Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Supporting Collaborative Health Tracking in the Hospital: Patients' Perspectives

The hospital setting creates a high-stakes environment where patients' lives depend on accurate tracking of health data. Despite recent work emphasizing the importance of patients' engagement in their own health care, less is known about how patients track their health and care in the hospital. Through interviews and design probes, we investigated hospitalized patients' tracking activity and analyzed our results using the stage-based personal informatics model. We used this model to understand how to support the tracking needs of hospitalized patients at each stage. In this paper, we discuss hospitalized patients' needs for collaboratively tracking their health with their care team. We suggest future extensions of the stage-based model to accommodate collaborative tracking situations, such as hospitals, where data is collected, analyzed, and acted on by multiple people. Our findings uncover new directions for HCI research and highlight ways to support patients in tracking their care and improving patient safety

인공지능과 대화하기: 일대일 그리고 그룹 상용작용을 위한 대화형 에이전트 시스템 개발

학위논문(박사) -- 서울대학교대학원 : 사회과학대학 언론정보학과, 2022.2. 이준환."인간-컴퓨터 상호작용"과 "사용자 경험"을 넘어, "인간-인공지능 상호작용" 그리고 "알고리즘 경험"의 시대가 도래하고 있다. 기술의 발전은 우리가 의사소통하고 협업하는 방식의 패러다임을 전환했다. 기계 에이전트는 인간 커뮤니케이션에서 적극적이며 주도적인 역할을 수행한다. 하지만 효과적인 AI 기반 커뮤니케이션과 토론 시스템 디자인에 대한 이해와 논의는 부족한 것이 사실이다. 이에 본 연구는 인간-컴퓨터 상호작용의 관점에서 다양한 형태의 커뮤니케이션을 지원할 수 있는 기술적 방법을 탐색하는 것을 목표로 한다. 이를 위해 저자는 일대일 그리고 그룹 상호작용을 지원하는 대화형 에이전트를 제시한다. 구체적으로 본 연구는 1) 일대일 상호작요에서 사용자 관여를 높이는 대화형 에이전트, 2) 일상적인 소셜 그룹 토론을 지원하는 에이전트, 3) 숙의 토론을 가능하게 하는 에이전트를 디자인 및 개발하고 그 효과를 정량적 그리고 정성적으로 검증했다. 시스템을 디자인함에 있어서 인간-컴퓨터 상호작용뿐 아니라, 커뮤니케이션학, 심리학, 그리고 데이터 과학을 접목한 다학제적 접근 방식이 적용되었다. 첫 번째 연구는 일대일 상호작용 상황에서 사용자의 관여 증진을 위한 대화형 에이전트의 효과를 검증했다. 설문조사라는 맥락에서 수행된 이 연구는 웹 설문조사에서 응답자의 불성실로 인해 발생하는 응답 데이터 품질의 문제를 극복하기 위한 새로운 인터랙션 방법으로 텍스트 기반 대화형 에이전트의 가능성을 탐색하는 것을 목표로 했다. 이를 위해 2 (인터페이스: 웹 對 챗봇) X 2 (대화 스타일: 포멀 對 캐쥬얼) 실험을 진행했으며, 만족화 이론에 근거하여 응답 데이터의 품질을 평가했다. 그 결과, 챗봇 설문조사의 참여자가 웹 설문조사의 참여자보다 더 높은 수준의 관여를 보이고, 결과적으로 더 높은 품질의 데이터를 생성하는 것을 확인할 수 있었다. 하지만 이런 챗봇의 데이터 품질에 대한 효과는 챗봇이 친구 같고 캐쥬얼한 대화체를 사용할 때만 나타났다. 이 결과는 대화형 인터랙티비티가 인터페이스뿐 아니라 대화 스타일이라는 효과적인 메세지 전략을 동반할 때 발생하는 것을 의미한다. 두 번째 연구는 일상적인 소셜 채팅 그룹에서 집단의 의사결정과정과 토론을 지원하는 대화형 시스템에 대한 것이다. 이를 위해 GroupfeedBot이라는 대화형 에이전트를 제작하였으며, GroupfeedBot은 (1) 토론 시간을 관리하고, (2) 구성원들의 균등한 참여를 촉진하며, (3) 구성원들의 다양한 의견을 요약 및 조직화하는 기능을 갖고 있다. 해당 에이전트를 평가하기 위해 다양한 태스크 (추론, 의사결정, 자유 토론, 문제 해결 과제)와 그룹 규모(소규모, 중규모)에 관하여 사용자 조사를 시행했다. 그 결과 의견의 다양성 측면에서 GroupfeedBot으로 토론한 집단이 기본 에이전트와 토론한 집단보다 더 다양한 의견을 생성했지만 산출된 결과의 품질과 메시지 양에 있어서는 차이가 없는 것을 확인할 수 있었다. 균등한 참여에 대한 GroupfeedBot의 효과는 태스크의 특성에 따라 다르게 나타났는데, 특히 자유 토론 과제에서 GroupfeedBot이 참여자들의 균등한 참여를 촉진했다. 세 번째 연구는 숙의 토론을 지원하는 대화형 시스템에 대한 것이다. 세 번째 연구에서 개발된 DebateBot은 GroupfeeedBot과 달리 더 진지한 사회적 맥락에서 적용되었다. DebateBot은 (1) 생각하기-짝짓기-공유하기 (Think-Pair-Share) 전략에 따라 토론을 구조화하고, (2) 과묵한 토론자에게 의견을 요청함으로써 동등한 참여를 촉진하는 두 가지 주요 기능을 수행했다. 사용자 평가 결과 DebateBot은 그룹 상호작용을 개선함으로써 심의 토론을 가능하게 했다. 토론 구조화는 토론의 질에 긍정적인 효과를 발휘하였고, 참여자 촉진은 진정한 합의 도달에 기여하였으며, 그룹 구성원들의 주관적 만족도를 향상했다. 본 연구는 이 세 가지 연구의 결과들을 바탕으로 인간-인공지능 커뮤니케이션에 대한 다양한 시사점들을 도출하였으며, 이를 TAMED (Task-Agent-Message-Information Exchange-Relationship Dynamics) 모델로 정리하였다.The advancements in technology shift the paradigm of how individuals communicate and collaborate. Machines play an active role in human communication. However, we still lack a generalized understanding of how exactly to design effective machine-driven communication and discussion systems. How should machine agents be designed differently when interacting with a single user as opposed to when interacting with multiple users? How can machine agents be designed to drive user engagement during dyadic interaction? What roles can machine agents perform for the sake of group interaction contexts? How should technology be implemented in support of the group decision-making process and to promote group dynamics? What are the design and technical issues which should be considered for the sake of creating human-centered interactive systems? In this thesis, I present new interactive systems in the form of a conversational agent, or a chatbot, that facilitate dyadic and group interactions. Specifically, I focus on: 1) a conversational agent to engage users in dyadic communication, 2) a chatbot called GroupfeedBot that facilitates daily social group discussion, 3) a chatbot called DebateBot that enables deliberative discussion. My approach to research is multidisciplinary and informed by not only in HCI, but also communication, psychology and data science. In my work, I conduct in-depth qualitative inquiry and quantitative data analysis towards understanding issues that users have with current systems, before developing new computational techniques that meet those user needs. Finally, I design, build, and deploy systems that use these techniques to the public in order to achieve real-world impact and to study their use by different usage contexts. The findings of this thesis are as follows. For a dyadic interaction, participants interacting with a chatbot system were more engaged as compared to those with a static web system. However, the conversational agent leads to better user engagement only when the messages apply a friendly, human-like conversational style. These results imply that the chatbot interface itself is not quite sufficient for the purpose of conveying conversational interactivity. Messages should also be carefully designed to convey such. Unlike dyadic interactions, which focus on message characteristics, other elements of the interaction should be considered when designing agents for group communication. In terms of messages, it is important to synthesize and organize information given that countless messages are exchanged simultaneously. In terms of relationship dynamics, rather than developing a rapport with a single user, it is essential to understand and facilitate the dynamics of the group as a whole. In terms of task performance, technology should support the group's decision-making process by efficiently managing the task execution process. Considering the above characteristics of group interactions, I created the chatbot agents that facilitate group communication in two different contexts and verified their effectiveness. GroupfeedBot was designed and developed with the aim of enhancing group discussion in social chat groups. GroupfeedBot possesses the feature of (1) managing time, (2) encouraging members to participate evenly, and (3) organizing the members’ diverse opinions. The group which discussed with GroupfeedBot tended to produce more diverse opinions compared to the group discussed with the basic chatbot. Some effects of GroupfeedBot varied by the task's characteristics. GroupfeedBot encouraged the members to contribute evenly to the discussions, especially for the open-debating task. On the other hand, DebateBot was designed and developed to facilitate deliberative discussion. In contrast to GroupfeedBot, DebateBot was applied to more serious and less casual social contexts. Two main features were implemented in DebateBot: (1) structure discussion and (2) request opinions from reticent discussants.This work found that a chatbot agent which structures discussions and promotes even participation can improve discussions, resulting in higher quality deliberative discussion. Overall, adding structure to the discussion positively influenced the discussion quality, and the facilitation helped groups reach a genuine consensus and improved the subjective satisfaction of the group members. The findings of this thesis reflect the importance of understanding human factors in designing AI-infused systems. By understanding the characteristics of individual humans and collective groups, we are able to place humans at the heart of the system and utilize AI technology in a human-friendly way.1. Introduction 1.1 Background 1.2 Rise of Machine Agency 1.3 Theoretical Framework 1.4 Research Goal 1.5 Research Approach 1.6 Summary of Contributions 1.7 Thesis Overview 2. Related Work 2.1 A Brief History of Conversational Agents 2.2 TAMED Framework 3. Designing Conversational Agents for Dyadic Interaction 3.1 Background 3.2 Related Work 3.3 Method 3.4 Results 3.5 Discussion 3.6 Conclusion 4. Designing Conversational Agents for Social Group Discussion 4.1 Background 4.2 Related Work 4.3 Needfinding Survey for Facilitator Chatbot Agent 4.4 GroupfeedBot: A Chatbot Agent For Facilitating Discussion in Group Chats 4.5 Qualitative Study with Small-Sized Group 4.6 User Study With Medium-Sized Group 4.7 Discussion 4.8 Conclusion 5. Designing Conversational Agents for Deliberative Group Discussion 5.1 Background 5.2 Related Work 5.3 DebateBot 5.4 Method 5.5 Results 5.6 Discussion and Design Implications 5.7 Conclusion 6. Discussion 6.1 Designing Conversational Agents as a Communicator 6.2 Design Guidelines Based on TAMED Model 6.3 Technical Considerations 6.4 Human-AI Collaborative System 7. Conclusion 7.1 Research Summary 7.2 Summary of Contributions 7.3 Future Work 7.4 Conclusion박

Design Knowledge for Virtual Learning Companions from a Value-centered Perspective

The increasing popularity of conversational agents such as ChatGPT has sparked interest in their potential use in educational contexts but undermines the role of companionship in learning with these tools. Our study targets the design of virtual learning companions (VLCs), focusing on bonding relationships for collaborative learning while facilitating students’ time management and motivation. We draw upon design science research (DSR) to derive prescriptive design knowledge for VLCs as the core of our contribution. Through three DSR cycles, we conducted interviews with working students and experts, held interdisciplinary workshops with the target group, designed and evaluated two conceptual prototypes, and fully coded a VLC instantiation, which we tested with students in class. Our approach has yielded 9 design principles, 28 meta-requirements, and 33 design features centered around the value-in-interaction. These encompass Human-likeness and Dialogue Management, Proactive and Reactive Behavior, and Relationship Building on the Relationship Layer (DP1,3,4), Adaptation (DP2) on the Matching Layer, as well as Provision of Supportive Content, Fostering Learning Competencies, Motivational Environment, and Ethical Responsibility (DP5-8) on the Service Layer

Mechanisms of Common Ground in Human-Agent Interaction: A Systematic Review of Conversational Agent Research

Human-agent interaction is increasingly influencing our personal and work lives through the proliferation of conversational agents in various domains. As such, these agents combine intuitive natural language interactions by also delivering personalization through artificial intelligence capabilities. However, research on CAs as well as practical failures indicate that CA interaction oftentimes fails miserably. To reduce these failures, this paper introduces the concept of building common ground for more successful human-agent interactions. Based on a systematic review our analysis reveals five mechanisms for achieving common ground: (1) Embodiment, (2) Social Features, (3) Joint Action, (4) Knowledge Base, and (5) Mental Model of Conversational Agents. On this basis, we offer insights into grounding mechanisms and highlight the potentials when considering common ground in different human-agent interaction processes. Consequently, we secure further understanding and deeper insights of possible mechanisms of common ground in human-agent interaction in the future

The history of chatbots: the journey from psychological experiment to educational object

Chatbots represent a strong and distinctive theme in the current literature on technology in education. What is lacking, however, is an analysis of them in terms of historical development or deeper historical-discursive classification. This paper focuses on the history of chatbots and places it in the context of a critical reflection on studies focusing on chatbots as educational objects between 2006-2021. It offers an analysis of each study and places them in the context of the development of the field as a whole. The study identifies three vital discourses that can be identified in the development of chatbots from a historical perspective - Turing-oriented, Searle-oriented and educational interaction-oriented

Designing a visual component of communication within 3D avatar virtual worlds

Merged with duplicate record 10026.1/2600 on 08.20.2017 by CS (TIS)Over the last few years 3D avatar virtual worlds (AVW) have emerged on the Internet. These are computer generated, multi-user, graphical spaces within which people meet, form social groups and interact with each other in real time, typically through the exchange of text or audio messages. Each user is represented within the space by a digital image known as an avatar, which is usually humanoid in form, and is predominantly under the control of the person it represents. This thesisd escribesa creativep roject that is concernedw ith aspectso f social communication between users of "Ws. In particular, an avatar is designed that is capable of performing body language, and a set of useful gestures are implemented that support aspects of social interaction and integrate with verbal discourse in a meaningful way. In addition to this, a number of scenic properties are derived that enable better comprehension of the non verbal communication, e. g. spatial arrangement, camera position and lighting effects. The research consists of a number of interrelated design activities which include reviewing the literature on avatar design in order to locate goals and variety of the project, therefore building on the on the work of others; a comparative review of three popular 3D AVWs to explore the design problem; a study that aims to gain an understanding of the social dynamics involved; the adaptation of a diagrammatic technique for the purpose of modelling social interaction; the development of 2D and 3D prototype techniques exploring the application of the social interaction modelling technique; a body of creative work developing ideas for conveying non verbal communication and the appraisal of the effectiveness of this creative work. The research contributes to the field of avatar design in a number of ways. Firstly, it develops our understanding of social dynamics in virtual worlds. Secondly, it postulates modes of non verbal communication for both individuals and social groups that supports multi-participatory social discourse. Additionally, a number of useful research techniques have been devised, such as a linear diagramming technique that can be used to represent the structure of conversation thereby facilitating the exploration and understanding of the dynamics of AVW social discourse. The work is of interest to those working in the field of avatar and multi-user virtual world design. It may also be of interest to anyone thinking of using an avatar virtual world for the application of collaborative leaming, collaborative games and conferencing

LOOKING BENEATH THE TIP OF THE ICEBERG: THE TWO-SIDED NATURE OF CHATBOTS AND THEIR ROLES FOR DIGITAL FEEDBACK EXCHANGE

Enterprises are forecasted to spend more on chatbots than on mobile app development by 2021. Up to today little is known on the roles chatbots play in facilitating feedback exchange. However, digitization and automation put pressure on companies to setup digital work environments that enable reskilling of employees. Therefore, a structured analysis of feedback-related chatbots for Slack was conducted. Our results propose six archetypes that reveal the roles of chatbots in facilitating feedback exchange on performance, culture and ideas. We show that chatbots do not only consist of conversational agents integrated into instant messenger but are tightly linked to complementary front-end systems such as mobile and web apps. Like the upper part of an iceberg, the conversational agent is above water and visible within the chat, whereas many user interactions of feedback-related chatbots are only possible outside of the instant messenger. Further, we extract six design principles for chatbots as digital feedback systems. We do this by analyzing chatbots and linking empirically observed design features to (meta-)requirements derived from explanatory theory on feedback, self-determination and persuasive systems. The results suggest that chatbots benefit the social environment of conversation agents and the richness of the graphical user interface of external applications