating Learning Goals with Your Future Learning-Self

This paper discusses the challenges towards designing an educational avatar which visualizes the future learning-self of a student in order to promote their self-regulated learning skills. More specifically, the avatar follows a negotiation-based interaction with the student during the goal-setting process of self-regulated learning. The goal of the avatar is to help the student get insights of their possible future learning-self based on their daily goals. Our approach utilizes a Recurrent Neural Network as the underlying prediction model for expected learning outcomes and goal feasibility. In this paper, we present our ongoing work and design process towards an explainable and personalized educational avatar, focusing both on the avatar design and the human-algorithm interactions.