Effects of Adaptive Conversational User Interfaces on Enjoyment and Engagement while assessing Wellbeing

A decrease in wellbeing worldwide due to the COVID-19 pandemic called for ways to assess wellbeing in a scalable and adequate manner. Conversational User Interfaces (CUIs) seem suitable, however, applying them optimally in certain contexts remains a challenge. This study aims to find ways to make CUIs more engaging and have a better experience by making them adaptive. A 3x2 between-subjects experiment is designed in which the effects of avatar presence, gender, and an empathic conversational style are researched. A chatbot was created in telegram, and the visual design and conversational style were altered to measure the effects on Questionnaire Experience (QX), Enjoyment, and Empathy. In total 30 participants chatted with a randomly assigned chatbot and filled in a survey about their experiences. There is no statistical preference for avatar presence or conversational style. Male gendered chatbots score higher on QX, but female chatbots are perceived as more empathic when comparing gender.
CSE3000 Research Project
Computer Science and Engineering