Filtered by themeAdapting to diverse users28 papersclear ✕

Does personality matter: examining the value of personality insights for personalized nudges that encourage the selection of learning resourcesCardenas Canto, dimitrova · 2024© 2024 Cardenas Canto, Dimitrova, Sherman and Flint. This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

UX of AI & PersonalizationResearch Papers

Article Functional Framework for Multivariant E-Commerce User InterfacesAdam Wasilewski · 2024Modern e-businesses heavily rely on advanced data analytics for product recommendations. However, there are still untapped opportunities to enhance user interfaces. Currently, online stores offer a single-page version to all customers, overlooking individual characteristics. This paper aims to identify the essential components and present a framework for enabling multiple e-commerce user interfaces. It also seeks to address challenges associated with personalized e-commerce user interfaces. The methodology includes detailing the framework for serving diverse e-commerce user interfaces and presenting pilot implementation results. Key components, particularly the role of algorithms in personalizing the user experience, are outlined. The results demonstrate promising outcomes for the implementation of the pilot solution, which caters to various e-commerce user interfaces. User characteristics support multivariant websites, with algorithms facilitating continuous learning. Newly proposed metrics effectively measure changes in user behavior resulting from different interface deployments. This paper underscores the central role of personalized e-commerce user interfaces in optimizing online store efficiency. The framework, supported by machine learning algorithms, showcases the feasibility and benefits of different page versions. The identified components, challenges, and proposed metrics contribute to a comprehensive solution and set the stage for further development of personalized e-commerce interfaces.

UX of AI & PersonalizationResearch Papers

User Characteristics in Explainable AI: The Rabbit Hole of Personalization?Robert Nimmo · 2024As Artificial Intelligence (AI) becomes ubiquitous, the need for Ex­ plainable AI (XAI) has become critical for transparency and trust among users. A significant challenge in XAI is catering to diverse users, such as data scientists, domain experts, and end-users. Recent research has started to investigate how users’ characteristics impact interactions with and user experience of explanations, with a view to personalizing XAI. However, are we heading down a rabbit hole by focusing on unimportant details? Our research aimed to investi­ gate how user characteristics are related to using, understanding, and trusting an AI system that provides explanations. Our empirical study with 149 participants who interacted with an XAI system that flagged inappropriate comments showed that very few user characteristics mattered; only age and the personality trait open­ ness influenced actual understanding. Our work provides evidence to reorient user-focused XAI research and question the pursuit of personalized XAI based on fine-grained user characteristics. Disclaimer: This paper contains examples of language that some people may find offensive. CCS CONCEPTS • Human-centered computing → Empirical studies in HCI; Interactive systems and tools; • Computing methodologies → Machine learning.

UX of AI & PersonalizationResearch Papers

One Size Does Not Fit All: Multivariant User Interface Personalization in E-CommerceAdam Wasilewski · 2024One of the most visible manifestations of the changes brought about by the digitization of everyday life is undoubtedly the spread of electronic commerce. It is difficult to think of the digital economy without considering transactions through electronic channels. In turn, the user interface (UI) is the key to e- commerce, as it is usually the first and primary point of contact between business and consumer. A key trend in e-commerce is the personalization of communications, which can improve the user experience, increase customer satisfaction and deliver tangible business benefits. Today, it is technically possible to base this personalization on an analysis of user behavior using artificial intelligence and machine learning techniques. A common form of personalization in e-commerce is the use of product recommendation systems, but the user interface can be tailored much more extensively. The approach described and discussed in this paper is a multivariant user interface that allows the layout to be tailored to the characteristics, attributes, and behaviors of customer groups generated using machine learning techniques. The results of the research carried out make it possible to verify the practicality of the proposed solution and provide an opportunity to identify development directions that take into account the potential of artificial intelligence. The application of the concept described in the paper is broad, covering all aspects of e-commerce design that require compromises when serving a single UI variant, but allow flexibility and customization for different users when serving a multivariant UI. INDEX TERMS Artificial intelligence, e-commerce, machine learning, personalization, user interface.

UX of AI & PersonalizationResearch Papers

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.

UX of AI & PersonalizationResearch Papers

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.

UX of AI & PersonalizationResearch Papers

Visual, textual or hybrid: the effect of user expertise on different explanationsMaxwell Szymanski · 2021As the use of AI algorithms keeps rising continuously, so does the need for their transparency and accountability. However, literature often adopts a one-size-fits-all approach for developing explana- tions when in practice, the type of explanations needed depends on the type of end-user. This research will look at user expertise as a variable to see how different levels of expertise influence the under- standing of explanations. The first iteration consists of developing two common types of explanations (visual and textual explana- tions) that explain predictions made by a general class of predictive model learners. These explanations are then evaluated by users of different expertise backgrounds to compare the understanding and ease-of-use of each type of explanation with respect to the different expertise groups. Results show strong differences between experts and lay users when using visual and textual explanations, as well as lay users having a preference for visual explanations which they perform significantly worse with. To solve this problem, the second iteration of this research focuses on the shortcomings of the first two explanations and tries to minimize the difference in understanding between both expertise groups. This is done through the means of developing and testing a candidate solution in the form of hybrid explanations, which essentially combine both visual and textual explanations. This hybrid form of explanations shows a significant improvement in terms of correct understanding (for lay users in particular) when compared to visual explanations, whilst not compromising on ease-of-use at the same time. CCS CONCEPTS • Human-centered computing →Empirical studies in visualiza- tion; User studies; User models; • Information systems →De- cision support systems; • Computing methodologies →Arti- ficial intelligence.

UX of AI & PersonalizationResearch Papers

User Context Ontology for Adaptive Mobile-Phone InterfacesReceived June · 2021The Adaptive User Interface (AUI) adapts to the changes in the context of use and provides improved interaction abilities for different users. The adaptivity in the user interfaces requires in depth knowledge of context. There is a need to enrich user profiles to achieve the personalized services with the ability to adapt the user’s context. The context can be reflected in a particular kind of knowledge and hence modeled as ontology. Ontology based context models are effective means to handle complex situations that support the sharing or integration of context information. This paper presents ontology based context model using OWL for adaptive mobile devices. It models the context over its four major elements including device, user, environment (location and time) and activity. The proposed ontology was derived in different classes, relationships, associations, dependencies and constraints to model dynamic context. Ontologies present a standardized, consistent and shareable context model. The context model and consequent context snapshots can be acknowledged by AUI to present a suitable user interface. The ontology was developed using Protégé on the basis of each context type having different values. Semantic querying (SPARQL) was used for knowledge acquisition. Moreover, the Pellet and HermiT Reasoner were used to verify the rules, relations and constraints to avoid the inconsistency between classes. Comparative to other context models for adaptive interfaces, ontological model provides more of scalability and growth with learning new context in to the shared context knowledge. INDEX TERMS Adaptive user interface, context aware interface, ontology driven interfaces, knowledge representation, knowledge engineering.

UX of AI & PersonalizationResearch Papers

PRIME: A Personalized Recommender System for Information Visualization Methods via Extended Matrix CompletionChen, Lau · 2021Adapting user interface designs for specific tasks performed by different users is a challenging yet important problem. Automatically adapting visualization designs to users and contexts (e.g., tasks, display devices, environments, etc.) can theoretically improve human–computer interaction to acquire insights from complex datasets. However, effectiveness of any specific visualization is moderated by individual differences in knowledge, skills, and abilities for different contexts. A modeling framework called Personalized Recommender System for Information visualization Methods via Extended matrix completion (PRIME) is proposed for recommending the optimal visualization designs for individual users in different contexts. PRIME quantitatively models covariates (e.g., psychological and behavioral measurements) to predict recommendation scores (e.g., perceived complexity, mental workload, etc.) for users to adapt the visualization specific to the context. An evaluation study was conducted and showed that PRIME can achieve satisfactory recommendation accuracy for adapting visualization, even when there are limited historical data. PRIME can make accurate recommendations even for new users or new tasks based on historical wearable sensor signals and recommendation scores. This capability contributes to designing a new generation of visualization systems that will adapt to users' states. PRIME can support researchers in reducing the sample size requirements to quantify individual differences, and practitioners in adapting visualizations according to user states and contexts.

UX of AI & PersonalizationResearch Papers

A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendationsPipat Thontirawong b, Punjaporn Chinchanachokchai c · 2021Recommender systems are used in e-Commerce websites to make product recommendations or deliver person­ alized content to users. We constructed a beer recommendation program using review data from existing online community to test the hypotheses. This research aims to bridge the gap between marketing and computer science by investigating the moderating effects of consumer knowledge (expertise) on the performance and evaluation of two widely-used recommendation systems – user-based collaborative filtering and content-based. The results show that expert consumers prefer user-based collaborative filtering systems, whereas there is no difference between the two systems among novice consumers. Theoretical and managerial implications are discussed.

UX of AI & PersonalizationResearch Papers

User interface design patterns and ontology models for adaptive mobile applications2020Mobile applications are an essential element in pervasive and ubiquitous computing, and they face many challenges during their generation process from the analysis of user needs to the design of specific mobile interfaces and their development in several technological platforms. Moreover, the rise of Ambient Intelligent and context-aware environments also introduces multiple interaction aspects to be considered when using mobile devices in this kind of scenarios. The present work seeks to examine the role of design patterns and ontology models in order to help with the generation of mobile applications, which can be adapted at runtime to the various user needs, different context scenarios, interactive design modes, or technology requirements. In this way, an ontology-based framework is introduced to represent, design, and support the adaptation of user interfaces in mobile appli- cations by using design patterns according to these user needs or preferences and the context around them. This framework provides developers with a client-server architecture that enables the access to an expert knowledge base of user, context, and pattern information together with a set of inference rules, which allow the dynamic selection of interface design patterns and the runtime adaptation of the user interface features. These ontology models and inference rules are key components of the proposed framework, and their implementation has helped to produce an example of mobile application supporting user interface adap- tation processes for disabled people, which can be required in Ambient Intelligent environments. Three examples of user scenarios have been considered to assess the framework potential, and usability dimensions have been tested by a limited set of users through the produced mobile application, making the usefulness of generated adaptive user interfaces apparent.

UX of AI & PersonalizationResearch Papers

Integrated model-driven development of self-adaptive user interfacesEnes Yigitbas · 2019Modern user interfaces (UIs) are increasingly expected to be plastic, in the sense that they retain a constant level of usability, even when subjected to context changes at runtime. Self-adaptive user interfaces (SAUIs) have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. The development of SAUIs is a challenging and complex task as additional aspects like context management and UI adaptation have to be covered. In classical model-driven UI development approaches, these aspects are not fully integrated and hence introduce additional complexity as they represent crosscutting concerns. In this paper, we present an integrated model-driven development approach where a classical model-driven development of UIs is coupled with a model-driven development of context-of-use and UI adaptation rules. We base our approach on the core UI modeling language IFML and introduce new modeling languages for context- of-use (ContextML) and UI adaptation rules (AdaptML). The generated UI code, based on the IFML model, is coupled with the context and adaptation services, generated from the ContextML and AdaptML model, respectively. The integration of the generated artifacts, namely UI code, context, and adaptation services in an overall rule-based execution environment, enables runtime UI adaptation. The benefit of our approach is demonstrated by two case studies, showing the development of SAUIs for different application scenarios and a usability study which has been conducted to analyze end-user satisfaction of SAUIs.

UX of AI & PersonalizationResearch Papers

To Explain or not to Explain: the Effects of Personal Characteristics when Explaining Music RecommendationsMartijn Millecamp · 2019Recommender systems have been increasingly used in online services that we consume daily, such as Facebook, Netflix, YouTube, and Spotify. However, these systems are often pre- sented to users as a “black box”, i.e. the rational for providing individual recommendations remains unexplained to users. In recent years, various attempts have been made to address this black box issue by providing textual explanations or interac- tive visualisations that enable users to explore the provenance of recommendations, and benefits in terms of precision and user satisfaction, among others, have been demonstrated. Pre- vious research had also indicated that personal characteristics such as domain knowledge, trust propensity and persistence may also play an important role on such perceived benefits. Yet, to date, little is known about the effects of personal char- acteristics when explaining recommendations. To address this gap, we developed a music recommender system with expla- nations and conducted an online study using a within-subject design. We captured various personal characteristics of par- ticipants and administered both qualitative and quantitative evaluation methods. Results indicated that personal character- istics have some significant influence on the interaction and perception of recommender systems and that this influence changes by adding explanations. Especially people with a low need for cognition benefited from explained recommendations. For people with a high need for cognition, we observed that explanations could lower their confidence. Based on these re- sults, we present some first design implications for explaining recommendations. 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 the author(s) 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. IUI ’19, © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. ISBN 123-4567-24-567/08/06...$15.00 DOI: http://dx.doi.org/10.475/123_4 ACM Classification Keywords H.5.2 Information Interfaces and Presentation (e.g. HCI): User-cen

UX of AI & PersonalizationResearch Papers

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.

UX of AI & PersonalizationResearch Papers

Towards incorporating personality into the design of an interface: a method for facilitating users' interaction with the displaySamer Muthana Sarsam, Hosam Al-Samarraie · 2018A novel user interface (UI) design based on the personality characteristics of users was proposed and examined in a mobile learning context. It was argued that differences in personality can stimulate individuals’ information processing capabili- ties in according to their display preferences, thus an effective visual experience. The personality characteristics and design preferences of 87 students (37 male, and 50 female) were collected and analysed. The clustering result (using k-means algorithm) revealed two potential personality types, which we call the neuroticism and the extra- conscientiousness groups. Then, an interface was designed for each personality group using the association rules method. An eye-tracking device was used to record changes in participants’ eye-pupil diameter and fixation duration, and thus examine their cogni- tive load and attention. The participants’ eye movement data of each group showed that their visual experience was significantly improved when using the interface designed based on their personality characteristics. This work offers some important design and practical insights to the human–computer interaction and the design of mobile device UI.

UX of AI & PersonalizationResearch Papers

Rule based adaptive user interface for adaptive E-learning systemManohara Pai M. M. · 2018The term Adaptive E-learning System (AES) refers to the set of techniques and approaches that are combined together to offer online courses to the learners with the aim of providing customized resources and interfaces. Most of these systems focus on adaptive contents which are generated to the learners without considering the learning styles of the learners. Learning style of the learner defines the way of learning the contents. The system should not only meet the individual need of the contents but also the customized user interface on the portal. Hence, an AES should mainly focus on recommending learning contents with Adaptive User Interface (AUI) on the portal. The work in the paper proposes a generic approach to provide the learning contents with AUI components based on the learning styles of the learners. The learning style adopted for the work is the Felder-Silverman Learning Style Model (FSLSM). The proposed approach defines generic rules which are generated automatically for any online course with the adaptive contents. Also, the approach takes care of new learners by providing learning path as a user interface component on the portal. The experiment has been conducted on engineering students for a particular online course. The portal is validated using parameters of usability testing by generating test cases and statistical analysis has been carried out to identify the impact of AUI components on the learning process. The result shows the well adaptation of user interface components and contents based on learning styles.

UX of AI & PersonalizationResearch Papers

The Influence of Personality Traits and Cognitive Load on the Use of Adaptive User InterfacesHarvard SEAS · 2017One of the problems adaptive interfaces must solve is the is- sue of stability—users must be able to complete a familiar task reliably. Split Adaptive Interfaces, where a limited part of the screen contains copies of the interface elements pre- dicted to be of immediate use, are one technique for resolv- ing this difficulty. While prior work demonstrated that Split Adaptive Interfaces improve performance on average, the re- sults of our study demonstrate systematic individual differ- ences in the utilization of the adaptive features, which cor- relate with the stable user traits of Need for Cognition and Extraversion. Specifically, higher Need for Cognition (a will- ingness to undertake difficult mental activities) is correlated with increased utilization rates, while higher Extraversion (a general orientation towards seeking gratification from the ex- ternal world) is negatively correlated with utilization rates. Our results also demonstrate a significant negative correlation between cognitive load induced by a secondary task and the utilization of the adaptive features. This effect, however, is very small (less than two percentage points). Together, these results provide additional evidence of the usefulness of the split adaptive interface approach and a negligible effect of ad- ditional cognitive load, but also demonstrate that the approach does not benefit all users equally. Author Keywords Adaptive user interfaces, cognitive load, extraversion, need for cognition ACM Classification Keywords H.5.m. Information Interfaces and Presentation: Miscella- neous

UX of AI & PersonalizationResearch Papers

Towards a Human-centered E-Commerce Personalization FrameworkMarios Belk · 2015This paper presents a personalization framework, namely PersonaWeb that adapts the visual and interaction design of E-Commerce Web environments based on human cognitive differences. In particular, it describes a user model formalization that incorporates a set of human cognitive factors (i.e., cognitive styles and working memory capacity) and an adaptation engine that personalizes the visual and interaction design attributes of E-Commerce product views. The proposed framework has been applied in a real-life E-Commerce Web-site and two subsequent user studies were conducted in which 135 users interacted with the personalized and the original (non-personalized) version of the same Web environment. Results indicate the added value of personalizing content and functionality of E-Commerce product views in terms of users’ task completion performance.

UX of AI & PersonalizationResearch Papers

CONSUMER ACCEPTANCE AND USE OF INFORMATION TECHNOLOGY: EXTENDING THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGYViswanath Venkatesh · 2012This paper extends the unified theory of acceptance and use of technology (UTAUT) to study acceptance and use of technology in a consumer context. Our proposed UTAUT2 incorporates three constructs into UTAUT: hedonic motivation, price value, and habit. Individual differences—namely, age, gender, and experience—are hypothesized to moderate the effects of these constructs on behavioral intention and technology use. Results from a two-stage online survey, with technology use data collected four months after the first survey, of 1,512 mobile Internet consumers supported our model. Compared to UTAUT, the extensions proposed in UTAUT2 produced a substantial improvement in the variance explained in behavioral intention (56 percent to 74 percent) and technology use (40 percent to 52 percent). The theoretical and managerial implications of these results are discussed.

UX of AI & PersonalizationResearch Papers

Emotional Design in Multimedia Learning: How Emotional Intelligence Moderates Learning OutcomesJeya Amanth · 2016This study is designed as a preliminary study to explore the effects of emotional intelligence (EI) on achievement, perceived intrinsic motivation and perceived satisfaction when expose to an emotional designed Multimedia Learning Environment (MLE) that was designed to induce either positive, neutral or negative emotions. All three designs had similar content and narration but differed in visual element such as colour, font size, font style and images. Based on the findings, it was reported that students performed better in the design used to induce negative emotion (NegD design) followed by the positive (PosD) and Neutral (NeuD). There is no significant difference in levels of emotional intelligence towards these learning outcomes; however, students with Low EI performed better overall. EI only qualified perceived satisfaction when using a MLE designed to induce emotions and it was found that students with Low EI preferred the design that induces positive emotions. In addition, High EI students favored designs with emotionality (positive or negative) compared to neutral design. Index Terms—Emotional Design, Engineering Education, Emotional Intelligence, Multimedia- Based Learning, Aesthetics.

Emotional DesignResearch Papers

Personas and user-centered design: How can personas benefit product design processes?Tomasz Miaskiewicz, Kenneth A. Kozar · 2011This paper investigates personas, an alternative method for representing and communicating customer needs. By using a narrative, picture, and name, a persona provides product designers with a vivid representation of the design target. Numerous benefits of incorporating personas into product design approaches have been suggested, but the present literature fails to identify the most significant and universal advantages of persona use. By incorporating expert opinion through the use of Delphi methodology, this research first examines the benefits of incorporating personas into design processes. After gaining consensus on the perceived importance of the individual benefits, this paper then elaborates on the most significant benefits of persona use and needed future research on the personas method.

Emotional DesignResearch Papers

Towards customized emotional design: An explorative study of user personality and user interface skin preferences2005Two key elements in the area of cognitive ergonomics are user-system performance and the user similarity. However, with the introduction of skinnable user interfaces, a technology that gives the user interface a chameleon-like ability, elements such as aesthetic, fun, and especially user individuality and identity become more important. This paper presents two explorative studies on user personality in relation to skin preferences. In the studies participants were asked to rate their preference of a set of Windows Media Player skins and to complete the BIS/BAS and the IPIP-NEO personality inventories. The results of the first study suggest colour and similarity-attraction as two possible underlying factors for the correlations found between personality traits and skin preferences. The results of the second study partly confirm these findings, however not for similar personality traits and skin types correlations.

Emotional DesignResearch 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

Article Methodologies of Learning Served by Virtual Reality: A Case Study in Urban InterventionsRicardo Torres-Kompen, David Fonsec · 2019A computer-simulated reality and the human-machine interactions facilitated by computer technology and wearable computers may be used as an educational methodology that transforms the way students deal with information. This turns the learning process into a more participative and active process, which fits both the practical part of subjects and the learner’s profile, as students nowadays are more technology-savvy and familiar with current technological advances. This methodology is being used in architectural and urbanism degrees to support the design process and to help students visualize design alternatives in the context of existing environments. This paper proposes the use of virtual reality (VR) as a resource in the teaching of courses that focus on the design of urban spaces. A group of users—composed of architecture students and professionals related to the architecture field—participated in an immersing VR experience and had the opportunity to interact with the space that was being redesigned. Later, a quantitative tool was used in order to evaluate the effectiveness of virtual systems in the design of urban environments. The survey was designed using as a reference the competences required in the urbanism courses; this allowed the authors to identify positive and negative aspects in an objective way. The results prove that VR helps to expand digital abilities in complex representation and helps users in the evaluation and decision-making processes involved in the design of urban spaces.

HCI & Adaptive InterfacesResearch Papers

Virtual and Augmented Reality in Architectural Design and EducationJulie Milovanovic, Guillaume Moreau et al. · 2017Virtual Reality and Augmented Reality research in the architecture field show a variety of possible uses of systems to accompany designers, laymen and decision makers in their architectural design process. This article provides a survey of VR and AR devices among a corpus of papers selected from conferences and journals on CAAD (Computer Aided Architectural Design). A closer look at some specific research projects highlights their potentials and limits, which formalize milestones for future challenges to address. Identifying advantages and drawbacks of those devices gave us insights to propose an alternative type of system, CORAULIS, including both VR and SAR technologies, in order to support collaborative design to be implemented in a pedagogical environment.

HCI & Adaptive InterfacesResearch Papers

Interactive architectural approach (interactive architecture): An effective and adaptive process for architectural designMojtaba Parsaee, Parinaz Motealleh et al. · 2015This research attempts to offer a new approach for architectural design process that the concepts of interaction and multi-relations are being achieved through it. This approach, which is identified as an interactive architecture, suggests a process that a dynamic and mutual relation will create among all factors and parameters of design and the effects of each factor or parameters on final design will be considered. In fact, the main axis of the suggested approach is comprehensive interaction with all various aspects of design, since the design problems have multi-aspects, mostly. Thus, the final design will be resulted based on these mutual relations and it is a production which will have a maximum and optimum adaption with all factors and parameters. What makes this atti- tude more significant and crucial is the chaotic situation that is produced in architecture and urban designing of most cities especially in developing countries and leads to lack of identity in these cities. So, the interactive approach can be able to eliminate the challenges and create the fields of sustain- able architecture and urban development through an effective method. However, this process encounters to some constraints and challenges along with some potentials which are discussed in this essay. The research method is analytical-interpretative and based on qualitative analyses. ª 2015 The Authors. Production and hosting by Elsevier B.V. on behalf of Housing and Building National Research Center. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

HCI & Adaptive InterfacesResearch Papers

UTOPIA: Participatory Design from Scandinavia to the WorldYngve Sundblad · 2011Studies and design of information technology support for workplaces, especially workshop floors, office floors and hospital floors, have a strong tradition in Scandinavia, involving workplace users and their trade unions and other stakeholders. The projects emphasize the active cooperation between researchers and workers in the organizations to help improve their work situation. This tradition is analyzed in its historic perspective, starting with the roots in Norway in the early 1970s while highlighting the seminal UTOPIA project from the early 1980s. Today computer use and interaction possibilities are changing quickly with use contexts and application types radically broadening. Technology no longer consists of static tools belonging only to the workplace; it permeates work activity, homes, and everyday lives. The Scandinavian tradition of user involvement in development is facing up with the challenges of new contexts. The influence on past and current practices for international ICT system design is described and analyzed.

HCI & Adaptive InterfacesResearch Papers