The Last Decade of HCI Research on Children and Voice-based Conversational Agents

Voice-based Conversational Agents (CAs) are increasingly being used by children. Through a review of 38 research papers, this work maps trends, themes, and methods of empirical research on children and CAs in HCI research over the last decade. A thematic analysis of the research found that work in this domain focuses on seven key topics: ascribing human-like qualities to CAs, CAs’ support of children’s learning, the use and role of CAs in the home and family context, CAs’ support of children’s play, children’s storytelling with CA, issues concerning the collection of information revealed by CAs, and CAs designed for children with differing abilities. Based on our findings, we identify the needs to account for children's intersectional identities and linguistic and cultural diversity and theories from multiple disciples in the design of CAs, develop heuristics for child-centric interaction with CAs, to investigate implications of CAs on social cognition and interpersonal relationships, and to examine and design for multi-party interactions with CAs for different domains and contexts

An ambient agent model for reading companion robot

Reading is essentially a problem-solving task. Based on what is read, like problem solving, it requires effort, planning, self-monitoring, strategy selection, and reflection. Also, as readers are trying to solve difficult problems, reading materials become more complex, thus demands more effort and challenges cognition. To address this issue, companion robots can be deployed to assist readers in solving difficult reading tasks by making reading process more enjoyable and meaningful. These robots require an ambient agent model, monitoring of a reader’s cognitive demand as it could consist of more complex tasks and dynamic interactions between human and environment. Current cognitive load models are not developed in a form to have reasoning qualities and not integrated into companion robots. Thus, this study has been conducted to develop an ambient agent model of cognitive load and reading performance to be integrated into a reading companion robot. The research activities were based on Design Science Research Process, Agent-Based Modelling, and Ambient Agent Framework. The proposed model was evaluated through a series of verification and validation approaches. The verification process includes equilibria evaluation and automated trace analysis approaches to ensure the model exhibits realistic behaviours and in accordance to related empirical data and literature. On the other hand, validation process that involved human experiment proved that a reading companion robot was able to reduce cognitive load during demanding reading tasks. Moreover, experiments results indicated that the integration of an ambient agent model into a reading companion robot enabled the robot to be perceived as a social, intelligent, useful, and motivational digital side-kick. The study contribution makes it feasible for new endeavours that aim at designing ambient applications based on human’s physical and cognitive process as an ambient agent model of cognitive load and reading performance was developed. Furthermore, it also helps in designing more realistic reading companion robots in the future