Towards Emotion-Sensitive Conversational User Interfaces in Healthcare Applications

Perception of emotions and adequate responses are key factors of a successful conversational agent. However, determining emotions in a healthcare setting depends on multiple factors such as context and medical condition. Given the increase of interest in conversational agents integrated in mobile health applications, our objective in this work is to introduce a concept for analyzing emotions and sentiments expressed by a person in a mobile health application with a conversational user interface. The approach bases upon bot technology (Synthetic intelligence markup language) and deep learning for emotion analysis. More specifically, expressions referring to sentiments or emotions are classified along seven categories and three stages of strengths using treebank annotation and recursive neural networks. The classification result is used by the chatbot for selecting an appropriate response. In this way, the concerns of a user can be better addressed. We describe three use cases where the approach could be integrated to make the chatbot emotion-sensitive

Chatbot recommender systems in tourism : a systematic review and a benefit-cost analysis

This research is focused on the utilization of artificially intelligent (AI), customer service chatbots in travel, tourism and hospitality. Rigorous criteria were used to search, screen, extract and synthesize articles on conversational, automated systems. The results shed light on the most-cited articles on the use of “chatbots” and “tourism” or “hospitality”. The researchers scrutinize the extracted articles, synthesize the findings and outline the pros and cons of using these interactive technologies. This contribution implies that there is scope for tourism businesses to continue improving their online customer services in terms of their efficiency and responsiveness to consumers and prospects. For the time being, AI chatbots are still not in a position to replace human agents in all service interactions as they cannot resolve complex queries and complaints. However, works are in progress to improve their verbal, vocal and anthropomorphic capabilities to deliver a better consumer experience.peer-reviewe

Human-Machine Communication: Complete Volume. Volume 6

his is the complete volume of HMC Volume 6

What Makes AI ‘Intelligent’ and ‘Caring’?:Exploring Affect and Relationality Across Three Sites of Intelligence and Care

This research was funded in whole by the Wellcome Trust [Seed Award ‘AI and Health’ 213643/Z/18/Z]. For the purpose of Open Access, the authors have applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The authors would like to thank Dr Jane Hopton for inspiring discussions about AI and dimensions of intelligence, and three anonymous reviewers as well as the editor in chief Dr Timmemans at Social Science and Medicine for their very helpful and constructive feedback.Peer reviewedPublisher PD

eLuna : A Co-Design Framework for Mixed Reality Narrative Game- Based Learning

De siste tiårs utvidede fokus på læring utenfor skolen har bidratt til økt anvendelse av vitensentre som læringsarena for barn i grunnskole og videregående utdanning. En læringsløype er en type integrert læringsmiljø der de lærende, fysiske installasjoner, og digitale hjelpemidler bidrar til å fremme læringsinnhold og mål. På vitensentre brukes læringsløyper som pedagogisk støtte innen et bredt spekter av pensumplaner og programmer, gjennom å kombinere forskjellige sett av installasjoner og ved å vektlegge forskjellige aspekter av installasjonenes innhold. Siden de er sammensatt av både fysiske installasjoner og digitale hjelpemidler, er læringsløyper blandet virkelighet systemer, der de lærende interagerer med elementer i både den fysiske og virtuelle virkeligheten. Forskning har vist at både narrativ og spillmekanikker er blant de mest effektive komponentene som kan ligge til grunn for at læringsløyper skal kunne oppnå økt fokus på læringsinnhold, og for å engasjere de lærende ved å sette dem i en tilstand av flyt (av engelsk flow). Forskningen som presenteres i denne avhandlingen har som hovedmål å forbedre læring på vitensentre, gjennom å bidra med et co-design-rammeverk for blandet virkelighet narrative spillbaserte læringsløyper som underbygger positive effekter på engasjement, motivasjon, og læring. Narrativ har vært brukt til læring og instruksjon siden forhistorisk tid, og spill for læring har vært teoretisert og anvendt i mennesker i århundrer, i enda større grad etter oppfinnelsen av datamaskiner, og mulighetene bragt på banen gjennom digitale spill. Selv om bade narrative og spill har vært vist å kunne ha positive effekter når anvendt for læring, har forskning på effekter fra narrative spillbasert læring vist variable og motstridende resultater. Mangelen av en felles modell for kategorisering av narrative spill medfører manglende kunnskap relatert til hvordan og under hvilke forutsetninger narrative spill har effekt på læring. På tross av at de fleste studier av narrativ spillbasert læring unnlater å nevne narratologiske modeller, og de som gjør det primært refererer til modeller lånt fra andre media som mangler de nødvendige egenskapene til å kategorisere hendelsesflyten som benyttes i mange spill, finnes det en ludo narrativ variabel modell (LNVM), som er en narratologisk modell som kategorisere alle spill som narrativ. Denne forskningen videreutvikler LNVM, og presenterer en felles modell for kategorisering av narrativ spillbasert læring; eLNVM (fra engelsk: The extended LNVM). Narrative spillbaserte læringsløyper består av interaktive installasjoner og digitale hjelpemidler som belyser læringsmål innenfor pensumprogrammer. Det er derfor nødvendig med deltakelse både fra pedagoger og utviklere når slike læringsløyper skal designes og presenteres til lærende. Forskning viser at det er mangel av modeller, metoder, og rammeverk som myndiggjør pedagoger og utvikleres felles design av spillbasert læring, noe som enten resulterer i tapt fokus på læringsinnhold til fordel for engasjerende spillmekanikk, eller i at underholdningspotensialet i spill blir underordnet læringsmålene. Slike rammeverk må videre kunne skille mellom fysiske og virtuelle elementer for å være anvendbare i blandet virkelighet omgivelser. Forskningen presentert i denne avhandlingen benytter et rammeverk for informasjonssystemer som vitenskapelig metode til å utvikle eLuna co-design-rammeverket for blandet virkelighet narrative spillbaserte læringsløyper som underbygger positive effekter på engasjement, motivasjon, og læring. En systematisk litteraturstudie identifiserte 15 studier som rapporterte effekter fra digitale spillbaserte læringssystemer på engasjement, motivasjon, og læring. Disse systemene ble kategorisert med bruk av eLNVM og sortert basert på deres rapportering for å identifisere karakteristikker av narrative digital spillbasert læring som har positive effekter på engasjement, motivasjon, og læring. Denne forskningen benytter en iterativ design-basert forskningsprosess der karakteristikkene assosiert med de positive effektene legges til grunn for et co-design-rammeverk bestående av en metode og et visuelt språk. Co-design-rammeverket blir deretter utvidet med kapasitet til å separere mellom fysiske og virtuelle elementer i blandet virkelighet omgivelser. Rammeverket blir gjennom prosessen testet i deltakende co-design workshops og evaluert med bruk av varierte metoder, inkludert fokus grupper, intervjuer, spørreskjemaer, tematisk analyse, og heuristisk evaluering. Forskningen som blir presentert i denne doktoravhandlingen resulterer i eLuna co-design-rammeverket for narrative spillbasert læring, som kan bli brukt av pedagoger og utviklere til å lage både narrative digitale spillbaserte læringssystemer, og blandet virkelighet narrative spillbaserte læringsløyper som optimaliserer potensiale for positive effekter på engasjement, motivasjon, og læring.Increased focus on out of school learning over the last decades has led to extended use of science centres as learning arenas for pupils in primary and secondary education. A learning trail is a form of embedded learning environment in which the learners themselves, physical exhibits, and digital companions are elements that promote learning content and goals. When used in science centres, learning trails can combine different sets of exhibits and emphasize various aspects of their content to support learning goals inside a broad range of curricular plans and programs. Being comprised of physical exhibits and digital companions, science centre learning trails are mixed reality systems in which learner interaction occurs in both the physical and virtual domains. Research has shown that narratives and game mechanics are among the most effective components for science centre learning trails to achieve increased focus on the learning content, and to induce flow and engagement in learners. With an aim to contribute to improving science centre learning, the main objective of this research is to develop a co-design framework for mixed reality narrative game-based learning trails that enforce positive effects on engagement, motivation, and learning. Narratives have been used in learning and instruction since prehistoric times, and games for learning have been theorized and applied in human culture for centuries, increasingly so with the advent of the computer, and opportunities provided by digital games. While both narratives and games are shown to have the ability to positively affect learning, research on the effects from narrative game-based learning has shown mixed and contradictory results. The lack of a common model to categorize narrative games has led to a knowledge gap regarding how and under which conditions narrative games have effects on learning. Whereas most studies of narrative game-based learning neglect mentioning a narratological model at all, the ones that do mainly refer to models adapted from different media that lack the capabilities to properly categorize the event flow of many digital games. An exception is the ludo narrative variable model (LNVM), a narratological model that can properly categorize all games as narratives. Building on the LNVM, this research fills this gap with the development of the extended LNVM (eLNVM), a common model to categorize and isolate narratives in digital game-based learning. Narrative game-based learning trails comprise interactive exhibits and digital companions and promote learning goals inside curricular programs. Therefore, they require participation from educator and developer stakeholders to be properly designed and brought to learners. Research has shown that there is a lack of models, methods, or frameworks that empower educators and developers to co-design game-based learning, something which results in either the learning content being lost in the engaging mechanics of the game, or the fun of the games becoming inferior to the learning goals. Furthermore, to be applicable in science centres, such a co-design framework must also distinguish between physical and digital elements in mixed reality environments. Applying an information system research framework as a design science methodology, the eLuna co-design framework for mixed reality narrative game-based learning trails that enforce positive effects on engagement, motivation, and learning was developed. A systematic literature review identified 15 studies that self-reported effects of digital game-based learning systems on engagement, motivation, and learning. These were categorized on the eLNVM and sorted by their self-reported effects to identify what characterizes narrative digital game-based learning systems that positively affect engagement, motivation, and learning. Using an iterative design-based research process these characteristics associated with positive effects were then applied in a co-design framework comprising a method and a visual language, which was later extended with the capabilities to distinguish between physical and virtual elements in mixed reality learning trails. Throughout the process the framework was tested in co-design workshops with stakeholders and evaluated through mixed methods, including focus groups, semi-structured interviews, questionnaires, thematic analysis, and heuristic usability inspection. The research presented in this PhD dissertation contributes the eLuna co-design framework for narrative game-based learning, which empowers educators and developers in the creation of both narrative digital game-based learning and mixed reality narrative game-based learning trails that optimize the potential to induce positive effects on engagement, motivation, and learning.Doktorgradsavhandlin

Responsible domestic robotics:Exploring ethical implications of robots in the home

Purpose: The vision of robotics in the home promises increased convenience, comfort, companionship, and greater security for users. The robot industry risks causing harm to users, being rejected by society at large, or being regulated in overly prescriptive ways if robots are not developed in a socially responsible manner. The purpose of this paper is to explore some of the challenges and requirements for designing responsible domestic robots.Design/methodology/approach: The paper examines definitions of robotics and the current commercial state of the art. In particular it considers the emerging technological trends, such as smart homes, that are already embedding computational agents in the fabric of everyday life. The paper then explores the role of values in design, aligning with human computer interaction and considers the importance of the home as a deployment setting for robots. The paper examines what responsibility in robotics means and draws lessons from past home information technologies. An exploratory pilot survey was conducted to understand user concerns about different aspects of domestic robots such as form, privacy and trust. The paper provides these findings, married with literature analysis from across technology law, computer ethics and computer science.Findings: By drawing together both empirical observations and conceptual analysis, this paper concludes that user centric design is needed to create responsible domestic robotics in the future.Originality/value: This multidisciplinary paper provides conceptual and empirical research from different domains to unpack the challenges of designing responsible domestic robotics