During cooperative interaction, participants introduce materials, artefacts, and other individuals into the ongoing interaction. Depending on how this introduction unfolds, the participants may embrace the new element in an easy way or not. If the new element is a collaborative application of interactive software designed to support the interaction, it may or may not improve the collaboration because of how it was introduced. Therefore, understanding and designing the initial interaction is key for unleashing the positive impact of collaborative systems. The literature has identified the fact that humans employ a specific range of behaviors when introducing an element into an ongoing interaction. Those introduction rituals are determined by whether the new element is a human or a material artefact. Introduction rituals involving interactive elements are still underexplored: How do participants introduce and initiate interaction with them? This manuscript explores the introduction behaviors emerging when an augmented-reality collaborative application is being introduced into a financial advisory service. It shows that the participants employ a wider range of introduction rituals during the introduction of this application than they do when they introduce a brochure. Notably, many of the observed behaviors resemble familiar opening rituals typically used when introducing and greeting humans. This supports the computers-are-social-actors argument and provides evidence that introducing a collaborative application has a social rather than a material character.

Conversational agents such as Apple's Siri or Amazon's Alexa are becoming more and more prevalent. Almost every smart device comes equipped with such an agent. While on the one hand they can make menial everyday tasks a lot easier for people, there are also more sophisticated use cases in which conversational agents can be helpful. One of these use cases is tutoring in higher education. Several systems to support both formal and informal learning have been developed. There have been many studies about single characteristics of pedagogical conversational agents and how these influence learning outcomes. But what is still missing, is an overview and guideline for atomic design decisions that need to be taken into account when creating such a system. Based on a review of articles on pedagogical conversational agents, this paper provides an extension of existing classifications of characteristics as to include more fine-grained design aspects.