Doodle Health: A Crowdsourcing Game for the Co-design and Testing of Pictographs to Reduce Disparities in Healthcare Communication

Supplementing patient education content with pictographs can improve the comprehension and recall of information, especially patients with low health literacy. Pictograph design and testing, however, are costly and time consuming. We created a Web-based game, Doodle Health, for crowdsourcing the drawing and validation of pictographs. The objective of this pilot study was to test the usability of the game and its appeal to healthcare consumers. The chief purpose of the game is to involve a diverse population in the co-design and evaluation of pictographs. We conducted a community-based focus group to inform the game design. Game designers, health sciences librarians, informatics researchers, clinicians, and community members participated in two Design Box meetings. The results of the meetings were used to create the Doodle Health crowdsourcing game. The game was presented and tested at two public fairs. Initial testing indicates crowdsourcing is a promising approach to pictograph development and testing for relevancy and comprehension. Over 596 drawings were collected and 1,758 guesses were performed to date with 70-90% accuracies, which are satisfactorily high

Design revolutions: IASDR 2019 Conference Proceedings. Volume 3: People

In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 3 includes papers from People track of the conference

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

Crowdsourcing Global Culture: Visual Representation in the Age of Information

This doctoral dissertation extends existing frameworks of visual content analysis by coupling them with crowdsourcing technologies for international data collection and an iterative, interpretative visual analysis. In the age of information, imagery continues to be consumed and circulated at exponential rates, influencing and changing global flows of information that parallels Internet communication technology as it penetrates and gains ubiquity in new regions. To investigate the visual, media, and cultural phenomena that lie within these globalized pictorial exchanges, a flexible, visually-based inquiry is essential. This qualitative, visual-ethnographic survey was conducted over the Internet and aims to help inform visually-based literacy and media studies and further image-based research methodologies. The researcher collected over 2000 drawings from 61 countries diverse in geography and culture. The researcher revealed fresh insights into the visual-textual relationship, identity, and representation in a globalized context, specifically looking at emergent tensions between local and global ways of interpretation and meaning construction online. The researcher also considers the effects of a technologically mediated visual culture and its potential to influence or change deeply ingrained ideas once specific to geography and culture into new global trends and evolving material practices. The analysis is centred on a selection of drawings from 106 Asian participants who drew intercultural representations of the words meal, marriage, and home. The most striking discoveries indicate varying degrees of homogeneity and hybridity among the visual cultural representations received and reveals connections among language, the Internet, advertising, and identity. The findings break with more traditional views of globalization occurring in a direct West-East flow and highlight regional powers that can serve as cultural hubs of attention. These hubs act as filters, possibly creating and hybridizing new commercial and cultural trends and positioning themselves as beacons of modernity with considerable visual cultural influence. The researcher also makes suggestions for future studies using an extended multimedia visual methodology as well as the potential inherent in emerging technologies for exploring phenomena in artistic, educative, and academic contexts

Pastplay: Teaching and Learning History with Technology

In the field of history, the Web and other technologies have become important tools in research and teaching of the past. Yet the use of these tools is limited—many historians and history educators have resisted adopting them because they fail to see how digital tools supplement and even improve upon conventional tools (such as books). In Pastplay, a collection of essays by leading history and humanities researchers and teachers, editor Kevin Kee works to address these concerns head-on. How should we use technology? Playfully, Kee contends. Why? Because doing so helps us think about the past in new ways; through the act of creating technologies, our understanding of the past is re-imagined and developed. From the insights of numerous scholars and teachers, Pastplay argues that we should play with technology in history because doing so enables us to see the past in new ways by helping us understand how history is created; honoring the roots of research, teaching, and technology development; requiring us to model our thoughts; and then allowing us to build our own understanding

Misogynistic Hate Speech on Social Networks: a Critical Discourse Analysis

The present dissertation aims at recognising online misogyny as a form of hate speech, by providing a qualitative analysis of this discourse on Twitter and Facebook. While recent reports in media coverage have revealed that sexist harassment is the most pervasive social problem on Web 2.0, much scholarly research has mainly focused on other types of hate speech (e.g., racist and xenophobic vilification), overlooking the seriousness of misogynistic verbal abuse. The multilayered impact of misogynous discourse on women’s lives shows the urgent need to recognise gender-based prejudice as a form of hate speech, and to provide a more thorough and updated theorisation of this phenomenon. For this reason, the present dissertation suggests considering online misogyny as a harmful speech act which employs different tactics and discursive strategies to harass and silence women who engage in online public conversation. Following the methodology of feminist Critical Discourse Analysis, it develops an extensive qualitative study of the abuse experienced online by six women who reside in three different countries (i.e., Australia, Italy, and the USA). By analysing the discursive strategies commonly employed in user-generated contents to reaffirm hegemonic patriarchal ideologies and fixed gender identities, this dissertation also examines the entanglement between gender prejudice and other types of discrimination (i.e., racism, xenophobia, homophobia, transphobia, and ageism), and it identifies the articulation of online misogynistic hate speech through a series of tactics which harm women’s lives on multiple levels. Therefore, it presents a taxonomy of these impacts through a new model that was specifically developed for the research at issue, and that will hopefully guide future research on misogynistic hate speech. In conclusion, this study argues for the development of effective educational tools to tackle sexist hate speech online, to guarantee women’s digital citizenship, and to promote a more respectful conversation in cyberspace

Translanguaging in Online Language Learning: Case Studies of Self-Directed Chinese Learning of Multilingual Adults

The aim of the thesis is to explain how multilingual adults use their linguistic and semiotic repertoires, which are records of their life experiences and mobility, to facilitate the learning of Chinese, in particular with the reading and writing of Chinese characters. The thesis begins with an overview of the background of the study in relation to the advent of mobile technologies and mobile learners. Through conducting an extensive literature review, it is argued that out-of-class, self-directed language learning through the use of online platforms has been an under-explored area and this thesis aims to fill in that research gap. This thesis adopts a multiperspectival approach in its choice of theoretical framework, consisting of translanguaging, multimodality and multilingualism. Each of these approaches contributes to the thesis in a unique way that crosses theoretical boundaries. This thesis illustrates the possibility of connecting these concepts and using them in a meaningful way so that they complement each other in explaining the complexity of meaning-making. Consequently, a combination of methodological approaches are used, including ethnography and social semiotic multimodality. Together they work in partnership with each other with an aim to generate a holistic view of how learning and teaching is conducted in the online learning environment. Eleven learners were studied in the thesis, among which four case studies are discussed in detail, with a focus on two learning practices: learning to read and learning to write Chinese characters. Learners engaged in these two practices demonstrated how they used their entire linguistic repertoires to construct knowledge through the process of translanguaging. The four case studies supported the need for a 'multimodal turn' in applied linguistics research in order to capture the multimodal nature of communication. Through repeatedly testing the boundaries and reach of translanguaging, multimodality and multilingualism, this thesis calls for a dialogue between applied linguistics and multimodality so that they can complement each other with the unique set of toolkits and explanatory powers that they have. This thesis has provided an example of how these perspectives can be brought together in a meaningful way to explore communication contexts that are complex and diverse

Digital Interaction and Machine Intelligence

This book is open access, which means that you have free and unlimited access. This book presents the Proceedings of the 9th Machine Intelligence and Digital Interaction Conference. Significant progress in the development of artificial intelligence (AI) and its wider use in many interactive products are quickly transforming further areas of our life, which results in the emergence of various new social phenomena. Many countries have been making efforts to understand these phenomena and find answers on how to put the development of artificial intelligence on the right track to support the common good of people and societies. These attempts require interdisciplinary actions, covering not only science disciplines involved in the development of artificial intelligence and human-computer interaction but also close cooperation between researchers and practitioners. For this reason, the main goal of the MIDI conference held on 9-10.12.2021 as a virtual event is to integrate two, until recently, independent fields of research in computer science: broadly understood artificial intelligence and human-technology interaction