International Journal of Human-Computer Studies最新文献

{"title":"What we chose to (Not) share: Unpacking how HCI researchers self-disclose in interactions with participants with stigmatised identities","authors":"Yvon Ruitenburg ,&nbsp;Hayoun Noh ,&nbsp;Jing Li ,&nbsp;Sima Amirkhani ,&nbsp;Hyuna Jo ,&nbsp;Max Van Kleek ,&nbsp;Younah Kang ,&nbsp;Sarah Foley ,&nbsp;Minha Lee","doi":"10.1016/j.ijhcs.2026.103755","DOIUrl":"10.1016/j.ijhcs.2026.103755","url":null,"abstract":"<div><div>As Human-Computer Interaction (HCI) researchers increasingly conduct studies involving populations with stigmatised identities, more researchers must focus on creating conversational spaces where participants feel comfortable discussing their experiences. This study unpacks how and why HCI researchers engage in self-disclosure to facilitate such spaces. We share eight autoethnographic personal stories of key moments when we disclosed or concealed personal information in our HCI studies with diverse participant groups (people with dementia, victims of online romance scams, children with autism, and North Korean defectors). Through analysing these stories, we found that these decisions were shaped by various goals: creating a welcoming environment, demonstrating credibility, establishing common ground, reducing stigma, and directing the interview’s focus. The acts of disclosure or concealment affected the interactions with participants, the collected data, and the well-being of the researcher and participant. We argue that greater awareness, reflection, guidance, and sharing are needed regarding self-disclosure in HCI research and offer a reflexive guide to help researchers prepare for and reflect on their self-disclosure practices. By making these practices visible and open to discussion, we aim to make researcher-participant interactions in sensitive settings more ethical, effective, and transparent.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103755"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidance++: Rendering poking feedback on wrist for 6DoF guidance","authors":"Yi-Ting Chiang,&nbsp;Shih-Hao Wang,&nbsp;Hsi-An Chen,&nbsp;Wei-Lin Hsu,&nbsp;Hsin-Ruey Tsai","doi":"10.1016/j.ijhcs.2026.103766","DOIUrl":"10.1016/j.ijhcs.2026.103766","url":null,"abstract":"<div><div>In telecollaboration or guidance in extended reality (XR), haptic guidance could be combined and complemented with visual guidance or physical-world visual feedback. It is more challenging for more sophisticated manipulation guidance, since it involves sequential steps with various directions and movements, <em>e.g.</em>, fetching an object from a drawer (opening, retrieving, placing), operating a complex panel with multiple types of operating elements, or preparing a drink (shaking, pouring). To achieve manipulation or even trajectory guidance on a hand, a hands-free guidance device, not occupying manipulation, with high degrees-of-freedom (DoF) in both translation and rotation, and without complicated haptic patterns for intuition, is required. However, the current guidance methods either leverage haptic patterns, increasing mental effort, or do not achieve such high DoF for both translation and rotation. Therefore, we propose a wrist-worn device, Guidance++, to render 6DoF poking guidance cues in translation and rotation directions. Guidance++ consists of a wristband and two poking sets, each with two tiltable tactors. The poking sets move along the wristband and tilt the tactors to render poking cues in 6DoF as if being poked by others in the real world. We conducted a guidance study to evaluate the performance in trajectory and rotation guidance, separately. Furthermore, we performed an XR experience study to observe how Guidance++ guides users in manipulation tasks, involving sequential steps, and to show its applications enabled by the proposed 6DoF force guidance.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103766"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147401525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emotional artificial intelligence: The impact of chatbot empathy and emotional tone on consumer satisfaction and word of mouth","authors":"Simoni F Rohden ,&nbsp;Lélis Balestrin Espartel","doi":"10.1016/j.ijhcs.2026.103764","DOIUrl":"10.1016/j.ijhcs.2026.103764","url":null,"abstract":"<div><div>This research examines the impact of empathic chatbots on consumer responses, exploring how Artificial Intelligence (AI) emotional skills, particularly the use of specific empathic language and emotional tone, can enhance user satisfaction and word of mouth intentions. Across three experimental studies (n = 643), findings reveal that empathic conversational agents are perceived as warmer and more competent, positively influencing satisfaction and encouraging word of mouth. The study advances existing literature by demonstrating that empathy in chatbots is feasible and effective in creating more affective and socially engaging consumer interactions, thereby mitigating some of the negative perceptions typically associated with AI tools. Warmth and competence were key mediating factors, suggesting that consumers ascribe human-like qualities to chatbot interactions, enhancing their service experience. The findings also highlight the practical benefits of implementing empathic AI in service settings, where language adaptations and rapport-building behaviors can improve service quality perception and consumer trust. Given the rapid integration of AI in consumer contexts, understanding the role of empathic chatbots in shaping customer experience is crucial. Future research directions include examining the empathic chatbot’s role across varied service types and exploring its impact on service employees’ perceptions. These insights contribute to theoretical and managerial perspectives, advocating for the integration of empathy as a core feature in AI-driven customer service.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103764"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147402102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A three-layered transparency framework for communicating algorithmic systems in the public sector: Exploring participatory prototype design with end users","authors":"Teresa Correa ,&nbsp;Francisca Luco ,&nbsp;Yelena Hernández-Estrada ,&nbsp;Iñaki Oyarzún-Merino ,&nbsp;Claudia López","doi":"10.1016/j.ijhcs.2026.103769","DOIUrl":"10.1016/j.ijhcs.2026.103769","url":null,"abstract":"<div><div>Algorithmic transparency debates have largely focused on technical strategies for unveiling how AI systems generate outcomes, often treating opacity as a computational problem detached from the institutional and social settings in which algorithmic decisions are enacted. Addressing this gap, this study examines how citizens perceive, trust, and demand transparency from algorithmic systems embedded in Chilean public services, particularly those that mediate access to education and health benefits. Drawing on the Transparency by Design framework, we conceptualize transparency as a sociotechnical, three-layered construct shaped by micro-level informational conditions, meso‑level relational dynamics, and macro-level institutional structures. We conducted six participatory design focus groups (<em>n</em> = 48) to elicit citizens’ perceptions, expectations, and proposals for transparency. Findings show that transparency expectations are tightly linked to institutional trust: participants tended to assume AI reliability when discussing it in abstract terms, but in concrete, high-impact algorithmic systems, they demanded explanations that clarify institutional processes, strengthen situational awareness, and preserve human control. Citizens articulated distinct ex-ante and ex-post transparency needs, favored progressive disclosure, and called for accessible communication about system integrity together with clear avenues to challenge decisions. We argue that algorithmic transparency in the public sector must extend beyond technical explanations to include relational and institutional aspects, and that participatory approaches are essential for designing transparency that fosters citizen agency.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103769"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147402108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cognitive and emotional engagement design factors in text-based pedagogical conversational agents: Impacts on student learning and motivation","authors":"Sunhyo Oh ,&nbsp;Taejun Park ,&nbsp;Gahgene Gweon","doi":"10.1016/j.ijhcs.2026.103750","DOIUrl":"10.1016/j.ijhcs.2026.103750","url":null,"abstract":"<div><div>Text-based pedagogical conversational agents (PCA) can encourage students’ engagement via natural conversations and have become increasingly prevalent in educational contexts. In this study, we explored how cognitive and emotional engagement can support learning achievement and five dimensions of intrinsic motivation. We conducted two between-subjects studies with 170 sixth-grade students using GeomBot, a text-based PCA. Our experimental results showed that for cognitive engagement, students presented with the constructive mode, compared to the active mode, showed a greater learning achievement, and interest-enjoyment. Emotional engagement was examined in terms of agent warmth and competency. Specifically, we observed higher learning achievement and interest-enjoyment when interacting with a high-warmth GeomBot while students who interacted with a high-competency GeomBot showed higher interest-enjoyment. Significant interaction effects between learning mode and agent warmth level were observed for learning achievement, interest-enjoyment, and tension-pressure, while no significant interaction effect was observed between learning mode and agent competency level.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103750"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The eyes show it: Exploring eye behavior and impact on human mental state during task interruption","authors":"Siyuan Chen,&nbsp;Julien Epps","doi":"10.1016/j.ijhcs.2026.103772","DOIUrl":"10.1016/j.ijhcs.2026.103772","url":null,"abstract":"<div><div>One technology adoption outcome is ever more frequent task interruptions, which makes interruption management a central human computer interface design problem. Studies on interruption often focused on the link between interruptions and genesis of error and eye gaze to validate associated task cues engagement. How eye behaviors reflect load type and level changes between primary and interrupting tasks and how emotional interruptions impact mental state in primary tasks – factors that contribute to cognitive processing – remain unanswered. In this study, we analyzed performance metrics and eye behaviors from 18 participants while they completed an uninterrupted and interrupted roleplay task. Our results reveal that although interruption notification could affect the time to attend to an interruption, high cognitive load resulted in a detrimental impact on completion time and low cognitive load led to time reset for primary tasks. No existing evidence suggests that affect type influences the time metrics, however, high arousal and valence induced by interruptions altered eye behavior upon returning to the primary task, indicating less visual information taken and under a high load level, which showed evidence of the impact of affective interruption for the first time. Noteworthily, the eye behaved differently at interruption beginning compared with the end and uninterrupted task transitions, indicating the feasibility of including eye behavior for interruption estimation. Overall, these results are the first experimental evidence for theories that interruption can cause high mental load, posit extra mental effort, forgetting primary tasks and behaviors being directed by the current most active goal.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103772"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147401526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of language comprehension in viewing video game live-streams: The effect of subtitles and AI voice on engagement and parasocial relationships","authors":"Jotaro Tasaki,&nbsp;Hendrik Engelbrecht,&nbsp;Ryosuke Yamanishi","doi":"10.1016/j.ijhcs.2026.103753","DOIUrl":"10.1016/j.ijhcs.2026.103753","url":null,"abstract":"<div><div>Live-streaming in the context of the gaming community (i.e., live-streams of video gameplay) has become a popular form of entertainment, enabling real-time interactions between streamers and viewers. However, many of these interactions actively rely on language comprehension and production, therefore limiting the reach of any stream to a more restricted audience. Live-streaming being a very different type of media compared to other existing media, makes the effects and outcomes of translation methods traditionally used in video media unknown. This study investigates how subtitles and AI generated dubbed voices as a form of machine translation affect viewer engagement and parasocial relationships (PSR) in viewing live-streams, by using mock videos imitating live-streams. Results suggest that translation helps the viewers to have a deeper understanding of the content regardless of language, compared to conditions without language comprehension support. Results have also suggested that language comprehension with machine translation leads to higher engagement and higher PSR, although the effects of each translation modality differed depending on the game titles. These findings highlight the potential for machine translation to be used in live-streaming, while also emphasizing the potentially differential effects of modalities of translation across types of streams.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103753"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"iGOAT: Intelligent linkography for online analysis and tracking of the ideation process","authors":"Chenkang He ,&nbsp;Haolun Lan ,&nbsp;Xuan Cheng ,&nbsp;Juncong Lin ,&nbsp;Guoliang Luo ,&nbsp;Jiazhi Xia ,&nbsp;Cheng Wang ,&nbsp;Wei Chen","doi":"10.1016/j.ijhcs.2026.103768","DOIUrl":"10.1016/j.ijhcs.2026.103768","url":null,"abstract":"<div><div>Ideation, a critical step in the design process, is usually accompanied by lively and perhaps disorganized discussion, and thus can easily go out of control. Linkography was proposed to track, visualize and analyze the ideation process. However, manual maintenance is tedious and places a heavy burden on users, often requiring offline construction. This paper presents <em>iGOAT</em>, an AI-enabled computational linkography tool, with large language models(LLMs) introduced to semi-automatically analyze the ideas raised by users and suggest new ideas/stimuli for inspiration. A coarse-to-fine exploration scheme is introduced to provide users with the freedom to either get an overview of the whole process or delve into details at specific moments. In-context visual stimuli are generated, decomposed into different visual aspects, and hierarchically arranged in a limited screen space. The effectiveness of the online tracking and visualization of the ideation process with linkography was validated in a series of experiments and user studies. LLMs show great potential in providing comprehensive support for the entire ideation process, covering move extraction, association and inspiration etc, although there are still some limitations for further investigation such as bias and accuracy.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103768"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147402122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploratory search with generative AI: An empirical study on the impact of interaction design strategies on information exploration and cognitive load","authors":"Nakyung Kim,&nbsp;Yong Gu Ji","doi":"10.1016/j.ijhcs.2026.103771","DOIUrl":"10.1016/j.ijhcs.2026.103771","url":null,"abstract":"<div><div>Recent advances in generative artificial intelligence (AI) have significantly simplified users’ information-seeking processes by providing natural language interfaces and integrated responses. However, limited research has examined how both user-driven input and system-generated output jointly shape the exploratory search experience. The present study empirically investigates how the interaction design of generative AI affects exploratory information behavior and cognitive outcomes based on Cognitive Load Theory.</div><div>We examined the effects of response disclosure methods and prompt initiative level in a 2 × 2 within-subject experiment with 36 participants. Specifically, we investigated whether disclosing AI responses progressively and fostering higher user initiative through prompt guidance enhances the exploratory search experience. Search tasks were designed around unfamiliar but relatable topics, intended to elicit curiosity-driven information seeking. Subjective measures (perceived knowledge change, engagement, and cognitive load) and behavioral data (prompt frequency and similarity) were analyzed.</div><div>The results showed that progressive disclosure and high prompt initiative significantly increased users’ perceived knowledge change, engagement, and germane cognitive load, and fostered more exploratory behavior. Notably, an interaction effect was observed for germane cognitive load as the effect of user prompt initiative on germane cognitive load varied with the response disclosure method. By highlighting the interplay between system features and user agency, this study provides empirical implications that the user’s level of initiative should be taken into account when selecting an appropriate information presentation strategy. The findings offer practical guidelines for AI interface design to alleviate cognitive load and facilitate deeper information exploration during complex search tasks.</div><div>Taken together, we contribute to the theoretical and practical implications for designing conversational search systems that accommodate diverse information-seeking contexts.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103771"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147402123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cross-domain study on the user experience of ChatGPT-based recommendations","authors":"Yizhe Zhang ,&nbsp;Yucheng Jin ,&nbsp;Li Chen ,&nbsp;Ting Yang","doi":"10.1016/j.ijhcs.2026.103743","DOIUrl":"10.1016/j.ijhcs.2026.103743","url":null,"abstract":"<div><div>Conversational recommender systems (CRS) allow users to express preferences and provide feedback through natural language. With the emergence of ChatGPT, there is growing interest in leveraging its capabilities to enhance user engagement and improve recommendation quality. Research suggests that well-crafted prompts are essential for ChatGPT to accurately interpret tasks and generate high-quality responses. Therefore, we define Prompt Guidance (PG) as offering an example of crafting queries (prompts) that clearly specify the context, constraints, and procedures for the recommendations users may seek. Offering Prompt Guidance (PG) to novices can improve the overall quality of conversations. Meanwhile, in the field of recommender systems, Recommendation Domain (RD) can influence user behavior and perception. This study explores how PG and RD interact to affect user experience (UX) in ChatGPT-based recommendations. To investigate this, we conducted an empirical study with 100 participants, analyzing dialogue data to uncover user intents and system actions. Using a within-subject (e.g., book vs. job recommendations) and between-subject (providing prompts vs. none) design, we evaluated UX under different experimental conditions. Results show that PG enhances explainability, adaptability, ease of use, and transparency. In terms of the RD factor, the system promotes higher user engagement, greater novelty, and a stronger intention to try suggested items in book recommendations compared to job recommendations. Overall, ChatGPT-based recommendations not only induce novel dialogue behaviors but also improve UX in multiple aspects, such as usefulness and alignment with user preferences. These findings provide valuable insights into designing CRS that leverage ChatGPT’s potential to deliver effective and engaging user experiences.</div></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":"210 ","pages":"Article 103743"},"PeriodicalIF":5.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146192296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}