"Pathways to the Metaverse": Exploring the User Experience Mechanisms Driving Technology Acceptance in Virtual Lab Visits with an LLM-powered AvatarMetaverse environments combined with large language models (LLMs) enable guided interaction through LLM-powered avatars that function as embodied conversational agents. In our study, we examined how scholars interact with an LLM-powered avatar modeled after a real professor during a virtual reality (VR) tour of a research lab. As little is known about how metaverse characteristics shape the user experience (UX) mechanisms that drive acceptance of such technologies, we conducted a 2 (avatar realism: abstract vs. hyperrealistic) × 2 (immersion: desktop vs. headset-based VR) within-subjects study (N = 30), where academic participants engaged in a virtual lab tour guided by the professor avatar. We conducted path analyses on three conceptual models and, based on the results, proposed the Virtual Lab Acceptance Model (VLAM), which features an experiential path (where perceived immersion increases empathy towards the avatar and task enjoyment) and a rational path (where perceived realism increases avatar credibility and task confidence). Flow states amplify these pathways by strengthening task experiences. Task enjoyment is the strongest predictor of behavioral intention. These findings inform HCI research on metaverse characteristics to drive technology acceptance through UX mechanisms, yielding design implications for developing LLM-powered avatars for virtual labs.2026XTXinyi Tu et al.Aalto UniversitySocial & Collaborative VRIdentity & Avatars in XRHuman-LLM CollaborationIUI
Creating and Evaluating Personas Using Generative AI: A Scoping Review of 81 ArticlesAs generative AI (GenAI) is increasingly applied in persona development to represent real users, understanding the implications and limitations of this technology is essential for establishing robust practices. This scoping review analyzes how 81 articles (2022-2025) use GenAI techniques for the creation, evaluation, and application of personas. The articles exhibited good level of reproducibility, with 61% of articles sharing resources (personas, code, or datasets). Furthermore, conversational persona interfaces are increasingly provided alongside traditional profiles. However, nearly half (45%) of the articles lack evaluation, and the majority (86%) use only GPT models. In some articles, GenAI use creates a risk of circularity, in which the same GenAI model both generates and evaluates outputs. Our findings also suggest that GenAI seems to reduce the role of human developers in the persona-creation process. To mitigate the associated risks, we propose actionable guidelines for the responsible integration of GenAI into persona development.2026DADanial Amin et al.University of VaasaGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationExplainable AI (XAI)CHI
Are We Still Under-Serving the Underserved?: An Analysis of 56 Blue-Collar Workers Using 2 Online Information ServicesWe examined the accessibility of online information services (OISs) for underserved communities through a user study involving 56 blue collar participants interacting with a website and an app for five tasks. The blue collar participants were generally unsuccessful on both platforms, with 12.7% (n=7) unable to successfully complete any tasks; a hundred percent required at least minor assistance. Participants were also inefficient, taking 28.62 more steps than optimal (143.1%) on the website and 10.41 more steps (47.3%) on the app. Time inefficiency was also noteworthy, with 535.76 more seconds than optimal (248.0%) on the website and 266.55 more seconds (142.4%) on the app. Though still poor, the app yielded better outcomes with higher success rates and usability ratings. Digital proficiency correlated with success on both platforms, which is good news as this is addressable by OIS providers. Qualitative analysis revealed that many in this underserved population were unaware that these valuable OISs were available to them. Findings underscore the need for OIS providers to prioritize targeted outreach to inform underserved communities that OISs are open and welcoming. Designing OISs with accessibility and simplicity targeted for mobile devices is crucial for bridging the digital literacy gap and empowering underserved communities to engage effectively with OISs.2025JAJinan Y. Azem et al.Universal & Inclusive DesignPrivacy Perception & Decision-MakingParticipatory DesignDIS
When Personas Talk to You: Evaluating the Evolution of User Personas from Static Profiles to Conversational User InterfacesThe development of persona systems provides a possibility for end users to interact with different persona modalities. In a 54-participant randomized controlled experiment, we compare two persona interaction modalities, document and dialogue personas, both generated using AI approaches from survey data. Overall, dialogue personas appear to be perceived more favorably than document personas. However, document personas exhibit a wider range of perceptions, suggesting that experiences with document personas are more polarizing among users. The document personas had higher transparency and were perceived as more complete, but the task completion was perceived as more difficult, although the task success rate was higher. The dialogue personas were perceived as more usable, with a higher System Usability Scale score, and more enjoyable. Our findings provide critical insights into the increasingly important area of persona interaction modalities and the broad paradigm of human-persona interaction.2025IKIlkka Kaate et al.Conversational ChatbotsAgent Personality & AnthropomorphismDIS
"You Always Get an Answer": Analyzing Users' Interaction with AI-Generated Personas Given Unanswerable Questions and Risk of HallucinationWe investigated the presence and acceptance of hallucinations (i.e., accidental misinformation) of an AI-generated persona system that leverages large language models for persona creation from survey data in a 54-user within-subjects experiment. After interacting with the personas, users were given a task to ask the personas a series of questions, including an unanswerable question, meaning the personas lacked the data to answer the question. The AI-generated persona system provided a plausible but incorrect answer half (52%) of the time, and more than half of the time (57%), the users accepted the incorrect answer, and the rest of the time, users answered the unanswerable question correctly (no answer). We found that when the AI-generated persona hallucinated, the user was significantly more likely to answer the unanswerable question incorrectly. Also, for genders separately, when the AI-generated persona hallucinated, it was significantly more likely for the female user and the male users to answer the unanswerable question incorrectly. We identified four themes in the AI-generated persona’s answers and found that users perceive AI-generated persona’s answers as long and unclear for the unanswerable question. Findings imply that personas leveraging LLMs require guardrails to ensure that personas clearly state the possibility of data restrictions and hallucinations when asked unanswerable questions.2025IKIlkka Kaate et al.Human-LLM CollaborationAI Ethics, Fairness & AccountabilityAlgorithmic Transparency & AuditabilityIUI
What is User Engagement?: A Systematic Review of 241 Research Articles in Human-Computer Interaction and BeyondUser engagement (UE) is widely discussed in HCI articles, but its definition, reliability, and application remain elusive. This research conducts a systematic literature review of 241 articles from 1993 to 2023 to analyze how UE is defined and measured within the domain of HCI. Our findings reveal significant definitional inconsistencies that hinder UE’s practical application in HCI research and system design. Based on our findings, we recommend using UE as a categorical label rather than a unified construct until more systematic frameworks are established. We also highlight the need for divergent views of UE across HCI research communities as a valuable avenue to pursue. This divergent view approach can help HCI researchers focus on specific, measurable aspects of UE that align with specific community practices and norms. Our findings also suggest that until such a framework emerges, researchers should be aware of its limitations when using UE as a research construct.2025BJBernard J. Jansen et al.Hamad Bin Khalifa University, Qatar Computing Research Institute; Penn State, College of Information Science and TechnologyUser Research Methods (Interviews, Surveys, Observation)CHI
“There’s Something About Noura”: Exploring Think-Aloud Reasonings for Users' Persona Choice in a Design TaskStakeholders like designers use personas to learn about users. After persona development, stakeholders are usually presented with a persona set. However, there is little research on how stakeholders select a persona from a persona set. A think-aloud analysis with 37 stakeholders who were asked to select a persona for a content design task reveals that persona selection is influenced by comparative, non-comparative, and subjective elements. Persona choice is often made with task compatibility in mind: interests, professions, and education were important contextual factors in our focal task. Storifying is commonly applied by stakeholders, reflecting personas’ narrative nature. The persona’s picture is often evoked, in addition to nationality and name, though demographics do not play a decisive role. Stakeholders refer to a host of persona attributes when explicating their persona choice. Overall, reasonings for persona choice are multifaceted and individualistic, as we might expect given the information-richness of personas.2024SŞSercan Şengün et al.Participatory DesignUser Research Methods (Interviews, Surveys, Observation)DIS
Deus Ex Machina and Personas from Large Language Models: Investigating the Composition of AI-Generated Persona DescriptionsLarge language models (LLMs) can generate personas based on prompts that describe the target user group. To understand what kind of personas LLMs generate, we investigate the diversity and bias in 450 LLM-generated personas with the help of internal evaluators (n=4) and subject-matter experts (SMEs) (n=5). The research findings reveal biases in LLM-generated personas, particularly in age, occupation, and pain points, as well as a strong bias towards personas from the United States. Human evaluations demonstrate that LLM persona descriptions were informative, believable, positive, relatable, and not stereotyped. The SMEs rated the personas slightly more stereotypical, less positive, and less relatable than the internal evaluators. The findings suggest that LLMs can generate consistent personas perceived as believable, relatable, and informative while containing relatively low amounts of stereotyping.2024JSJoni Salminen et al.University of VaasaHuman-LLM CollaborationAI Ethics, Fairness & AccountabilityCHI
Developing Persona Analytics Towards Persona ScienceMuch of the reported work on personas suffers from the lack of empirical evidence. To address this issue, we introduce Persona Analytics (PA), a system that tracks how users interact with data-driven personas. PA captures users’ mouse and gaze behavior to measure users’ interaction with data-driven personas and system features of an interactive persona system. Measuring these activities grants an understanding of the behaviors of a persona user, required for quantitative measurement of persona use to obtain scientifically valid evidence. Conducting a study with 144 participants, we demonstrate how PA can be deployed for remote user studies during exceptional times when physical user studies are difficult if not impossible.2022JSJoni Salminen et al.User Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingIUI
Use Cases for Design Personas: A Systematic Review and New FrontiersPersonas represent the needs of users in diverse populations and impact design by endearing empathy and improving communication. While personas have been lauded for their benefits, we could locate no prior review of persona use cases in design, prompting the question: how are personas actually used to achieve these benefits? To address this question, we review 95 articles containing persona application across multiple domains, and identify software development, healthcare, and higher education as the top domains that employ personas. We then present a three-stage design hierarchy of persona usage to describe how personas are used in design tasks. Finally, we assess the increasing trend of persona initiatives aimed towards social good rather than solely commercial interests. Our findings establish a roadmap of best practices for how practitioners can innovatively employ personas to increase the value of designs and highlight avenues of using personas for socially impactful purposes.2022JSJoni O. Salminen et al.Hamad Bin Khalifa University, University of VaasaInclusive DesignEmpowerment of Marginalized GroupsParticipatory DesignCHI
Picturing It!: The Effect of Image Styles on User Perceptions of PersonasThough photographs of real people are typically used to portray personas, there is little research into the potential advantages or disadvantages of using such images, relative to other image styles. We conducted an experiment with 149 participants, testing the effects of six different image styles on user perceptions and personality traits that are attributed to personas by the participants. Results show that perceptions of clarity, completeness, consistency, credibility, and empathy for a persona increase with picture realism. Personas with more realistic pictures are also perceived as more agreeable, open, and emotionally stable, with higher confidence in these assessments. We also find evidence of the uncanny valley effect, with realistic cartoon personas experiencing a decrease in the user perception scores.2021JSJoni Salminen et al.Hamad Bin Khalifa University, University of TurkuEye Tracking & Gaze InteractionAgent Personality & AnthropomorphismCHI
A Literature Review of Quantitative Persona CreationQuantitative persona creation (QPC) has tremendous potential, as HCI researchers and practitioners can leverage user data from online analytics and digital media platforms to better understand their users and customers. However, there is a lack of a systematic overview of the QPC methods and progress made, with no standard methodology or known best practices. To address this gap, we review 49 QPC research articles from 2005 to 2019. Results indicate three stages of QPC research: Emergence, Diversification, and Sophistication. Sharing resources, such as datasets, code, and algorithms, is crucial to achieving the next stage (Maturity). For practitioners, we provide guiding questions for assessing QPC readiness in organizations.2020JSJoni O. Salminen et al.Qatar Computing Research Institute, Hamad Bin Khalifa University & University of TurkuAgent Personality & AnthropomorphismParticipatory DesignCHI
Personas and Analytics: A Comparative User Study of Efficiency and Effectiveness for a User Identification TaskPersonas are a well-known technique in human computer interaction. However, there is a lack of rigorous empirical research evaluating personas relative to other methods. In this 34-participant experiment, we compare a persona system and an analytics system, both using identical user data, for efficiency and effectiveness for a user identification task. Results show that personas afford faster task completion than the analytics system, as well as outperforming analytics with significantly higher user identification accuracy. Qualitative analysis of think-aloud transcripts shows that personas have other benefits regarding learnability and consistency. However, the analytics system affords insights and capabilities that personas cannot due to inherent design differences. Findings support the use of personas to learn about users, empirically confirming some of the stated benefits in the literature, while also highlighting the limitations of personas that may necessitate the use of accompanying methods.2020JSJoni Salminen et al.Hamad Bin Khalifa University & University of TurkuUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Is More Better?”: Impact of Multiple Photos on Perception of Persona ProfilesIn this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. The results show that more contextual photos significantly improve the information end users derive from a persona profile; however, showing images of different people creates confusion and lowers the informativeness. Moreover, we discover that choice of pictures results in various interpretations of the persona that are biased by the end users’ experiences and preconceptions. The results imply that persona creators should consider the design power of photos when creating persona profiles.2018JSJoni O. Salminen et al.Hamad Bin Khalifa UniversityEye Tracking & Gaze InteractionOnline Identity & Self-PresentationCHI