International Journal of Human-Computer Studies最新文献_第5页

Movement instability and body image factors: Unobtrusive real-time detection of loss of control in ballet dancers 运动不稳定和身体形象因素：芭蕾演员失控的不显眼的实时检测

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-15 DOI: 10.1016/j.ijhcs.2025.103686

Concepción Valdez , Ana Tajadura-Jimenez , Monica Tentori

Understanding the relationship between movement variability and body image is essential in disciplines where motor control and body perception are closely linked, such as dance. The present study with 24 ballet dancers presents a computational approach for detecting moments of loss of control in elbow movement fluidity. This serves as an objective proxy for body image and body awareness, as subtle disruptions in movement, especially in joints that are not the primary focus of technical training, can reflect increased self-monitoring or discomfort, factors commonly associated with negative body image in dancers.

Through movement analysis during two common rehearsal contexts (i.e., marking choreography and full execution with music) we examined how movement variability differs based on task demands. Our findings show that loss of control moments are more frequent during marking, underscoring the influence of rehearsal context on both motor performance and body-related self-perception. Furthermore, we demonstrate that movement instability in the elbow joint can be associated with self-reported measures of body image and awareness, reinforcing the connection between motor variability and psychological well-being.

By identifying the elbow as a sensitive and reliable indicator of instability during ballet practice, our approach offers a lightweight alternative to full-body kinematic analysis, supporting practical applications beyond laboratory settings. From a Human-Computer Interaction (HCI) and Ubiquitous Computing (Ubicomp) perspective, this work contributes design insights for systems that integrate body image and movement behavior metrics. These findings open new possibilities for interactive technologies aimed at enhancing body image and improving movement precision in dancers and other movement practitioners.

在运动控制和身体感知密切相关的学科中，如舞蹈，理解运动变异性和身体形象之间的关系是必不可少的。目前的研究与24芭蕾舞者提出了一种计算方法来检测失去控制的时刻在肘部运动的流动性。这是身体形象和身体意识的客观代表，因为运动中的细微中断，特别是在不是技术训练的主要重点的关节，可以反映出自我监控或不适的增加，这些因素通常与舞者的负面身体形象有关。通过在两种常见的排练情境（即标记编舞和完全执行音乐）中的动作分析，我们研究了基于任务需求的动作可变性是如何不同的。我们的研究结果表明，在标记过程中失去控制的时刻更频繁，强调了排练环境对运动表现和身体相关自我感知的影响。此外，我们证明肘关节的运动不稳定可能与自我报告的身体形象和意识测量有关，从而加强了运动变异性和心理健康之间的联系。通过确定肘部在芭蕾练习中是一个敏感而可靠的不稳定性指标，我们的方法为全身运动学分析提供了一个轻量级的替代方案，支持实验室环境之外的实际应用。从人机交互（HCI）和普适计算（Ubicomp）的角度来看，这项工作为整合身体图像和运动行为指标的系统提供了设计见解。这些发现为旨在增强舞者和其他动作实践者的身体形象和提高动作精度的互动技术开辟了新的可能性。

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引用次数: 0

Unraveling multiparty conversations: From human interaction mechanisms to conversational agent challenges and persona design 解开多方对话：从人类交互机制到对话代理挑战和角色设计

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-12-19 DOI: 10.1016/j.ijhcs.2025.103719

Shitao Fang , Xingyu Liu , Takeo Igarashi , Koji Yatani

Multiparty conversations are ubiquitous and indispensable in diverse social and collaborative contexts. However, current conversational agents (CAs) face significant challenges in effectively engaging in such interactions, particularly within text-based environments. While earlier limitations were often attributed to the inadequacies of AI models, recent advances in large language models now compel us to revisit both our understanding of multiparty conversation and the way we design CAs. This paper synthesizes findings from two complementary qualitative investigations and proposes a conceptual model for designing CAs that can genuinely participate, rather than merely function as tools or outsiders. The first study, employing retrospective think-aloud sessions (N=30) with users in text-based multiparty settings, uncovers 5 key interactional mechanisms (e.g., Turn-taking Management, Presence Management) that underpin successful human-human multiparty interactions, derived from participants’ articulated perceptions and reasoning. Subsequently, the second study, through semi-structured interviews (N=15), identifies user expectations for CA integration and key traits (e.g., proactivity, social authenticity) that shape an ideal CA persona perceived by users as a genuine participant. Drawing from these human-centric insights, we then derive design considerations, aiming to guide the development of CAs capable of more natural, effective, and socially intelligent participation in multiparty conversation.

多方对话在不同的社会和协作环境中无处不在，也是不可或缺的。然而，当前的会话代理（ca）在有效地参与这种交互方面面临着重大挑战，特别是在基于文本的环境中。虽然早期的限制通常归因于人工智能模型的不足，但大型语言模型的最新进展现在迫使我们重新审视我们对多方对话的理解以及我们设计人工智能的方式。本文综合了两个互补的定性调查的结果，并提出了一个概念模型，用于设计能够真正参与的ca，而不仅仅是作为工具或局外人。第一项研究在基于文本的多方环境中与用户进行回顾性思考会话（N=30），揭示了5个关键的互动机制（例如，轮流管理，在场管理），这些机制支撑了成功的人与人之间的多方互动，源自参与者的清晰感知和推理。随后，第二项研究通过半结构化访谈（N=15），确定了用户对CA集成的期望和关键特征（例如，主动性，社会真实性），这些特征塑造了用户视为真正参与者的理想CA角色。从这些以人为中心的见解中，我们得出了设计考虑，旨在指导ca的开发，使其能够更自然、更有效、更智能地参与多方对话。

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引用次数: 0

MusicTraces: Combining music and painting to support adults with neurodevelopmental conditions and intellectual disabilities MusicTraces：结合音乐和绘画来帮助有神经发育障碍和智力障碍的成年人

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-07 DOI: 10.1016/j.ijhcs.2025.103675

Valentin Bauer , Giacomo Caslini , Marco Mores , Mattia Gianotti , Franca Garzotto

People with NeuroDevelopmental Conditions (NDC) and associated Intellectual Disability (ID) often face social and emotional issues affecting their well-being. Although art therapies like music-making or painting can be beneficial, they often lack adaptability for those with moderate-to-severe ID or limited language abilities. Multisensory creative technologies combining art practices offer promising solutions but remain under-explored. This research investigates the impact of integrating music-making and painting within an interactive multisensory environment to support social communication, emotional regulation, and well-being in adults with moderate-to-severe NDCs and ID. The two-player music and painting activity called MusicTraces was first created through co-design process involving caregivers and people with NDCs and ID. Two field studies were conducted. The first study compared MusicTraces with traditional group painting with music for ten adults, while the second examined its impact over two sessions on eight adults with more severe conditions. Both studies showed improved social communication, social regulation and well-being. Insights are discussed to enhance collaboration between people with NDCs and ID through interactive creative technologies.

患有神经发育疾病（NDC）和相关智力残疾（ID）的人经常面临影响其福祉的社会和情感问题。尽管音乐创作或绘画等艺术疗法可能是有益的，但对于中度至重度ID或语言能力有限的人来说，它们往往缺乏适应性。结合艺术实践的多感官创意技术提供了有希望的解决方案，但仍未得到充分探索。本研究调查了在互动多感官环境中整合音乐制作和绘画对中重度ndc和ID成人的社会沟通、情绪调节和幸福感的影响。这款名为“MusicTraces”的双人音乐和绘画活动最初是由护理人员和拥有ndc和ID的人共同设计的。进行了两次实地研究。第一项研究比较了10名成年人的MusicTraces与传统集体绘画的音乐，而第二项研究则对8名病情更严重的成年人进行了为期两次的研究。两项研究都显示了社交沟通、社会调节和幸福感的提高。讨论了通过互动创意技术加强国家自主贡献中心和ID之间的协作的见解。

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引用次数: 0

Creating text-based AI clones of myself: Exploring perceptions, development strategies, and challenges 创造基于文本的我的AI克隆体：探索认知、发展策略和挑战

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-24 DOI: 10.1016/j.ijhcs.2025.103692

Donggun Lee , Suyoun Lee , Hyunseung Lim, Hwajung Hong

AI clones are evolving to include digital representations of real world individuals as chatbots. While often used to replicate famous figures, as the technology becomes more accessible, it is crucial to understand whether everyday users would create their own clones and how they interact with them. In this study, within the scope of AI-generated personas and their role in representing users’ needs and identities, we focus on personas that directly reflect the qualities of real humans. We define this as AI self clones—conversational AI representations that reflect their human creators—and examine how creators construct and engage with them. We conducted a 7-day study in which participants (N=12) created and interacted with their text based AI self clones using CloneBuilder, a web-based authoring interface for configuring and tuning AI self clones. The system enables individuals to create AI representations that encapsulate their unique personality, values, and interaction style. Our findings reveal that each participant developed a clone tailored to their personal circumstances. As the participants iteratively refined and tested their clone, their direction and expectations of AI clones evolved from performing specific roles to becoming entities that facilitated self exploration and relationship formation. Unexpected responses from the clone prompted self reflection and identity questioning. Overall, this paper explores the motivations for creating these clones, the strategies participants use to build and refine them, and the moments of emotional connection and break out experiences that emerge during the crafting process, along with key design implications, challenges, and ethical considerations in developing AI self clones.

人工智能克隆正在进化，包括现实世界中个人的数字表示，如聊天机器人。虽然这种技术经常被用来复制名人，但随着技术变得越来越容易获得，了解日常用户是否会创建自己的克隆以及他们如何与之互动是至关重要的。在本研究中，在人工智能生成的人物角色及其在代表用户需求和身份方面的作用范围内，我们关注直接反映真实人类品质的人物角色。我们将其定义为人工智能的自我克隆——反映其人类创造者的对话式人工智能代表——并研究创造者如何构建和与它们互动。我们进行了一项为期7天的研究，其中参与者（N=12）使用CloneBuilder（用于配置和调整AI自克隆的基于web的创作界面）创建并与基于文本的AI自克隆进行交互。该系统使个人能够创建包含其独特个性、价值观和交互风格的AI表示。我们的研究结果表明，每个参与者都根据自己的个人情况定制了一个克隆体。随着参与者不断完善和测试他们的克隆体，他们对人工智能克隆体的方向和期望也从执行特定角色演变为成为促进自我探索和关系形成的实体。来自克隆人的意外反应引发了自我反思和身份质疑。总体而言，本文探讨了创造这些克隆的动机，参与者用于构建和完善它们的策略，以及在制作过程中出现的情感联系和突破体验，以及开发AI自我克隆的关键设计含义，挑战和道德考虑。

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引用次数: 0

A music recommendation system for constructed music-evoked episodic memories (CoMEEMs) 构建音乐诱发情景记忆的音乐推荐系统

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-12-17 DOI: 10.1016/j.ijhcs.2025.103717

Paul Raingeard de la Bletiere , Mark Neerincx , Rebecca Schaefer , Catharine Oertel

Music is widely used in human–computer interaction (HCI) to enhance engagement, sustain attention, and support cognitive stimulation. Yet its potential for deliberate mood regulation, particularly through personalized memory recall, remains largely unexplored.

Music-evoked autobiographical memories (MEAMs) are often elicited by well-known, favorite songs, yielding stronger mood effects than music without personal memory associations. However, songs can also trigger distressing memories, and will never capture all positive personal memories. Since happy personal memories can enhance mood, broader methods for retrieval are needed.

To address this, we introduce Constructed Music-Evoked Episodic Memories (CoMEEMs), a framework linking chosen episodic memories to music. By creating a personalized song-memory database, CoMEEMs enable autonomous mood regulation and communication in interactive systems, integrating memory cues—such as people and places—alongside mood congruence, to help choose songs with high mood regulatory impact.

In an experiment with 71 Dutch and French adults, participants described 87 positive memories and received song recommendations based on associated people and places, with and without mood matching. Results showed that song familiarity and genre were the strongest predictors of perceived fit, while valence, arousal, tempo, and lyrics played smaller roles. Mood congruence, especially in valence, significantly influenced song relevance. Participants emphasized the need for user input on emotional states and memory context. Based on these findings, we propose design guidelines to improve future music recommendation systems targeting memories.

音乐被广泛应用于人机交互（HCI）中，以增强参与，保持注意力，并支持认知刺激。然而，它在有意调节情绪方面的潜力，特别是通过个性化的记忆回忆，在很大程度上仍未得到探索。音乐诱发的自传式记忆（MEAMs）通常是由知名的、喜爱的歌曲引起的，比没有个人记忆关联的音乐产生更强的情绪效应。然而，歌曲也会引发痛苦的记忆，永远不会捕捉到所有积极的个人记忆。由于愉快的个人记忆可以改善情绪，因此需要更广泛的检索方法。为了解决这个问题，我们引入了构建音乐诱发情景记忆（CoMEEMs），这是一个将选定的情景记忆与音乐联系起来的框架。通过创建个性化的歌曲记忆数据库，CoMEEMs可以在互动系统中实现自主情绪调节和交流，将记忆线索（如人物和地点）与情绪一致性结合起来，帮助选择具有高情绪调节影响的歌曲。在一项针对71名荷兰和法国成年人的实验中，参与者描述了87个积极的记忆，并根据相关的人和地点（有或没有情绪匹配）收到了歌曲推荐。结果表明，歌曲熟悉度和类型是感知契合度的最强预测因子，而效价、唤醒、节奏和歌词的作用较小。情绪一致性，特别是在效价上，显著影响歌曲关联。参与者强调需要用户输入情绪状态和记忆背景。基于这些发现，我们提出了设计指南，以改进未来针对记忆的音乐推荐系统。

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引用次数: 0

Easy to handle: Exploring users’ interactions with an augmented reality human-machine interface for virtual stops in automated on-demand mobility scenarios 易于操作：探索用户与增强现实人机界面的交互，用于自动按需移动场景中的虚拟站点

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-08 DOI: 10.1016/j.ijhcs.2025.103671

Fabian Hub , Marc Wilbrink , Michael Oehl

For the success of future shared automated mobility on-demand (SAMOD) a high quality of service needs to be assured. One key challenge lies in the passenger journey, particularly in finding the designated virtual stop (vStop) for pick-up and identifying the approaching shuttle. Therefore, the new vStop human-machine interface (vStop HMI) concept supports passengers with means of augmented reality (AR). This explorative user study with young adults (N = 44) used a virtual reality (VR) setup to simulate the AR-based vStop HMI and answers two research questions across two consecutive scenarios: (1) When using an AR-based navigation aid like the vStop HMI, users tend to focus heavily on their device while walking, which may increase the risk of negligent roadside behavior. While restricting AR information access during walking might reduce this risk, how does it affect overall user experience? To examine this, we compared a vStop HMI with restricted AR information access against a baseline condition. Results showed positive effects on user experience and acceptance for both HMI versions, although workload was partly negatively affected. (2) When identifying the approaching shuttle, does using the vStop HMI effectively assist users in doing so and lead to positive user experience? Usability testing indicated positive rates of workload, user experience, and acceptance during the shuttle identification task. Overall, the findings suggest that selectively restricting AR information during navigation tasks can help mitigate undesired user behavior in roadside environments while maintaining high levels of pragmatic quality and acceptance. Moreover, the vStop HMI enables seamless shuttle identification, even under complex conditions. By improving these critical stages of the passenger journey, the vStop HMI concept has the potential to enhance the overall quality of SAMOD services and increase public acceptance of future shared, automated, demand-responsive transportation systems.

未来共享自动按需出行（SAMOD）的成功需要保证高质量的服务。一个关键的挑战在于乘客的旅程，特别是找到指定的虚拟站点（vStop）接送和识别接近的班车。因此，新的vStop人机界面（vStop HMI）概念为乘客提供增强现实（AR）的手段。这项探索性的用户研究（N = 44）使用虚拟现实（VR）设置来模拟基于ar的vStop HMI，并在两个连续的场景中回答了两个研究问题：(1)当使用基于ar的导航辅助工具（如vStop HMI）时，用户倾向于在行走时过多地关注他们的设备，这可能会增加疏忽路边行为的风险。虽然在行走过程中限制AR信息访问可能会降低这种风险，但它如何影响整体用户体验？为了检验这一点，我们将限制AR信息访问的vStop HMI与基线条件进行了比较。结果显示，两个HMI版本对用户体验和接受度都有积极影响，尽管工作量部分受到负面影响。(2)在识别接近的班车时，使用vStop人机界面是否有效地帮助用户识别并带来积极的用户体验？可用性测试表明，在航天飞机识别任务期间，工作量、用户体验和接受度都是积极的。总的来说，研究结果表明，在导航任务中有选择地限制AR信息可以帮助减轻路边环境中不受欢迎的用户行为，同时保持高水平的实用质量和接受度。此外，即使在复杂的条件下，vStop HMI也能实现无缝穿梭识别。通过改善乘客旅程的这些关键阶段，vStop HMI概念有可能提高SAMOD服务的整体质量，并提高公众对未来共享、自动化、需求响应的交通系统的接受度。

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引用次数: 0

SnapSound: Empowering everyone to customize sound experience with Generative AI SnapSound：让每个人都能通过生成式AI定制声音体验

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-06 DOI: 10.1016/j.ijhcs.2025.103673

Jiyeon Oh, Jin-Woo Jeong

The rise of user-centric experiences in the digital landscape has led to a surge in demand for personalized multimedia content. Users now seek to customize not only visual but also auditory components to suit their preferences. In this context, sound design plays a crucial role, enabling users to tailor audio experiences accordingly. However, its inherent complexity poses various challenges, particularly for non-expert users. To address this challenge, we introduce SnapSound, a novel assistive system designed specifically for non-experts in sound design for video content. Our system leverages generative AI to streamline the sound design process and offers intuitive tools for sound selection, synchronization, and seamless integration with visuals. Through a user study, we evaluate SnapSound’s usability and effectiveness compared to manual editing. Furthermore, our study provides valuable insights and design recommendations for enhancing user experience of future AI-based sound design systems. This work represents a significant step forward in empowering non-experts to easily customize their auditory experiences.

以用户为中心的体验在数字领域的兴起导致了对个性化多媒体内容需求的激增。用户现在不仅寻求自定义视觉组件，还寻求自定义听觉组件，以满足他们的偏好。在这种情况下，声音设计起着至关重要的作用，使用户能够相应地定制音频体验。然而，其固有的复杂性带来了各种挑战，特别是对于非专业用户。为了应对这一挑战，我们引入了SnapSound，这是一种专门为非视频内容声音设计专家设计的新型辅助系统。我们的系统利用生成式人工智能来简化声音设计过程，并为声音选择、同步和视觉无缝集成提供直观的工具。通过用户研究，我们评估了SnapSound的可用性和有效性，与手动编辑相比。此外，我们的研究为增强未来基于人工智能的声音设计系统的用户体验提供了宝贵的见解和设计建议。这项工作代表了一个重要的一步，使非专家能够轻松地定制他们的听觉体验。

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引用次数: 0

Ensuring provider fairness in recommender systems across coarse- and fine-grained groups 确保跨粗粒度和细粒度组的推荐系统中的提供者公平性

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-29 DOI: 10.1016/j.ijhcs.2025.103688

Elizabeth Gómez , David Contreras , Ludovico Boratto , Maria Salamó

The goal of provider fairness in recommender systems is to ensure equity by suggesting products from diverse providers or provider groups. When group fairness is among the goals of a system, coarse groups are frequently used, since there are typically few provider groups (e.g., two genders, or three/four age groups) and the number of items per group is large. Practically speaking, having fewer groups makes it easier for a platform to oversee how equity is distributed among them. Nevertheless, there are sensitive attributes, such as the age or the geographic provenance of the providers, that can be characterized at a fine granularity (e.g., one might group providers at the country level, instead of the continent one), which increases the number of groups and decreases the number of items per group. This study reveals that state-of-the-art models often fail to adequately recommend fine-grained provider groups when only coarse-grained groups are considered. This oversight can result in a fairness approach that, while adequate for broader demographic groups, neglects the needs of smaller subgroups. To address this disparity, we introduce CONFIGRE (COarse aNd FIne GRained Equity), an approach designed to balance equity across both coarse and fine-grained provider groups. Our methodology ensures that fairness is not only maintained at a broad demographic level but is also extended to more precisely defined groups, offering a more nuanced and comprehensive equity management in recommender systems.

推荐系统中供应商公平性的目标是通过推荐来自不同供应商或供应商群体的产品来确保公平。当群体公平是系统的目标之一时，通常使用粗糙的群体，因为通常很少有提供者群体（例如，两个性别，或三个/四个年龄组），每个群体的项目数量很大。实际上，拥有更少的群体使平台更容易监督公平是如何在他们之间分配的。然而，有些敏感属性，例如提供者的年龄或地理来源，可以以细粒度进行特征描述（例如，可以在国家一级对提供者进行分组，而不是在大陆一级），这会增加组的数量并减少每组的项目数量。这项研究表明，当只考虑粗粒度组时，最先进的模型往往不能充分推荐细粒度的提供者组。这种疏忽可能导致一种公平的方法，虽然适合于更广泛的人口群体，但忽视了较小的子群体的需求。为了解决这种差异，我们引入了CONFIGRE（粗粒度和细粒度公平性），这是一种旨在平衡粗粒度和细粒度提供者组之间公平性的方法。我们的方法确保公平不仅在广泛的人口层面上保持，而且还扩展到更精确定义的群体，在推荐系统中提供更细致和全面的公平管理。

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引用次数: 0

User personas, ideation and large language models: A post-hoc study 用户角色、构思和大型语言模型：一项事后研究

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-11-17 DOI: 10.1016/j.ijhcs.2025.103690

Stefano De Paoli

Covering the full ideation of design with Large Language Models (LLMs) and user interview data remains an underexplored area in the current scholarship. This paper begins to address this gap and investigates the integration of LLMs in a user-centered design process, creating user personas based on qualitative interview data. This work further explores using these personas for deriving scenarios, and functionality requirements, also with LLMs. First, LLMs are used to identify key themes of users from interviews, subsequently synthesising these into personas. Second, personas are expanded into scenarios and associated functionalities for a digital platform, simulating the ideation phase of a design process. The findings illustrate how LLMs can potentially streamline these early design stages. An evaluation shows that the process discovers a list of functionalities which are, to a reasonable extent, comparable to those that human researchers have produced separately.

The study proposes a practical procedure for integrating LLMs into qualitative design ideation workflows. The dataset used comprises 26 Open Access interviews from a previous Horizon project, from which eight personas and related scenarios are derived. To support further experimentation and practical applications, several computational resources used in performing analysis and generating LLM-based personas are shared. This enables reproducibility and encourages broader exploration of LLM-assisted design ideation.

用大型语言模型（llm）和用户访谈数据覆盖设计的完整构思，在当前的学术研究中仍然是一个未被充分探索的领域。本文开始解决这一差距，并调查法学硕士在以用户为中心的设计过程中的集成，基于定性访谈数据创建用户角色。这项工作进一步探索了使用这些角色来派生场景和功能需求，也与llm一起。首先，法学硕士被用来从访谈中识别用户的关键主题，随后将这些主题合成为人物角色。其次，人物角色被扩展为数字平台的场景和相关功能，模拟设计过程的构思阶段。这些发现说明了法学硕士如何有可能简化这些早期设计阶段。评估表明，该过程发现了一系列功能，这些功能在一定程度上可与人类研究人员单独产生的功能相媲美。该研究提出了一个将法学硕士整合到定性设计构思工作流程中的实用程序。使用的数据集包括来自先前Horizon项目的26个开放获取访谈，从中衍生出8个人物角色和相关场景。为了支持进一步的实验和实际应用，在执行分析和生成基于llm的角色时使用的几个计算资源被共享。这使得可重复性和鼓励法学硕士辅助设计思想的更广泛的探索。

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引用次数: 0

Pika: Designing a social-support agent to improve drivers’ experience in gig work 皮卡：设计一个社会支持代理，改善司机在零工工作中的体验

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2026-01-01 Epub Date: 2025-12-17 DOI: 10.1016/j.ijhcs.2025.103721

Wei Xiang , Xinli Chen , Tianhui Guo , Min Zhou , Shi Chen

Drivers in gig work face a steady stream of demanding tasks, with the interaction between agents and workers playing a significant role in drivers’ performance. However, there has been limited exploration of challenges and opportunities in these interactions. This paper introduces social support in conversational agents to improve human-agent interaction within driving gigs. We began by conducting semi-structured interviews with 20 driving workers to uncover interaction challenges and strategies they employ. Building upon these insights, we designed Pika, a conversational agent offering both informational and emotional support. A two-stage empirical study involving 59 driving workers demonstrated the benefits of Pika in improving work performance and user experience. Our work calls for a focus on equitable collaborative relationships to enhance work efficiency and well-being in gig work.

从事零工工作的司机面临着源源不断的高要求任务，代理人和工人之间的互动对司机的表现起着重要作用。然而，对这些互动中的挑战和机遇的探索有限。本文在会话代理中引入社会支持，以改善驾驶任务中的人机交互。我们首先对20名司机进行了半结构化的采访，以揭示他们采用的互动挑战和策略。基于这些见解，我们设计了Pika，一个提供信息和情感支持的对话代理。一项涉及59名驾驶工人的两阶段实证研究证明了皮卡在提高工作绩效和用户体验方面的好处。我们的工作要求关注公平的合作关系，以提高零工工作的工作效率和福祉。

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