Elaheh Sanoubari

Elaheh Sanoubari, Alicia Pan, Keith Rebello et al.

Social robots are increasingly used in education, but most applications cast them as tutors offering explanation-based instruction. We explore an alternative: Robot-Mediated Applied Drama (RMAD), in which robots function as life-like puppets in interactive dramatic experiences designed to support reflection and social-emotional learning. This paper presents REMind, an anti-bullying robot role-play game that helps children rehearse bystander intervention and peer support. We focus on a central design challenge in RMAD: how to make robot drama emotionally and aesthetically engaging despite the limited expressive capacities of current robotic platforms. Through the development of REMind, we show how performing arts expertise informed this process, and argue that the aesthetics of robot drama arise from the coordinated design of the wider experience, not from robot expressivity alone.

Elaheh Sanoubari

We used the Webots robotics simulation platform to simulate a dyadic avoiding and mobbing predator behavior in a group of Braitenbergian robots. Mobbing is an antipredator adaptation used by some animals in which the individuals cooperatively attack or harass a predator to protect themselves. One way of coordinating a mobbing attack is using mobbing calls to summon other individuals of the mobbing species. We imitated this mechanism and simulated Braitenbergian robots that use mobbing calls when they face a light source (representing an inanimate predator) and mob it if they can summon allies, otherwise, they escape from it. We explore the effects of range of mobbing call (infinite range, mid-range and low-range) and the size of the robot group (ten robots vs three) on the overall success of mobbing. Our results suggest that both variables have significant impacts. This work has implications for simulations of action selection in artificial life and designing control architectures for autonomous agents.

Elaheh Sanoubari, Neil Fernandes, Keith Rebello et al.

This paper presents REMind, an innovative educational robot-mediated role-play game designed to support anti-bullying bystander intervention among children. REMind invites players to observe a bullying scenario enacted by social robots, reflect on the perspectives of the characters, and rehearse defending strategies by puppeteering a robotic avatar. We evaluated REMind through a mixed-methods play-testing study with 18 children aged 9--10. The findings suggest that the experience supported key learning goals related to self-efficacy, perspective-taking, understanding outcomes of defending, and intervention strategies. These results highlight the promise of Robot-Mediated Applied Drama (RMAD) as a novel pedagogical framework to support Social-Emotional Learning.

Justin Edwards, Elaheh Sanoubari

Across several branches of conversational interaction research including interactions with social robots, embodied agents, and conversational assistants, users have identified trust as a critical part of those interactions. Nevertheless, there is little agreement on what trust means within these sort of interactions or how trust can be measured. In this paper, we explore some of the dimensions of trust as it has been understood in previous work and we outline some of the ways trust has been measured in the hopes of furthering discussion of the concept across the field.