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Advancements in Context Recognition for Edge Devices and Smart Eyewear: Sensors and ApplicationsFrancesca Palermo, Luca Casciano · 2025Edge devices have garnered significant attention for their ability to process data locally, providing low-latency, context-aware services without the need for extensive reliance on cloud computing. This capability is particularly crucial in context recognition, which enables dynamic adaptation to a user’s real-time environment. Applications range from health monitoring and augmented reality to smart assistance and social interaction analysis. Among edge devices, smart eyewear has emerged as a promising platform for context recognition due to its ability to unobtrusively capture rich, multi-modal sensor data. However, the deployment of context-aware systems on such devices presents unique challenges, including real- time processing, energy efficiency, sensor fusion, and noise management. This manuscript provides a comprehensive survey of context recognition in edge devices, with a specific emphasis on smart eyewear. It reviews the state-of-the-art sensors and applications for context inference. Furthermore, the paper discusses key challenges in achieving reliable, low-latency context recognition while addressing energy and computational constraints. By synthesizing advancements and identifying gaps, this work aims to guide the development of more robust and efficient solutions for context recognition in edge computing. INDEX TERMS Context recognition, edge computing, smarteyewear, wearable technology.

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Visualizing the knowledge mapping of artificial intelligence in education: A systematic reviewInformation Technologies · 2024Artificial Intelligence (AI) plays a vital role in the growth and progress of educa- tion. Therefore, there is a need to scientifically explore the application of Artifi- cial Intelligence in Education (AIED) and systematically analyze the development trends and research hotspots of AIED to provide reference for researchers. In this study, 1356 articles (2016–2023) in WOS were selected for further research, utiliz- ing knowledge graph analysis. Using both VOSviewer and CiteSpace, which facili- tated triangulating the data across software platforms to ensure the reliability of the results, the main highly co-cited literature and keywords were thoroughly analyzed. The key highlights of the results are: Firstly, the study reveals three major themes in the field of AI education, namely, medical theme, educational theme, and ChatGPT theme. Secondly, important literature and nodes in the field of AIED were identi- fied. Thirdly, the study demonstrates the main technologies in the field of AIED, including Natural Language Processing, Machine Learning, Deep Learning, and Generative Artificial Intelligence. Finally, the burst analysis illustrates the hotspots and themes of the AIED at different stages. This study enriches the understanding of the fundamental knowledge and research frontiers essential to the application of AIED, which helps identify the patterns and trends for future research and teaching practices.

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Unveiling the landscape of generative artificial intelligence in education: a comprehensive taxonomy of applications, challenges, and future prospectsInformation Technologies · 2024The rapid advancement of Generative Artificial Intelligence (GenAI) models, particularly ChatGPT, has sparked widespread discussion among educators and researchers regarding their potential implications for education. This study presents a comprehensive taxonomy of GenAI in academia and education, encompassing a wide range of applications, challenges, ethical considerations, and future prospects. Drawing on a scoping review of 453 articles, including the 50 most cited works throughout 2023, the taxonomy provides a state-of-the-art analysis of the current landscape of GenAI in education. The taxonomy offers a theoretical framework that aligns with the current discourse in GenAI and education, providing a critical evaluation of the existing literature and proposing innovative perspectives and solu- tions. The practical implications of the taxonomy for educators, researchers, and policymakers are highlighted, emphasizing the need for ethical considerations and informed policies to maximize the benefits of GenAI while minimizing its risks and negative impacts.

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A Systematic Review on Human and ComputerRESHNA NANDIPI · 2024As technology continues to advance at an unprecedented pace, the interaction between humans and computers has become an integral part of our daily lives. This study provides a comprehensive review of the evolving landscape of human- computer interaction (HCI) research, focusing on the key concepts, methodologies, and advancements in this interdisciplinary field. The review begins by presenting an overview of the historical evolution of HCI, tracing its roots from early command-line interfaces to the current era of intuitive touchscreens and voice recognition systems. The fundamental principles of HCI, including usability, accessibility, and user- centered design, are examined in detail, highlighting their significance in enhancing the overall user experience. Moreover, the review explores various interaction modalities that have emerged over the years, such as graphical user interfaces, haptic feedback, augmented reality, and virtual reality. It examines the strengths, limitations, and potential applications of these modalities, shedding light on the future possibilities they hold for human-computer interaction. Furthermore, the review delves into the emerging trends in HCI research, including natural language processing, gesture recognition, machine learning, and affective computing. These advancements have paved the way for more personalized and adaptive interfaces, enabling computers to understand and respond to human emotions and intentions, thereby fostering deeper levels of engagement and satisfaction. The study also addresses the challenges and ethical considerations associated with human-computer interaction, such as privacy concerns, data security, and algorithmic biases. It emphasizes the importance of designing inclusive and ethical systems that respect users' rights and values.

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AI Assistance for UX: A Literature Review Through Human-Centered AIYuwen Lu · 2024Recent advancements in HCI and AI research attempt to support user experience (UX) practitioners with AI-enabled tools. Despite the potential of emerging models and new interaction mechanisms, mainstream adoption of such tools remains limited. We took the lens of Human-Centered AI and presented a systematic literature review of 359 papers, aiming to synthesize the current landscape, identify trends, and uncover UX practitioners’ unmet needs in AI support. Guided by the Double Diamond design framework, our analysis un- covered that UX practitioners’ unique focuses on empathy building and experiences across UI screens are often overlooked. Simplistic AI automation can obstruct the valuable empathy-building pro- cess. Furthermore, focusing solely on individual UI screens without considering interactions and user flows reduces the system’s prac- tical value for UX designers. Based on these findings, we call for a deeper understanding of UX mindsets and more designer-centric datasets and evaluation metrics, for HCI and AI communities to collaboratively work toward effective AI support for UX. CCS CONCEPTS • General and reference →Surveys and overviews; • Human- centered computing →HCI design and evaluation methods; Interaction design process and methods; Empirical studies in interaction design; Systems and tools for interaction design.

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Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature ReviewTita A.Bach · 2024Ensuring quality human-AI interaction (HAII) in safety-critical industries is essential. Failure to do so can lead to catastrophic and deadly consequences. Despite this urgency, existing research on HAII is limited, fragmented, and inconsistent. We present here a survey of that literature and recommendations for research best practices that should improve the field. We divided our investigation into the following areas: 1) terms used to describe HAII, 2) primary roles of AI-enabled systems, 3) factors that influence HAII, and 4) how HAII is measured. Additionally, we described the capabilities and maturity of the AI-enabled systems used in safety-critical industries discussed in these articles. We found that no single term is used across the literature to describe HAII and some terms have multiple meanings. According to our literature, seven factors influence HAII: user characteristics (e.g., user personality), user perceptions and attitudes (e.g., user biases), user expectations and experience (e.g., mismatched user expectations and experience), AI interface and features (e.g., interactive design), AI output (e.g., perceived accuracy), explainability and interpretability (e.g., level of detail, user understanding), and usage of AI (e.g., heterogeneity of environments). HAII is most measured with user-related subjective metrics (e.g., user perceptions, trust, and attitudes), and AI-assisted decision-making is the most common primary role of AI-enabled systems. Based on this review, we conclude that there are substantial research gaps in HAII. Researchers and developers need to codify HAII terminology, involve users throughout the AI lifecycle (especially during development), and tailor HAII in safety-critical industries to the users and environments. INDEX TERMS Artificial intelligence, humans, measurement, methods, safety, safety-critical, society, survey, systematic literature review, technology readiness level, user.

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A Systematic Review of the Impact of Auxiliary Information on Recommender SystemsMatthew Ayemowa · 2024Recommender systems are essential tools that provide personalized user experiences across various domains such as e-commerce, entertainment, social media, education and content streaming. The integration of auxiliary information, including user demographics, item attributes, and contextual data has shown significant promise in enhancing the performance of recommender systems. This systematic review investigates the impact of incorporating auxiliary information into various types of recommender systems, examining recent advancements, methodologies, datasets, evaluation metrics, and to equally examine its significance on generative artificial intelligence. Similarly, five (5) reputable online databases were used to identify the relevant studies for answering our research questions. To obtain effective results of our findings, we focus more on the recent studies published between (2019 - June 2024) to ensure that of our findings up-to-date. After filtering the selected primary papers that solely focused on auxiliary information recommender systems a total of 37 papers were identified and analyzed. Our analysis shows the most utilized datasets, metrics, models, addressed issues and future works. Research limitations and future scope are also highlighted to assist researchers and practitioners for their future studies. INDEX TERMS Recommender systems, auxiliary information, data sparsity, cold start problem.

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Understanding Design Collaboration Between Designers and Artificial Intelligence: A Systematic Literature ReviewYang Shi, Tian Gao et al. · 2023Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing. Designers, as a special user group interacting with AI, have received more attention in the Human-Computer Interaction community. Prior work has discussed emerging challenges that persist in designing for AI. However, few systematic reviews focus on AI for design to understand how designers and AI can augment each other's complementary strengths in design collaboration. In this work, we conducted a landscape analysis of AI for design, via a systematic literature review of 93 papers. The analysis first provides a bird's eye view of overall patterns in this area. The analysis also reveals three themes interpreted from the paper corpus associated with AI for design, including AI assisting designers, designers assisting AI, and characterizing designer-AI collaboration. We discuss the implications of our findings and suggested methodological proposals to guide HCI toward research and practices that center on collaborative creativity.

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An Outlook into the Future of Egocentric VisionChiara Plizzari · 2023What will the future be? We wonder! In this survey, we explore the gap between current research in egocentric vision and the ever-anticipated future, where wearable computing, with outward facing cameras and digital overlays, is expected to be integrated in our every day lives. To understand this gap, the article starts by envisaging the future through character-based stories, showcasing through examples the limitations of current technology. We then provide a mapping between this future and previously defined research tasks. For each task, we survey its seminal works, current state-of-the-art methodologies and available datasets, then reflect on shortcomings that limit its applicability to future research. Note that this survey focuses on software models for egocentric vision, independent of any specific hardware. The paper concludes with recommendations for areas of immediate explorations so as to unlock our path to the future always-on, personalised and life-enhancing egocentric vision.

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End-User Development for Artificial Intelligence: A Systematic Literature ReviewAndrea Esposito · 2023In recent years, Artificial Intelligence has become more and more relevant in our society. Creating AI systems is almost always the prerogative of IT and AI experts. However, users may need to create intelligent solutions tailored to their specific needs. In this way, AI systems can be enhanced if new approaches are devised to allow non-technical users to be directly involved in the definition and personalization of AI technologies. End-User Development (EUD) can provide a solution to these problems, allowing people to create, customize, or adapt AI-based systems to their own needs. This paper presents a systematic literature review that aims to shed the light on the current landscape of EUD for AI systems, i.e., how users, even without skills in AI and/or programming, can customize the AI behavior to their needs. This study also discusses the current challenges of EUD for AI, the potential benefits, and the future implications of integrating EUD into the overall AI development process.

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Impact of AI on Mobile Computing - A Systematic Review from a Human Factors PerspectiveHelmut Degen · 2023Editorial Board Members Elisa Bertino, Purdue University, West Lafayette, IN, USA Wen Gao, Peking University, Beijing, China Bernhard Steffen , TU Dortmund University, Dortmund, Germany Moti Yung , Columbia University, New York, NY, USA The series Lecture Notes in Computer Science (LNCS), including its subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI), has established itself as a medium for the publication of new developments in computer science and information technology research, teaching, and education. LNCS enjoys close cooperation with the computer science R & D community, the series counts many renowned academics among its volume editors and paper authors, and collaborates with prestigious societies. Its mission is to serve this international commu- nity by providing an invaluable service, mainly focused on the publication of conference and workshop proceedings and postproceedings. LNCS commenced publication in 1973. Helmut Degen · Stavroula Ntoa · Abbas Moallem Editors

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Algorithms for the Development of Adaptive Web Interfaces: A Systematic Literature ReviewMichael Rodrigues da Silva · 2022The User Interface (UI) is a fundamental part of web interfaces, being considered a fundamental aspect of user satisfaction when using a web application. The UI that offers a good User Experience (UX) is the one that makes the interaction as simple and efficient as possible for the user to achieve the previously desired goals. In this way, web interfaces that have adaptive interfaces tend to offer a better UX, as they seek to adapt to the needs and desires of users. Therefore, this paper carries out a Systematic Literature Review (SLR) to identify the most used algorithms for the development of Adaptive Web Interfaces (AWI). The results indicate that the use of Machine Learning (ML) techniques, both to improve the performance of some task and to induce results, are the most popular ways to develop AWI. During the execution of SLR, 294 articles were analyzed using automated and manual searches, and inclusion, exclusion and quality criteria were applied to them. The research findings allow us to state that the topic is quite relevant to the academic community, with an average publication of 20 papers each year.1

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Bibliometric and Visualized Analysis of User Experience Design Research: From 1999 to 2019Rui Li · 2022With increasing research attention to user experience (UX), UX design (UXD) has gained concomitant interest. This study systematically reviews UXD research using a bibliometrical knowledge map. We collected and reviewed 14,825 documents to analyze UXD research from five perspectives: keyword trends, reference co-citation, author co-citation, categories, and author institutes. (a) UXD, as a research term, broadens the boundaries of experience and design and brings them together. (b) Publications in UXD focus on user, business, and technology orientation. (c) Author co-citation analysis reveals “invisible college networks” among UXD scholars. (d) Computer Science and Engineering are the most significant majors in UXD, although interdisciplinary research is common. (e) Research from the United States dominates. This review recognizes research gaps and future trends for conceptualizing and assessing UXD skills. The findings can benefit researchers, curriculum designers, and instructors.

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A review of AI teaching and learning from 2000 to 2020Davy Tsz Kit Ng, Min Lee et al. · 2022In recent years, with the popularity of AI technologies in our everyday life, research- ers have begun to discuss an emerging term “AI literacy”. However, there is a lack of review to understand how AI teaching and learning (AITL) research looks like over the past two decades to provide the research basis for AI literacy education. To summarize the empirical findings from the literature, this systematic literature review conducts a thematic and content analysis of 49 publications from 2000 to 2020 to pave the way for recent AI literacy education. The related pedagogical mod- els, teaching tools and challenges identified help set the stage for today’s AI literacy. The results show that AITL focused more on computer science education at the uni- versity level before 2021. Teaching AI had not become popular in K-12 classrooms at that time due to a lack of age-appropriate teaching tools for scaffolding support. However, the pedagogies learnt from the review are valuable for educators to reflect how they should develop students’ AI literacy today. Educators have adopted collab- orative project-based learning approaches, featuring activities like software develop- ment, problem-solving, tinkering with robots, and using game elements. However, most of the activities require programming prerequisites and are not ready to scaf- fold students’ AI understandings. With suitable teaching tools and pedagogical sup- port in recent years, teaching AI shifts from technology-oriented to interdisciplinary design. Moreover, global initiatives have started to include AI literacy in the lat- est educational standards and strategic initiatives. These findings provide a research foundation to inform educators and researchers the growth of AI literacy education that can help them to design pedagogical strategies and curricula that use suitable technologies to better prepare students to become responsible educated citizens for today’s growing AI economy.

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Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directionsRene Riedl · 2022Artificial intelligence (AI) refers to technologies which support the execution of tasks normally requiring human intelligence (e.g., visual perception, speech recognition, or decision-making). Examples for AI systems are chatbots, robots, or autono- mous vehicles, all of which have become an important phenomenon in the economy and society. Determining which AI system to trust and which not to trust is critical, because such systems carry out tasks autonomously and influence human- decision making. This growing importance of trust in AI systems has paralleled another trend: the increasing understanding that user personality is related to trust, thereby affecting the acceptance and adoption of AI systems. We developed a frame- work of user personality and trust in AI systems which distinguishes universal personality traits (e.g., Big Five), specific personality traits (e.g., propensity to trust), general behavioral tendencies (e.g., trust in a specific AI system), and specific behaviors (e.g., adherence to the recommendation of an AI system in a decision-making context). Based on this framework, we reviewed the scientific literature. We analyzed N = 58 empirical studies published in various scientific disciplines and developed a “big picture” view, revealing significant relationships between personality traits and trust in AI systems. However, our review also shows several unexplored research areas. In particular, it was found that prescriptive knowledge about how to design trustworthy AI systems as a function of user personality lags far behind descriptive knowledge about the use and trust effects of AI systems. Based on these findings, we discuss possible directions for future research, including adaptive systems as focus of future design science research.

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How Well Does the Algorithm Know Me?Julia Graefe · 2022The use of artificial intelligence (AI) in everyday products increases and thereby also the interest on human-AI interaction. Research on user-adaptive systems still lacks uniform terminology and common definitions. To fill this gap, a taxonomy of user-adaptive systems, the Levels of Adaptive Sensitive Responses (LASR), has been proposed in previous research. The LASR levels are a first step towards a uniform classification of user-adaptive systems, but still need to be validated in terms of comprehensiveness and accuracy. This paper presents an evaluation of the LASR taxonomy through its application on technical products, to examine whether the taxonomy is complete and applicable in a meaningful way. We used a four steps analysis approach, covering the definition of classification criteria, two research iterations on suitable user-adaptive product features, and the analysis to which degree these features fulfill the classification criteria. As a result, our analysis shows that nine out of eleven analyzed product features can clearly be categorized into one of the five levels of LASR. Two features showed characteristics of two different levels which reveals that the levels are not mutually exclusive but can be combined within one product feature.

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Model-based intelligent user interface adaptation: challenges and future directionsSilvia Abrahao · 2021Adapting the user interface of a software system to the requirements of the context of use continues to be a major challenge, particularly when users become more demanding in terms of adaptation quality. A considerable number of methods have, over the past three decades, provided some form of modelling with which to support user interface adaptation. There is, however, a crucial issue as regards in analysing the concepts, the underlying knowledge, and the user experience afforded by these methods as regards comparing their benefits and shortcomings. These methods are so numerous that positioning a new method in the state of the art is challenging. This paper, therefore, defines a conceptual reference framework for intelligent user interface adaptation containing a set of conceptual adaptation properties that are useful for model-based user interface adaptation. The objective of this set of properties is to understand any method, to compare various methods and to generate new ideas for adaptation. We also analyse the opportunities that machine learning techniques could provide for data processing and analysis in this context, and identify some open challenges in order to guarantee an appropriate user experience for end-users. The relevant literature and our experience in research and industrial collaboration have been used as the basis on which to propose future directions in which these challenges can be addressed.

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Inertial Motion Tracking on Mobile and Wearable Devices: Recent Advancements and ChallengesZhipeng Song, Zhichao Cao et al. · 2021Motion tracking via Inertial Measurement Units (IMUs) on mobile and wearable devices has attracted significant interest in recent years. High-accuracy IMU-tracking can be applied in various applications, such as indoor navigation, gesture recognition, text input, etc. Many efforts have been devoted to improving IMU-based motion tracking in the last two decades, from early calibration techniques on ships or airplanes, to recent arm motion models used on wearable smart devices. In this paper, we present a comprehensive survey on IMU-tracking techniques on mobile and wearable devices. We also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices and possible directions to address these challenges. Key words: Inertial Measurement Units (IMUs); motion tracking; accelerometer; gyroscope; magnetometer; sensor fusion

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Artificial intelligence in E‑Commerce: a bibliometric study and literature reviewBawack · 2021This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes guidelines on how information systems (IS) research could contribute to this research stream. To this end, the innovative approach of combining bibliometric analysis with an extensive literature review was used. Bibliometric data from 4335 documents were analysed, and 229 articles published in leading IS journals were reviewed. The bibliometric analysis revealed that research on AI in e-commerce focuses primarily on recommender systems. Sentiment analysis, trust, personalisation, and optimisation were identified as the core research themes. It also places China- based institutions as leaders in this researcher area. Also, most research papers on AI in e-commerce were published in computer science, AI, business, and management outlets. The literature review reveals the main research topics, styles and themes that have been of interest to IS scholars. Proposals for future research are made based on these findings. This paper presents the first study that attempts to synthesise research on AI in e-commerce. For researchers, it contributes ideas to the way forward in this research area. To practitioners, it provides an organised source of information on how AI can support their e-commerce endeavours.

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Putting Humans in the Natural Language Processing Loop - A SurveyDongjin Choi · 2020How can we design Natural Language Process- ing (NLP) systems that learn from human feed- back? There is a growing research body of Human-in-the-loop (HITL) NLP frameworks that continuously integrate human feedback to improve the model itself. HITL NLP research is nascent but multifarious—solving various NLP problems, collecting diverse feedback from different people, and applying different methods to learn from collected feedback. We present a survey of HITL NLP work from both Machine Learning (ML) and Human- Computer Interaction (HCI) communities that highlights its short yet inspiring history, and thoroughly summarize recent frameworks fo- cusing on their tasks, goals, human interac- tions, and feedback learning methods. Finally, we discuss future directions for integrating hu- man feedback in the NLP development loop.

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The Trend of Published Literature on User Experience (UX) Evaluation: A Bibliometric Analysis2020The term user experience (UX) emerged in the early 1990’s. Thenceforth, UX has become a key term for researchers to focus on aspects that go beyond usability and particularly in the field of Human Computer Interaction (HCI). The aim of this study is to analyse the bibliometric aspect of UX evaluation literature from Scopus database whereby 644 papers were extracted. The study utilised publishing or perishing software to collect the data, while VOSviewer was used to visualise the data. Data analysis was also carried out using SPSS and Microsoft Excel. The publication of articles between 2018 and 2019 increased to 117 articles in 2019 and this is the highest publication to date. Most of the publications are from journals and conferences, mainly in English. Based on the analysis of the co-occurrence map of all keywords in the articles published, the keywords frequently used by the authors are user experience (416) and user experience evaluation (155). Most of the research related to UX evaluation was conducted in United States; and the researchers prefer multi-authored publications. The co-authorship map of the journal’s authors showed that V. Roto is one of the dominant co-authorships. Other than that, Arnold P. O. S. Vermeeren is also the most cited author of UX evaluation in Scopus database. This study presents the history of scientific literature in user experience evaluation and will provide guidance for future research.

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Measuring the impact of online personalization - Past, present and futureMarkus Zanker⁎, Laurens Rookb et al. · 2019Research on understanding, developing and assessing personalisation systems is spread over multiple disciplines and builds on methodologies and findings from several different research fields and traditions, such as Artificial Intelligence (AI), Machine Learning (ML), Human–Computer Interaction (HCI), and User Modelling based on (applied) social and cognitive psychology. The fields of AI and ML primarily focus on the optimisation of per- sonalisation applications, and concentrate on creating ever more accurate algorithmic decision makers and prediction models. In the fields of HCI and Information Systems, scholars are primarily interested in the phe- nomena around the use and interaction with personalisation systems, while Cognitive Science (partly) delivers the theoretical underpinnings for the observed effects. The aim and contribution of this work is to put together the pieces about the impact of personalisation and recommendation systems from these different backgrounds in order to formulate a research agenda and provide a perspective on future developments.

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History and Future of Human AutomationJanssen · 2019We review the history of human-automation interaction research, assess its current status and identify future directions. We start by reviewing articles that were published on this topic in the International Journal of Human-Computer Studies during the last 50 years. We find that over the years, automated systems have been used more frequently (1) in time-sensitive or safety-critical settings, (2) in embodied and situated systems, and (3) by non-professional users. Looking to the future, there is a need for human-automation interaction research to focus on (1) issues of function and task allocation between humans and machines, (2) issues of trust, incorrect use, and confusion, (3) the balance between focus, divided attention and attention management, (4) the need for interdisciplinary approaches to cover breadth and depth, (5) regulation and explainability, (6) ethical and social dilemmas, (7) allowing a human and humane experience, and (8) radically different human-automation inter- action.

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Self-Adaptation in Mobile Apps: a SystematicGrua · 2019With their increase, smartphones have become more integral components of our lives but due to their mobile nature it is not possible to develop a mobile application the same way another software system would be built. In order to always provide the full service, a mobile application needs to be able to detect and deal with changes of context it may be presented with. A suitable method to achieve this goal is self-adaptation. However, as of today it is difficult to have a clear view of existing research on self-adaptation in the context of mobile applications. In this paper, we apply the systematic literature review methodology on selected peer-reviewed papers focusing on self- adaptability in the context of mobile applications. Out of 607 potentially relevant studies, we select 44 primary studies via carefully-defined exclusion and inclusion criteria. We use known modelling dimensions for self-adaptive software systems as our classification framework, which we apply to all selected primary studies. From the synthesized data we obtained, we produce an overview of the state of the art. The results of this study give a solid foundation to plan for future research and practice on engineering self-adaptive mobile applications.

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A survey of cyber‑physical system implementations of real‑time personalized interventionsRobert Steele · 2019Advances in sensor technology and machine learning as well as the widespread use of smartphones are shifting the focus of healthcare. Emerging paradigms such as cyber-physical systems (CPSs) make possible the transition from reactive to preventive care. CPSs can be implemented to achieve effective mobile health solutions and to provide sophisticated new mechanisms to monitor an individual’s state in real-time via the use of sensors and mobile devices. Despite the significant potential impact of such systems, their implementation poses a range of complex technical challenges. This article surveys the state-of-the-art in implementations of CPSs for real-time personalized interventions. A general three layer architecture which can be used to consider current implementations is first presented along with a description of its main components. We also propose a three level taxonomy in accordance with the system capabilities. Then, the principal technical challenges, human-machine interaction challenges and future directions are discussed. Fifteen of the state-of-the-art implementations are qualitatively evaluated in terms of sensor capabilities, just-in-time reaction, interruptibility, and adherence, among other characteristics. By reviewing the state-of-the-art of the systems that have been built to-date, the focus of the review is to summarize current technical challenges and future opportunities for both future CPS implementers and behavioral scientists designing CPS for personalized interventions.

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A Comparative Analysis of Industry of Human-AI Interaction GuidelinesHaekyu Park · 2019With the recent release of AI interaction guidelines from Apple, Google, and Microsoft, there is clearly interest in understanding the best practices in human-AI interaction. However, industry standards are not determined by a single company, but rather by the synthesis of knowledge from the whole community. We have surveyed all of the design guidelines from each of these major companies and developed a single, unified structure of guidelines, giving develop- ers a centralized reference. We have then used this framework to compare each of the surveyed companies to find differences in areas of emphasis. Finally, we encourage people to contribute additional guidelines from other companies, academia, or individuals, to pro- vide an open and extensible reference of AI design guidelines at [https://ai-open-guidelines.readthedocs.io/](https://ai-open-guidelines.readthedocs.io/). Index Terms: Human-centered computing—Human computer in- teraction (HCI); Computing methodologies—Artificial intelligence

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Information Dashboards and Tailoring Capabilities - A Systematic Literature ReviewAndrea Vazques-Ingelmo · 2019The design and development of information dashboards are not trivial. Several factors must be accounted; from the data to be displayed to the audience that will use the dashboard. However, the increase in popularity of these tools has extended their use in several and very different contexts among very different user profiles. This popularization has increased the necessity of building tailored displays focused on specific requirements, goals, user roles, situations, domains, etc. Requirements are more sophisticated and varying; thus, dashboards need to match them to enhance knowledge generation and support more complex decision-making processes. This sophistication has led to the proposal of new approaches to address personal requirements and foster individualization regarding dashboards without involving high quantities of resources and long development processes. The goal of this work is to present a systematic review of the literature to analyze and classify the existing dashboard solutions that support tailoring capabilities and the methodologies used to achieve them. The methodology follows the guidelines proposed by Kitchenham and other authors in the field of software engineering. As results, 23 papers about tailored dashboards were retrieved. Three main approaches were identified regarding tailored solutions: customization, personalization, and adaptation. However, there is a wide variety of employed paradigms and features to develop tailored dashboards. The present systematic literature review analyzes challenges and issues regarding the existing solutions. It also identifies new research paths to enhance tailoring capabilities and thus, to improve user experience and insight delivery when it comes to visual analysis. INDEX TERMS SLR, systematic literature review, tailoring, custom, personalized, adaptive, information dashboards.

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A Framework for the Development of a Dynamic AdaptiveVivien Johnston · 2019 The aim of this paper is to present PhD research that aims to enhance the User Experience by proposing a framework that combines the three core components of: dynamic interfaces; adaptive interfaces; and intelligent interfaces. Initial research into the field has identified a gap at the intersection of these types of interaction. A dynamic interaction understands the user, their device and their physical environment to provide a basic User Experience. An adaptive interaction understands the user’s capabilities further to implement an enhanced experience via usability and accessibility whilst recognising the flow of the user and their pipeline. The intelligent interaction builds further upon this through the incorporation of Machine Learning algorithms that assist in making the interface intelligent and provide a personalised experience for each user based upon their end goal. This in turn will reduce a user’s cognitive load and enhance their interactive experience with an interface. CCS CONCEPTS • Human-centered computing~Human computer interaction (HCI) • Human-centered computing~Usability testing • Computing methodologies~Machine learning Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. ECCE 2019, September 10-13, 2019, BELFAST, United Kingdom © 2019 Association for Computing Machinery. ACM ISBN 978-1-4503-7166-7/19/09...$15.00 https://doi.org/10.1145/3335082.3335125

UX of AI & PersonalizationResearch Papers

Artificial Intelligence (AI) for User Experience (UX) design: A systematic literature review and future reseaarch agendaAsne Stige · 2018Purpose The aim of this article is to map the use of AI in the user experience (UX) design process. Disrupting the UX process by introducing novel digital tools such as Artificial Intelligence (AI) has the potential to improve efficiency and accuracy, while creating more innovative and creative solutions. Thus, understanding how AI can be leveraged for UX has important research and practical implications. Design/Methodology/Approach This article builds on a systematic literature review approach and aims to understand how AI is used in UX design today, as well as uncover some prominent themes for future research. Through a process of selection and filtering, 46 research articles are analysed, with findings synthesized based on a user-centred design and development process. Findings Our analysis shows how AI is leveraged in the UX design process at different key areas. Namely, these include understanding the context of use, uncovering user requirements, aiding solution design, and evaluating design, and for assisting development of solutions. We also highlight the ways in which AI is changing the UX design process through illustrative examples. Originality/value While there is increased interest in the use of AI in organizations, there is still limited work on how AI can be introduced into processes that depend heavily on human creativity and input. Thus, we show the ways in which AI can enhance such activities and assume tasks that have been typically performed by humans.

UX of AI & PersonalizationResearch Papers

Explanation in artificial intelligence: Insights from the social sciencesTim Miller · 2018Article history: Received 22 June 2017 Received in revised form 17 May 2018 Accepted 16 July 2018 Available online 27 October 2018

UX of AI & PersonalizationResearch Papers

A systematic review and taxonomy of explanations in decision support and recommender systemsIngrid Nunes · 2017With the recent advances in the field of artificial intelligence, an increasing number of decision-making tasks are delegated to software systems. A key requirement for the success and adoption of such systems is that users must trust system choices or even fully automated decisions. To achieve this, explanation facilities have been widely investigated as a means of establishing trust in these systems since the early years of expert systems. With today’s increasingly sophisticated machine learning algorithms, new challenges in the context of explanations, accountability, and trust towards such systems constantly arise. In this work, we systematically review the literature on explanations in advice-giving systems. This is a family of systems that includes recommender systems, which is one of the most successful classes of advice- giving software in practice. We investigate the purposes of explanations as well as how they are generated, presented to users, and evaluated. As a result, we derive a novel comprehensive taxonomy of aspects to be considered when designing explanation facilities for current and future decision support systems. The taxonomy includes a variety of different facets, such as explanation objective, responsiveness, content and presentation. Moreover, we identified several challenges that remain unaddressed so far, for example related to fine-grained issues associated with the presentation of explanations and how explanation facilities are evaluated. B Ingrid Nunes ingridnunes@inf.ufrgs.br Dietmar Jannach dietmar.jannach@tu-dortmund.de 1 Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil 2 TU Dortmund, Dortmund, Germany 123 394 I. Nunes, D. Jannach

UX of AI & PersonalizationResearch Papers

Developing Emotion-Aware, Advanced Learning Technologies: A Taxonomy of Approaches and FeaturesClaude Frasson, Nathan C. Hall · 2016A growing body of work on intelligent tutoring systems, affective computing, and artificial intelligence in education is exploring creative, technology-driven ap- proaches to enhance learners’ experience of adaptive, positively-valenced emotions while interacting with advanced learning technologies. Despite this, there has been no published work to date that captures this topic’s breadth. We took up this grand challenge by integrating related empirical studies and existing conceptual work and proposing a theoretically-guided taxonomy for the development and improvement of emotion-aware systems. In particular, multiple strategies system developers may use to help learners experience positive emotions are mapped out, including those that require different amounts and types of information about the user, as well as when this information is required. Examples from the literature are provided to illustrate how different emotion- aware system approaches can be combined to take advantage of different types of data, both prior to and during the learner-system interaction. High-level system features that emotion-aware systems can tailor to learners in order to elicit positive emotions are also described and exemplified. Theoretically, the taxonomy is primarily informed by the control-value theory of achievement emotions (Pekrun 2006, 2011) and its assumptions about the relationship between distal and proximal antecedents and the elicitation and Int J Artif Intell Educ (2017) 27:268–297 DOI 10.1007/s40593-016-0126-8 Note. This manuscript is based on an extended version of: Harley, J. M., Lajoie, S. P., Frasson, C., & Hall, N.C. (2015a). An integrated emotion-aware framework for intelligent tutoring systems. In C. Conati & N. Heffernan (Eds.), Lectures Notes in Artificial Intelligence: Vol. 9112. Artificial Intelligence in Education (pp. 620-624). Switzerland: Springer. * Jason M. Harley jharley1@ualberta.ca 1 Educational Psychology, University of Alberta, 6-102 Education North, Edmonton, AB T6G 2G5, Canada 2 Educational and Counselling Psychology, McGill University, 3700 McTavish Street 614, Montréal, QC H3A 1Y2, Canada 3 Computer Science and Operations Research, Université de Montréal, 2920 Chemin de la Tour, Pavillon André-Aisenstadt 2194, Montréal, QC H3C 3J7, Canada regulation of emotion. The taxonomy expands upon a dichotomy of emotion-aware systems proposed by D’Mello and Graesser (2015) and is intended to guide the design of emotion-aware systems that can fos

UX of AI & PersonalizationResearch Papers

UX Research on Conversational Human AI interaction - A Literature Review of the ACM Digital LibraryQingxiao Zheng · 2013Early conversational agents (CAs) focused on dyadic human-AI interaction between humans and the CAs, followed by the increasing popularity of polyadic human-AI interaction, in which CAs are designed to mediate human-human interactions. CAs for polyadic interactions are unique because they encompass hybrid social interactions, i.e., human-CA, human-to-human, and human-to- group behaviors. However, research on polyadic CAs is scattered across different fields, making it challenging to identify, compare, and accumulate existing knowledge. To promote the future design of CA systems, we conducted a literature review of ACM publications and identified a set of works that conducted UX (user experience) research. We qualitatively synthesized the effects of polyadic CAs into four aspects of human-human interactions, i.e., communication, engagement, connection, and relationship maintenance. Through a mixed-method analysis of the selected polyadic and dyadic CA studies, we developed a suite of evaluation measurements on the effects. Our findings show that designing with social boundaries, such as privacy, disclosure, and identification, is crucial for ethical polyadic CAs. Future research should also advance usability testing methods and trust-building guidelines for conversational AI.

UX of AI & PersonalizationResearch Papers

User experience evaluation methods: Current state and development needsArnold P.O.S. Vermeeren, Effie Lai-Chong Law, Virpi Roto, Marianna Obrist, Jettie Hoonhout, Kaisa Väänänen-Vainio-Mattila · 2010The recent shift of emphasis to user experience (UX) has rendered it a central focus of product design and evaluation. A multitude of methods for UX design and evaluation exist, but a clear overview of the current state of the available UX evaluation methods is missing. This is partly due to a lack of agreement on the essential characteristics of UX. In this paper, we present the results of our multi-year effort of collecting UX evaluation methods from academia and industry with different approaches such as literature review, workshops, Special Interest Groups sessions and an online survey. We have collected 96 methods and analyzed them, among other criteria, based on the product development phase and the studied period of experience. Our analysis reveals development needs for UX evaluation methods, such as early-stage methods, methods for social and collaborative UX evaluation, establishing practicability and scientific quality, and a deeper understanding of UX. Author Keywords User Experience, Evaluation method, Methodological development needs ACM Classification Keywords H5.2. User Interfaces (D.2.2, H.1.2, I.3.6): Evaluation/methodology

UX of AI & PersonalizationResearch Papers

Research Through Design as a Method for InteractionJohn Zimmerman, Jodi Forlizzi et al. · 2007For years the HCI community has struggled to integrate design in research and practice. While design has gained a strong foothold in practice, it has had much less impact on the HCI research community. In this paper we propose a new model for interaction design research within HCI. Following a research through design approach, designers produce novel integrations of HCI research in an attempt to make the right thing: a product that transforms the world from its current state to a preferred state. This model allows interaction designers to make research contributions based on their strength in addressing under-constrained problems. To formalize this model, we provide a set of four lenses for evaluating the research contribution and a set of three examples to illustrate the benefits of this type of research. Author Keywords design, interaction design, interaction design research, HCI research, research through design, wicked problems, design theory, design method ACM Classification Keywords H5.2. User Interfaces: Theory and methods.

UX of AI & PersonalizationResearch Papers

Review of eye tracking metrics involved in emotional and cognitive processesVasileios Skaramagkas, Giorgos Giannakakis et al.Eye behaviour provides valuable information reveal- ing one’s higher cognitive functions and state of affect. Although eye tracking is gaining ground in the research community, it is not yet a popular approach for the detection of emotional and cognitive states. In this paper, we present a review of eye and pupil tracking related metrics (such as gaze, fixations, saccades, blinks, pupil size variation, etc.) utilized towards the detection of emotional and cognitive processes, focusing on visual attention, emotional arousal and cognitive workload. Besides, we investigate their involvement as well as the computational recognition meth- ods employed for the reliable emotional and cognitive assessment. The eye-tracking publicly available datasets employed in relevant research efforts were concentrated and described their specifi- cations and details. The multimodal approaches which combine eye-tracking features with other modalities (e.g. biosignals), along with artificial intelligence and machine learning techniques were also surveyed in terms of their recognition/classification accuracy. The limitations, current open research problems and prospective future research directions were discussed for the usage of eye- tracking as the primary sensor modality. This study aims to comprehensively present the most robust and significant eye/pupil metrics based on available literature towards the development of a robust emotional or cognitive computational model. Index Terms—eye tracking, gaze, pupil, fixations, saccades, smooth pursuit, blinks, stress, visual attention, emotional arousal, cognitive workload, emotional arousal datasets, cognitive work- load datasets Vasileios Skaramagkas, Giorgos Giannakakis, Emmanouil Ktistakis, Dim- itris Manousos, Ioannis Karatzanis are with the Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH), GR-700 13 Heraklion, Crete, Greece (Email: vskaramag@ics.forth.gr, ggian@ics.forth.gr, mandim@ics.forth.gr, karatzan@ics.forth.gr) Giorgos Giannakakis is with the Institute of AgriFood and Life Sciences, University Research Centre, Hellenic Mediterranean University, Heraklion, Greece. Emmanouil Ktistakis is with the Institute of Computer Science, Foundation for Research and Technology Hellas (FORTH) and the Laboratory of Optics and Vision, School of Medicine, University of Crete, Heraklion, Greece (Email: mankti@ics.forth.gr) Nikolaos S. Tachos and Evanthia E. Tripoliti, are with the Department of Biomedical Rese

Emotional DesignResearch Papers

Review The Cognitive-Emotional Design and Study of Architectural Space: A Scoping Review of Neuroarchitecture and Its Precursor ApproachesJuan Luis Higuera-Trujillo · 2021Humans respond cognitively and emotionally to the built environment. The modern possibility of recording the neural activity of subjects during exposure to environmental situations, using neuroscientific techniques and virtual reality, provides a promising framework for future design and studies of the built environment. The discipline derived is termed “neuroarchitecture”. Given neuroarchitecture’s transdisciplinary nature, it progresses needs to be reviewed in a contextualised way, together with its precursor approaches. The present article presents a scoping review, which maps out the broad areas on which the new discipline is based. The limitations, controversies, benefits, impact on the professional sectors involved, and potential of neuroarchitecture and its precursors’ approaches are critically addressed.

Emotional DesignResearch Papers

A review of immersive virtual reality serious games to enhance learning and trainingDavid Checa, Andres Bustillo · 2020The merger of game-based approaches and Virtual Reality (VR) environments that can enhance learning and training methodologies have a very promising future, reinforced by the widespread market-availability of affordable software and hardware tools for VR-environ- ments. Rather than passive observers, users engage in those learning environments as active participants, permitting the development of exploration-based learning paradigms. There are separate reviews of VR technologies and serious games for educational and training purposes with a focus on only one knowledge area. However, this review covers 135 proposals for serious games in immersive VR-environments that are combinations of both VR and serious games and that offer end-user validation. First, an analysis of the forum, nationality, and date of publication of the articles is conducted. Then, the application domains, the target audience, the design of the game and its technological implementation, the performance evaluation proce- dure, and the results are analyzed. The aim here is to identify the factual standards of the proposed solutions and the differences between training and learning applications. Finally, the study lays the basis for future research lines that will develop serious games in immersive VR- environments, providing recommendations for the improvement of these tools and their successful application for the enhancement of both learning and training tasks.

Emotional DesignResearch Papers

Drivers of Consumers' Emotional Engagement with Everyday Products: An Intensive Review of the Literature and an Attempt to Conceptualize the Consumer-Product Interactions Within the Emotional Design Process2017....................................................................................................................................................... iii

Emotional DesignResearch Papers

Emotion detection: a technology review2017Emotion detection has become one of the most important aspects to consider in any project related to Affective Computing. Due to the almost endless applications of this new discipline, the development of emotion detection technologies has brought up as a quite profitable opportunity in the corporate sector. Many start-up enterprises have emerged in the last years, dedicated almost exclusively to a specific type of emotion detection technology. In this paper, we present a thorough review of current technologies to detect human emotions. To this end, we explore the different sources from which emotions can be read, along with existing technologies developed to recognize them. We also explore some application domains in which this technology has been applied. This survey has let us identify the strengths and shortcomings of current technology for emotion detection. We conclude the survey highlighting the aspects that requires further research and development. CCS CONCEPTS • Human-Centered Computing → Interaction Design.

Emotional DesignResearch Papers

Unconscious Human Behavior at Visceral Level of Emotional Design2013In the near future, the emphasis on product design innovation will be on finding a fit between technology and human values. However, there is still a limited discussion available on the unconscious human behaviour as well as inadequate literature related to the visceral level of emotional design. The purpose of this study is to manipulate the respect to the emotional design, as well as the direction for the development of innovative product design. © 2013 Published by Elsevier Ltd. Selection and peer-review under responsibility of the Centre for Environment- Behaviour Studies (cE-Bs), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.

Emotional DesignResearch Papers

The Behaviour Change Wheel: a new method for characterising and designing behaviour change interventions2011Background: Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. Methods: A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Results: Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a ‘behaviour system’ involving three essential conditions: capability, opportunity, and motivation (what we term the ‘COM-B system’). This forms the hub of a ‘behaviour change wheel’ (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health’s 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence’s guidance on reducing obesity. Conclusions: Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a ‘behaviour system’ at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions. Background Improving the implementation of evidence-based prac- tice and public health depends on behaviour change. Thus, behaviour change interventions are fundamental to

Emotional DesignResearch Papers

Emotional Design in Human Factors and Ergonomics2010The concept of emotion is closely related to affect, which is an encompassing term and it consists of emotions, feelings, moods, and evaluations (Simon, Clark, & Fiske, 1982). The most important concept is probably emotion. Nevertheless, in psychology, the theories about emotion consider it a 'very confused and confusing field of study' (Ortony, Clore, & Collins, 1988) and thus there is no consensus on a definition. Various factors are associated with emotions, including subjective factors, environmental factors, and neural and hormonal processes. In this chapter, we make use of the summary of emotion provided by Kleinginna and Kleinginna (1981), which incorporates the key elements of definitions in psychology as follows: (1) Emotions give rise to affective experience, such as pleasure or displeasure. (2) Emotions stimulate us to generate cognitive explanations to attribute the cause to ourselves or to the environment, for example. (3) Emotions trigger a variety of internal adjustments in the autonomic nervous system, such as an increased heart rate and a decreased skin conductance response. (4) Emotions elicit behaviors that are often, but not always, expressive (laughing or crying), goal-directed (approaching or avoiding), and adaptive (removal of a potential threat).

Emotional DesignResearch Papers

The focus of UX research is to design and develop systems that must support usability and user’s affective needs and goals[10-11]. UX research has gained more interest due to limitations of the conventional usability models [4]. UX studies do not only focus on task related aspects but also on affective qualities, sensation, meaning and value of interactive systems, products and services [12-14]. In order to better understand the concept of UX, many frameworks and models are proposed e.g. [11, 14, 15] that include various integrated UX constructs and measures. These frameworks are presented from different perspectives that include interaction-centered, user-centered and system-centered [16, 17]. It is also focused to understand and document different types of experience created while interacting with systems. Experience is described as a constant stream of “self-talk” that occurs while interaction is carried out with products e.g. using instant messaging systems. An experience is described as something that can be articulated e.g. watching a movie and sitting on free fall ride. Co-experience is described as the motions and meanings created together while interacting with products e.g. playing mobile messaging games with friends. UX can be created either positive or negative depending on systems qualities perceived by users [18-20]. It introduces a valid point of interest to research that how positive UX of interactive systems can be created, measured and modeled [19]. Thus, UX is being studied extensively in HCI field to design systems to be more useful, pleasant and attractive [14, 18]. Despite the availability of different frameworks and models, there is still no consensus on the definition of UX [3, 10, 21]. It is argued that UX encompasses various integrated aspects and shares diverse views. The wider scope and incoherent views on UX make it more complex [4, 10]. It presents many challenges such as selecting and validating the core constructs, factors and relevant2006In recent years, the notion of User Experience (UX) has gained a greater attention among HCI researchers in academia and industry. Due to its importance, several frameworks and models have been proposed to design and assess UX of interactive systems. These models guide to improve the design and help to determine the quality of interactive systems, products and services. UX is highly subjective, dynamic, and context dependent; it evolves during the interaction with the system. Different factors collectively influence UX and present a challenging task to define, model, measure and validate it. The less attention is paid to understand and underline these factors; this paper is an attempt to understand and underline the core UX factors based on literature review. These factors make UX more complex, diverse and vague in nature. It is recommended to incorporate the management aspect in UX process that may help to overwhelming the issues of complexity, diversity and vagueness.

Emotional DesignResearch Papers

Design and Emotion: Time for a New Direction?Terence Love · 2004This paper describes research investigating why the extensive effort in Design and Emotion research and publications has not had more significant effect in improving design theory and practice in spite of the large amounts of funding expended, the number of research projects and research centers and the large number of publications. The analyses point to two foundational research issues that appear to have been overlooked and which point to why Design and Emotion research culture is failing to make radical and significant impacts on design theory, design research, design practice and design education across all the major fields of design in the art and design, technical design and other design sectors. The paper concludes with a brief outline of the changes likely to make the Design and Emotion field more effective in improving design outcomes, design practice, design research and design theory. Key words: Design and Emotion, theory failure, design practice failure, cognitive neuroscience.

Emotional DesignResearch Papers

Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI LiteratureShuning Zhang, Hui Wang et al. · 2025As Artificial Intelligence (AI) increasingly becomes an active collaborator in co-creation, understanding the distribution and dynamic of agency is paramount. The Human-Computer Interaction (HCI) perspective is crucial for this analysis, as it uniquely reveals the interaction dynamics and specific control mechanisms that dictate how agency manifests in practice. Despite this importance, a systematic synthesis mapping agency configurations and control mechanisms within the HCI/CSCW literature is lacking. Addressing this gap, we reviewed 134 papers from top-tier HCI/CSCW venues (e.g., CHI, UIST, CSCW) over the past 20 years. This review yields four primary contributions: (1) an integrated theoretical framework structuring agency patterns, control mechanisms, and interaction contexts, (2) a comprehensive operational catalog of control mechanisms detailing how agency is implemented; (3) an actionable cross-context map linking agency configurations to diverse co-creative practices; and (4) grounded implications and guidance for future CSCW research and the design of co-creative systems, addressing aspects like trust and ethics.

HCI & Adaptive InterfacesResearch Papers

Behavioural Intervention Technology in UX Design: Conceptual Review, Synthesis, and Research DirectionYoungsoo Shin, Chajoong Kim et al. · 2021The notion of Behavioural Intervention Technologies (BITs) has received increasing attention from researchers and practitioners creating design and technology to support users' behavioural change processes. However, the value of consolidating previous findings to connect insightful research and practical design works and generating new knowledge on BITs has been under-recognized in the design community. To support researchers and practitioners who struggle with creating humancentred BITs to effectively induce changes in human behaviour, this paper investigates existing literature on BITs through a systematic literature review with 28 selected publications. From this literature review process, this paper proposes a structured synthesis of extant perspectives and approaches, offering an overarching perspective for effective applications of the BIT design approach. At the end of the paper, these findings are extended to discuss further research and implementations of design practices for changes in human behaviours.

HCI & Adaptive InterfacesResearch Papers

Towards Augmented Reality-driven Human-City Interaction: Current Research on Mobile Headsets and Future ChallengesLik-Hang Lee · 2021Interaction design for Augmented Reality (AR) is gaining increasing attention from both academia and industry. This survey discusses 260 articles (68.8% of articles published between 2015 – 2019) to review the field of human interaction in connected cities with emphasis on augmented reality-driven interaction. We provide an overview of Human-City Interaction and related technological approaches, followed by reviewing the latest trends of information visualization, constrained interfaces, and embodied interaction for AR headsets. We highlight under-explored issues in interface design and input techniques that warrant further research, and conjecture that AR with complementary Conversational User Interfaces (CUIs) is a crucial enabler for ubiquitous interaction with immersive systems in smart cities. Our work helps researchers understand the current potential and future needs of AR in Human-City Interaction.

HCI & Adaptive InterfacesResearch Papers

Computer Science ReviewMaaruf Ali, Peter S. Excell · 2021A review of research on universal usability, plasticity of user interface design and facilitation of interface development with universal usability is presented. The survey was based on 165 research papers spanning over fifty-five years. The foundations of adaptive or intelligent user interfaces (AUI or IUI) are presented, three core domains being focused upon: Artificial Intelligence (AI), User Modelling (UM) and Human–Computer Interaction (HCI). For comparison of the various AUIs, a proposed taxonomy is given. One conclusion is that an efficient training vector for fast optimal convergence of the machine-learning algorithm is a necessity, but key to this is the bounding of the dataset, the goal being to achieve an accurate user preference model, which has to be built from a limited number of datasets obtained from the human interaction. More research also needs to be conducted to ascertain the usefulness and effectiveness of IUIs compared against AUIs. With the global mobility of users, interface design must take account of the abilities and cultures of users, derived from actual user behaviour and not on their feedback. A key question is whether the interface should be adaptive under system control or be made adaptable under user control. A need is identified for an ‘‘afferential component’’ that stores a priori information about the end user, an ‘‘inferential component’’ that determines to what extent the user interface actually needs to be adapted, and the ‘‘efferential component’’ that actually determines how the adaptivity is applied seamlessly to the system. Application to e-learning is a priority: the use of machine intelligence to achieve appropriate learnability, ideally enhanced by ‘‘Playful interaction’’, was found to be desirable. Universal application of adaptation lies in the future, but AUI properties cannot be ascertained while disregarding the other parameters of the system in which it will be used. A more complete understanding of the human mental model is necessary, requiring a highly multidisciplinary approach and cooperation between diverse researchers. Finally, a performance evaluation of plasticity of user interface was conducted: it is concluded that the use of dynamic techniques can enhance the user experience to a much greater extent than more basic approaches, although optimisation of usability parameter trade-offs needs further attention. It is noted that most of the work reviewed originated from a limited range of cultural pe

HCI & Adaptive InterfacesResearch Papers

DESIGN RESEARCH IN THE DIGITAL ERAIlaria Mariani · 2020The Design International series is thus born as a cultural setting for the sharing of ideas and experiences from the different fields of design, a place in which you can discover the wealth and variety of design research, where different hypotheses and different answers present themselves, in an attempt to draw up a map of Italian design, though in a continuous comparison with the world scene.

HCI & Adaptive InterfacesResearch Papers