<p>This thesis focuses on the delivery of government services to citizens with a particula r emphasis on enabling those who are at risk of exclusion from the digital society to gain access to it. Following in this direction, one of the frequently addressed issues concerning the accessibility of e-services and information in government websites is found to be the users’ unawareness concerning the location of the desired information or service. Consequently, the overall objective of the thesis is to find, develop, and assess a solution to provide citizens with a simple and effective means of accessing and utilizing e-government services in government websites. The solution might be seen as a contribution to preventing digital exclusion among citizens caused by difficulties associated with navigation and way-finding, as well as the complexity of the utilization of the digitally provided services.</p><p>To gain this objective, the thesis argues for the use of a digital assistant; i.e. an embodied conversational agent able to provide the user with the desired services or information by means of a dialogue. Influenced by a real life situation, the overall idea behind the use of a digital assistant is that since knowledge about the arrangement of available drugs in a pharmacy and a particular drug's whereabouts in that organization is of little concern to customers, so too should knowledge of the organization and the whereabouts of services and information in a website be of little consequence to users. Therefore, a digital assistant is expected to act in a similar manner to a human agent who possesses knowledge regarding the existing infor mation and services, their application area, and where these are stored.</p><p>In order to realize the defined objective, this thesis is organized to cover all stages of the research process; i.e. the identification of the users’ difficulties in the current sit uation, the development of a prototype of a digital assistant, and the assessment and evaluation of the suggested solution in both a laboratory environment and in a real life situation. The thesis concludes by gathering and placing the results of the conducted studies in to a bigger context to find out whether or not the use of digital assistants improves the delivery of e-government services and the citizen’s utilization of them, and also to clarify and present the research project’s practical and methodological findings. With reference to the findings addressing the identified difficulties in the currents situation, the conducted studies showed that a digital assistant solution, such as the one described in this thesis, offers contributions to the accessibility of e-government services. It was also found that a digital assistant could contribute to the delivery of egovernment services by: a) reducing the technology barrier caused by the traditional input/output technologies, b) reducing the navigation barrier caused by the conventional web design, c) reducing the mental load of the user, and d) adding benefits and subjective pleasing.</p><p>The other interesting finding concerns the contribution of the digital assistant’s “approach” to the development of egovernment services. In other words, going from a traditional design of web interfaces to a digital assistant approach is similar to moving from an inside out perspective to a strictly customer or citizen oriented perspective. This shift in perspective could be recognized as a small revolution and it has many consequences for the development of e-government services compared to the current traditions.</p><p>Taken together, these findings have lead to an improvement in the digital assistant developed in this thesis, and suggest possibilities for future work within this area of research.</p>

This thesis focuses on the delivery of government services to citizens with a particula r emphasis on enabling those who are at risk of exclusion from the digital society to gain access to it. Following in this direction, one of the frequently addressed issues concerning the accessibility of e-services and information in government websites is found to be the users’ unawareness concerning the location of the desired information or service. Consequently, the overall objective of the thesis is to find, develop, and assess a solution to provide citizens with a simple and effective means of accessing and utilizing e-government services in government websites. The solution might be seen as a contribution to preventing digital exclusion among citizens caused by difficulties associated with navigation and way-finding, as well as the complexity of the utilization of the digitally provided services. To gain this objective, the thesis argues for the use of a digital assistant; i.e. an embodied conversational agent able to provide the user with the desired services or information by means of a dialogue. Influenced by a real life situation, the overall idea behind the use of a digital assistant is that since knowledge about the arrangement of available drugs in a pharmacy and a particular drug's whereabouts in that organization is of little concern to customers, so too should knowledge of the organization and the whereabouts of services and information in a website be of little consequence to users. Therefore, a digital assistant is expected to act in a similar manner to a human agent who possesses knowledge regarding the existing infor mation and services, their application area, and where these are stored. In order to realize the defined objective, this thesis is organized to cover all stages of the research process; i.e. the identification of the users’ difficulties in the current sit uation, the development of a prototype of a digital assistant, and the assessment and evaluation of the suggested solution in both a laboratory environment and in a real life situation. The thesis concludes by gathering and placing the results of the conducted studies in to a bigger context to find out whether or not the use of digital assistants improves the delivery of e-government services and the citizen’s utilization of them, and also to clarify and present the research project’s practical and methodological findings. With reference to the findings addressing the identified difficulties in the currents situation, the conducted studies showed that a digital assistant solution, such as the one described in this thesis, offers contributions to the accessibility of e-government services. It was also found that a digital assistant could contribute to the delivery of egovernment services by: a) reducing the technology barrier caused by the traditional input/output technologies, b) reducing the navigation barrier caused by the conventional web design, c) reducing the mental load of the user, and d) adding benefits and subjective pleasing. The other interesting finding concerns the contribution of the digital assistant’s “approach” to the development of egovernment services. In other words, going from a traditional design of web interfaces to a digital assistant approach is similar to moving from an inside out perspective to a strictly customer or citizen oriented perspective. This shift in perspective could be recognized as a small revolution and it has many consequences for the development of e-government services compared to the current traditions. Taken together, these findings have lead to an improvement in the digital assistant developed in this thesis, and suggest possibilities for future work within this area of research.

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.

Uma questão que se apresenta relevante, nesta tese, é que na maioria das vezes, o estudante, principalmente, o novato, demonstra grande dificuldade na aprendizagem baseada na resolução de problemas. Portanto, este precisa de monitoração, isto exige um apoio de entidades ou pessoas mais experientes. Percebe-se que, muitas vezes, por falta de domínio na área do conhecimento tratada, o estudante não analisa minuciosamente os dados do problema para poder conduzir objetivamente cada etapa de solução. Várias habilidades cognitivas são exigidas durante o processo de resolução de problemas, como por exemplo, codificação, comparação e combinação, componentes cognitivos significativos detectados em estudantes talentosos. A aprendizagem por meio do processo de resolução de problemas num ambiente online pode ampliar o pensamento crítico e aprimorar a tomada de decisão. Nesta pesquisa, foi criado um agente conversacional chamado Blaze, com o intuito de apoiar o estudante durante a aprendizagem autorregulada baseada na resolução de problemas. O agente foi desenvolvido com a linguagem de marcação AIML (Artificial Intelligence Markup Language), tendo sua base de conhecimento construída por meio da elicitação e representação dos processos cognitivos dos estudantes talentosos, alunos medalhistas da Olimpíada Brasileira de Matemática das Escolas Públicas. Utilizou-se a técnica de Raciocínio Baseado em Casos para permitir a recuperação e reutilização de experiências passadas dos estudantes talentosos. Foram realizados tantos experimentos com outros estudantes de graus de escolaridades distintos (2ª série do ensino médio, Licenciatura em Ciências e Licenciatura em Matemática) com o objetivo de investigar o engajamento e o aprimoramento das habilidades cognitivas destes durante a resolução dos problemas com a assistência do agente conversacional Blaze. Nestes experimentos, alguns estudantes interagiram com o agente Blaze durante o processo de resolução de problemas matemáticos, enquanto outros trabalharam sozinhos na resolução dos mesmos problemas. Os resultados obtidos nos experimentos permitiram verificar que o apoio do agente conversacional Blaze, no contexto de uma aprendizagem autorregulada durante a resolução de problemas, contribuiu qualitativamente para o aprimoramento de diversas habilidades cognitivas, como por exemplo, pensamento crítico, pensamento criativo, raciocínio lógico, bem como, permitiu o uso da metacognição. / A relevant issue raised in this paper is that most times students, especially inexperienced ones, show great difficulty for learning based on problem solving. Therefore, such students need to be monitored, which requires support from entities or more experienced people. Many times we see that due to students’ lack of mastery of the field of knowledge addressed, they fail to thoroughly analyze the problem data so as to objectively handle each stage of the solution. Several cognitive skills are required during the problem-solving process, such as coding, and comparison and combination, significant cognitive components detected in talented students. Learning by means of a problem-solving process in an online environment is capable of expanding critical thinking and improving students’ decision-making skills. In this research, a conversational agent we call Blaze was created in an effort to help students during their self-regulated, problem solving-based learning. The agent was developed via the AIML (Artificial Intelligence Markup Language), and its knowledge base was put together by means of eliciting and representing the cognitive processes of talented students, students who had won medals at the Brazilian Public School Mathematics Olympic Games. We used the Case-Based Reasoning technique to enable us to recover and reuse the talented students’ past experiences. Some other experiments were carried out with other students from various schooling levels (high school sophomores, and Science and Math undergrads) in order to look into those students’ engagement and improvement of their cognitive skills as they solved problems assisted by the Blaze conversational agent. In those experiments, some students interacted with the Blaze agent during the math problem-solving process, while other students worked alone on solving the same problems. The results obtained from the experiments allowed us to find that the support from the Blaze conversational agent, in the context of self-regulated learning during problem-solving, qualitatively helped the students improve their several cognitive skills, such as critical thinking, creative thinking, and logic reasoning, besides enabling the use of meta-cognition.

Nous présentons dans cette thèse un modèle pour la coordination de la parole dans des interactions dyadiques utilisateur-agent. Selon une approche courante, coordonner la parole reviendrait à éviter les recouvrements de parole et à minimiser les moments de silence entre deux tours, ceci pour rendre plus fluide l’interaction avec l’agent et améliorer l’expérience de l’utilisateur en interaction dialogique avec l’agent. Les interactions humaines montrent néanmoins une coordination plus complexe avec des recouvrements de parole compétitifs ou non compétitifs et des moments de silences longs. Selon notre approche, c’est en permettant cette diversité des situations que nous verrons émerger, entre l’utilisateur et l’agent, une interaction plus fluide et plus crédible, améliorant l’expérience de l’utilisateur avec l’agent. Les échanges de paroles sont néanmoins, par nature, complexes, la coordination se faisant par l’interaction entre locuteur et auditeur plus que par un participant en particulier. Pour capturer cette complexité, nous avons élaboré un modèle mettant l’accent sur une coordination de la parole basée sur un couplage sensorimoteur continu. Sur la base de ce couplage sensorimoteur, le comportement de l’agent n’est pas entièrement contrôlé par ce dernier, mais est émergent de l’interaction entre les participants. Nous montrons la capacité de notre modèle à faire émerger les différentes situations liées à la coordination de la parole humaine à la fois dans une interaction entre deux agents et dans une interaction utilisateur-agent. / In this thesis, we present a model for the coordination of speaking turns in dyadic interactions between users and agents. According to a common view, to coordinate turns means avoiding overlaps and reduces silences between turns. By optimizing turn transitions between users and agents, the user’s experience is expected to be improved. However, observations of human conversations show a more complex coordination of speaking turns between users and agents: awkward silences and overlaps, competitive or not, are common. In order to improve the credibility and the naturalness of the interaction, we must observe the same variability of situations in a user-agent interaction. Nevertheless, coordination of speaking turns is, by nature, complex, the coordination is managed by the interaction between participants more than controlled by one participant alone. To capture this complexity, we elaborated a model emphasizing the continuous sensory-motor coupling existing between the user and the agent. As a result of this sensory-motor coupling, the behavior of the agent is not entirely controlled by the agent but is an emergent property of the interaction between the user and the agent. We show the capacity of our model to make emerge the different situations linked to the coordination of speaking turns in interactions between two agents and between one user and one agent.

Embodied Conversational Agents (ECAs)’ gestures can enhance human perception in many dimensions during interactions. In recent years, data-driven gesture generation approaches for ECAs have attracted considerable research attention and effort, and methods have been continuously optimized. Researchers have typically used human-agent interaction for user studies when evaluating systems of ECAs that generate rule-based gestures. However, when evaluating the performance of ECAs that generate gestures based on data-driven methods, participants are often required to watch prerecorded videos, which cannot provide an adequate assessment of human perception during the interaction. To address this limitation, we proposed two main research objectives: First, to explore the workflow of assessing data-driven gesturing ECAs through real-time interaction. Second, to investigate whether gestures could affect ECAs’ human-likeness, animacy, perceived intelligence, and humans’ focused attention in ECAs. Our user study required participants to interact with two ECAs by setting two experimental conditions with and without hand gestures. Both subjective data from the participants’ self-report questionnaire and objective data from the gaze tracker were collected. To our knowledge, the current study represents the first attempt to evaluate data-driven gesturing ECAs through real-time interaction and the first experiment using gaze-tracking to examine the effect of ECA gestures. The eye-gazing data indicated that when an ECA can generate gestures, it would attract more attention to its body. / Förkroppsligade konversationsagenter (Embodied Conversational Agents, ECAs) gester kan förbättra människans uppfattning i många dimensioner under interaktioner. Under de senaste åren har datadrivna metoder för att generera gester för ECA:er fått stor uppmärksamhet och stora ansträngningar inom forskningen, och metoderna har kontinuerligt optimerats. Forskare har vanligtvis använt sig av interaktion mellan människa och agent för användarstudier när de utvärderat system för ECA:er som genererar regelbaserade gester. När man utvärderar prestandan hos ECA:er som genererar gester baserat på datadrivna metoder måste deltagarna ofta titta på förinspelade videor, vilket inte ger en adekvat bedömning av människans uppfattning under interaktionen. För att åtgärda denna begränsning föreslog vi två huvudsakliga forskningsmål: För det första att utforska arbetsflödet för att bedöma datadrivna ECA:er för gester genom interaktion i realtid. För det andra att undersöka om gester kan påverka ECA:s människoliknande, animerade karaktär, upplevd intelligens och människors fokuserade uppmärksamhet i ECA:s. I vår användarstudie fick deltagarna interagera med två ECA:er genom att ställa in två experimentella villkor med och utan handgester. Både subjektiva data från deltagarnas självrapporterande frågeformulär och objektiva data från gaze tracker samlades in. Såvitt vi vet är den aktuella studien det första försöket att utvärdera datadrivna ECA:er med gester genom interaktion i realtid och det första experimentet där man använder blickspårning för att undersöka effekten av ECA:s gester. Uppgifterna om blickspårning visade att när en ECA kan generera gester skulle den locka mer uppmärksamhet till sin kropp.

Notre objectif est de simuler des comportements multimodaux expressifs pour les agents conversationnels animés ACA. Ceux-ci sont des entités dotées de capacités affectives et communicationnelles; ils ont souvent une apparence humaine. Quand un ACA parle ou rit, il est capable de montrer de façon autonome des comportements multimodaux pour enrichir et compléter son discours prononcé et transmettre des informations qualitatives telles que ses émotions. Notre recherche utilise les modèles d’apprentissage à partir données. Un modèle de génération de comportements multimodaux pour un personnage virtuel parlant avec des émotions différentes a été proposé ainsi qu’un modèle de simulation du comportement de rire sur un ACA. Notre objectif est d'étudier et de développer des générateurs d'animation pour simuler la parole expressive et le rire d’un ACA. En partant de la relation liant prosodie de la parole et comportements multimodaux, notre générateur d'animation prend en entrée les signaux audio prononcés et fournit en sortie des comportements multimodaux. Notre travail vise à utiliser un modèle statistique pour saisir la relation entre les signaux donnés en entrée et les signaux de sortie; puis cette relation est transformée en modèle d’animation 3D. Durant l'étape d’apprentissage, le modèle statistique est entrainé à partir de paramètres communs qui sont composés de paramètres d'entrée et de sortie. La relation entre les signaux d'entrée et de sortie peut être capturée et caractérisée par les paramètres du modèle statistique. Dans l'étape de synthèse, le modèle entrainé est utilisé pour produire des signaux de sortie (expressions faciale, mouvement de tête et du torse) à partir des signaux d'entrée (F0, énergie de la parole ou pseudo-phonème du rire). La relation apprise durant la phase d'apprentissage peut être rendue dans les signaux de sortie. Notre module proposé est basé sur des variantes des modèles de Markov cachés (HMM), appelées HMM contextuels. Ce modèle est capable de capturer la relation entre les mouvements multimodaux et de la parole (ou rire); puis cette relation est rendue par l’animation de l’ACA. / Our aim is to render expressive multimodal behaviors for Embodied conversational agents, ECAs. ECAs are entities endowed with communicative and emotional capabilities; they have human-like appearance. When an ECA is speaking or laughing, it is capable of displaying autonomously behaviors to enrich and complement the uttered speech and to convey qualitative information such as emotion. Our research lies in the data-driven approach. It focuses on generating the multimodal behaviors for a virtual character speaking with different emotions. It is also concerned with simulating laughing behavior on an ECA. Our aim is to study and to develop human-like animation generators for speaking and laughing ECA. On the basis of the relationship linking speech prosody and multimodal behaviors, our animation generator takes as input human uttered audio signals and output multimodal behaviors. Our work focuses on using statistical framework to capture the relationship between the input and the output signals; then this relationship is rendered into synthesized animation. In the training step, the statistical framework is trained based on joint features, which are composed of input and of output features. The relation between input and output signals can be captured and characterized by the parameters of the statistical framework. In the synthesis step, the trained framework is used to produce output signals (facial expression, head and torso movements) from input signals (F0, energy for speech or pseudo-phoneme of laughter). The relation captured in the training phase can be rendered into the output signals. Our proposed module is based on variants of Hidden Markov Model (HMM), called Contextual HMM. This model is capable of capturing the relationship between human motions and speech (or laughter); then such relationship is rendered into the synthesized animations.

Chatbotar ses allt oftare i olika sammanhang och blir i takt med teknologins utveckling mer avancerade. Innovationer inom områden som artificiell intelligens (AI) och natural language processing (NLP) har bidragit till att chatbotar kan uppfatta och svara på komplexa frågeställningar samt utföra en mängd olika tjänster. Trots den accelererande utvecklingen pekar tidigare forskning på att användare upplever svårigheter i interaktionen och att chatbotarna lämnar mycket att önska. Relaterat till problematiken kring användarupplevelsen av chatbotar visar även forskningen svårigheter med att stärka användarupplevelser. Det har i tidigare forskning identifierats behov av att omvandla teori från tidigare forskning till praktiskt tillämpningsbara riktlinjer för hur användarvänliga chatbotar kan utformas och utvärderas. Denna litteraturstudie minskar kunskapsgapet genom att med tematisk analys identifiera, syntetisera och kategorisera kvalitetskriterier baserade på användarupplevelser av chatbotar. Dessa kategorier och kriterier speglar den samlade forskningens krav på chatbotar och utgör vägledande kunskap vid design- och utvärdering av chatbotar. Denna studie syftar därmed att bidra med svar på frågan: Vilka kvalitetskriterier bör övervägas vid design och utvärdering av chatbotar? / Chatbots are increasingly seen in different contexts and are becoming more advanced as technology develops. Innovations in areas such as artificial intelligence (AI) and natural language processing (NLP) have helped chatbots to perceive and respond to complex queries and perform a wide range of services. Despite this accelerating development, previous research indicates that users experience difficulties in interacting and that chatbots leave much to be desired. Related to the problems surrounding the user experience of chatbots, research also shows difficulties in enhancing user experiences. Previous research has identified the need to translate theory from previous research into practically applicable guidelines for how user-friendly chatbots can be designed and evaluated. This literature review addresses the knowledge gap by using thematic analysis to identify, synthesise and categorise quality criteria based on user experiences of chatbots. These categories and criteria reflect the overall research requirements for chatbots and provide guiding knowledge for the design and evaluation of chatbots. This study thus aims to contribute answers to the question: What quality criteria should be considered in the design and evaluation of chatbots?

Der Einsatz von Sprachassistenten (Alltagsbeispiele sind Alexa von Amazon, Siri von Apple oder der Chatbot von Hellofresh) hat auch im Gesundheitswesen Einzug gehalten. Ein aktuelles Beispiel ist der WhatsApp Chatbot der WHO, welcher Nutzer:innen über COVID-19 aufklärt. Sprachassistenten haben die Fähigkeit, Patienten und Patientinnen orts- und zeitunabhängig aufzuklären, wodurch Mitarbeiter:innen entlastet werden. Jedoch gibt es neben den technischen (u. a. Entwicklung und Optimierung der Algorithmen für die Spracherkennung) auch Herausforderungen in der Mensch-Chatbot-Interaktion. In dieser Studie wird untersucht, welche Rolle die menschenähnliche Gestaltung (u. a. menschlicher Name, Begrüßung, menschlicher Avatar) eines Reiseimpfberatungschatbots auf dessen Wahrnehmung durch Nutzer:innen hat. Spezifisch geht es darum zu verstehen, ob und wie sich Anthropomorphismus (die Wahrnehmung von Menschlichkeit und sozialer Präsenz in Objekten, Tieren und Maschinen) auf die wahrgenommene Vertrauenswürdigkeit und letztendliche Zufriedenheit mit dem Service auswirkt. In einem Online-Experiment mit 78 Teilnehmer:innen, wurden zwei Chatbot-Gestaltungen (mit menschenähnlichen Gestaltungselementen vs. ohne diese Elemente) verglichen. Die Ergebnisse zeigen, dass die wahrgenommene soziale Präsenz signifikant die wahrgenommene Vertrauenswürdigkeit und die Zufriedenheit mit dem Service des Chatbots erhöhen. Somit ist die Implikation, dass bei der Reiseimpfberatung und ähnlichen Beratungsprozessen eine menschliche Gestaltung der Sprachassistenten zu empfehlen ist.