Towards a Synthetic Tutor Assistant: The EASEL Project and its Architecture

Abstract

Abstract. Robots are gradually but steadily being introduced in our daily lives. A paramount application is that of education, where robots can assume the role of a tutor, a peer or simply a tool to help learners in a specific knowledge domain. Such endeavor posits specific challenges: affective social behavior, proper modelling of the learner's progress, discrimination of the learner's utterances, expressions and mental states, which, in turn, require an integrated architecture combining perception, cognition and action. In this paper we present an attempt to improve the current state of robots in the educational domain by introducing the EASEL EU project. Specifically, we introduce the EASEL's unified robot architecture, an innovative Synthetic Tutor Assistant (STA) whose goal is to interactively guide learners in a science-based learning paradigm, allowing us to achieve such rich multimodal interactions.

Children’s Age Influences Their Use of Biological and Mechanical Questions Towards a Humanoid

“…HRI scenarios Two interactive scenarios, developed to explore HRI in an educational context (Expressive agents for Symbiotic Education and Learning, EASEL [16], [17]) were used for data collection. Both scenarios had been pretested for suitability as a social and educational interaction for the age groups in this study.…”

Children use non-verbal cues to learn new words from robots as well as people

“…Prior research has shown that young children will not only treat social robots as companions and guides (Belpaeme et al, 2012;Kahn et al, 2012;Shiomi et al, 2015), but will also readily learn new information from them (Breazeal et al, 2016;Kennedy et al, 2016;Movellan et al, 2009;Tanaka and Matsuzoe, 2012;Vouloutsi et al, 2016).…”

Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions

“…2. Please refer to [24] for details. The modules interacts with each other: (1) The DM generates behaviour specifications transmitted to the BR; (2) The BR converts the behaviour specifications into platform-specific commands to the ACE; (3) The ACE executes the commands and delivers feedback to the BR about planning and execution of the commands; (4) The BR provides higher level feedback to the DM about the behaviour progression.…”