Recently, text-based chatbots had a rise in popularity, possibly due to new APIs for online social networks and messenger services, and development platforms that help dealing with all the necessary Natural Language Processing. But, as chatbots use natural language as interface, their users may struggle to discover which sentences the chatbots will understand and what they can do. Because of that it is important to support their designers in deciding how to convey the chatbots’ features, as this might determine whether the user will continue chatting or not. In this work, our goal is to analyze the communicative strategies used by popular chatbots when conveying their features to users. We used the Semiotic Inspection Method (SIM) for that end, and as a result we were able to identify a series of strategies used by the analyzed chatbots for conveying their features to users. We then consolidate these findings by analyzing other chatbots. Finally, we discuss the use of these strategies, as well as challenges for designing such interfaces and limitations of using SIM on them.

No abstract

Human-computer interaction (HCI) is increasingly becoming a subject taught in universities around the world. However, little is known of the interactions of the HCI curriculum with students in different types of institutions and disciplines internationally. In order to explore these interactions, we studied the performance of HCI students in design, technology and business faculties in universities in UK, India, Namibia, Mexico and China who participated in a common set of design and evaluation tasks. We obtained participants' cognitive style profiles based on Allinson and Hayes scale in order to gain further insights into their learning styles and explore any relation between these and performance. We found participants' cognitive style preferences to be predominantly in the adaptive range, i.e. with combined analytical and intuitive traits, compared to normative data for software engineering, psychology and design professionals. We further identified significant relations between students' cognitive styles and performance in analytical and creative tasks of a HCI professional individual. We discuss the findings in the context of the distinct backgrounds of the students and universities that participated in this study and the value of research that explores and promotes diversity in HCI education.

No abstract

No abstract

No abstract

Interação Humano-Computador (IHC) é uma área do conhecimento diversa em termos de países, instituições, departamentos e cursos em que é oferecida; e também em termos de pessoas que são ou estão se tornando pesquisadores e profissionais na área. A diversidade de contextos, conteúdos, e estilos de aprendizado dos estudantes são alguns dos fatores que trazem desafios para o ensino de IHC. Este estudo procura contribuir para o entendimento da interação entre o currículo de IHC e estudantes em diferentes instituições, áreas do conhecimento e países através da exploração da interação entre o currículo de IHC e estudantes de contextos distintos.

No abstract