Paul Baxter

The Robot Who Tried Too Hard: Social Behaviour of a Robot Tutor Can Negatively Affect Child Learning

Social robots are finding increasing application in the domain of education, particularly for children, to support and augment learning opportunities. With an implicit assumption that social and adaptive behaviour is desirable, it is therefore of interest to determine precisely how these aspects of behaviour may be exploited in robots to support children in their learning. In this paper, we explore this issue by evaluating the effect of a social robot tutoring strategy with children learning about prime numbers. It is shown that the tutoring strategy itself leads to improvement, but that the presence of a robot employing this strategy amplifies this effect, resulting in significant learning. However, it was also found that children interacting with a robot using social and adaptive behaviours in addition to the teaching strategy did not learn a significant amount. These results indicate that while the presence of a physical robot leads to improved learning, caution is required when applying social behaviour to a robot in a tutoring context. Categories and Subject Descriptors H.1.2 [Models and Principles]: User/Machine Systems

A review of long-term memory in natural and synthetic systems

Memory may be broadly regarded as information gained from past experience that is available in the service of ongoing and future adaptive behavior. The biological implementation of memory shares little with memory in synthetic cognitive systems where it is typically regarded as a passive storage structure. Neurophysiological evidence indicates that memory is neither passive nor centralized. A review of the relevant literature in the biological and computer sciences is conducted and a novel methodology is applied that incorporates neuroethological approaches with general biological inspiration in the design of synthetic cognitive systems: a case study regarding episodic memory provides an illustration of the utility of this methodology. As a consequence of applying this approach to the reinterpretation of the implementation of memory in synthetic systems, four fundamental functional principles are derived that are in accordance with neuroscientific theory, and which may be applied to the design of more adaptive and robust synthetic cognitive systems: priming, cross-modal associations, cross-modal coordination without semantic information transfer, and global system behavior resulting from activation dynamics within the memory system.

Comparing Robot Embodiments in a Guided Discovery Learning Interaction with Children

The application of social robots to the domain of education is becoming more prevalent. However, there remain a wide range of open issues, such as the effectiveness of robots as tutors on student learning outcomes, the role of social behaviour in teaching interactions, and how the embodiment of a robot influences the interaction. In this paper, we seek to explore children’s behaviour towards a robot tutor for children in a novel guided discovery learning interaction. Since the necessity of real robots (as opposed to virtual agents) in education has not been definitively established in the literature, the effect of robot embodiment is assessed. The results demonstrate that children overcome strong incorrect biases in the material to be learned, but with no significant differences between embodiment conditions. However, the data do suggest that the use of real robots carries an advantage in terms of social presence that could provide educational benefits.

Child-Robot Interaction: Perspectives and Challenges

Child-Robot Interaction (cHRI) is a promising point of entry into the rich challenge that social HRI is. Starting from three years of experiences gained in a cHRI research project, this paper offers a view on the opportunities offered by letting robots interact with children rather than with adults and having the interaction in real-world circumstances rather than lab settings. It identifies the main challenges which face the field of cHRI: the technical challenges, while tremendous, might be overcome by moving away from the classical perspective of seeing social cognition as residing inside an agent, to seeing social cognition as a continuous and self-correcting interaction between two agents.

A touchscreen-based 'sandtray' to facilitate, mediate and contextualise human-robot social interaction

In the development of companion robots capable of any-depth, long-term interaction, social scenarios enable exploration of the robots capacity to engage a human interactant. These scenarios are typically constrained to structured task-based interactions, to enable the quantification of results for the comparison of differing experimental conditions. This paper introduces a hardware setup to facilitate and mediate human-robot social interaction, simplifying the robot control task while enabling an equalised degree of environmental manipulation for the human and robot, but without implicitly imposing an a priori interaction structure.

From Characterising Three Years of HRI to Methodology and Reporting Recommendations

Human-Robot Interaction (HRI) research requires the integration and cooperation of multiple disciplines, technical and social, in order to make progress. In many cases using different motivations, each of these disciplines bring with them different assumptions and methodologies. We assess recent trends in the field of HRI by examining publications in the HRI conference over the past three years (over 100 full papers), and characterise them according to 14 categories. We focus primarily on aspects of methodology. From this, a series of practical recommendations based on rigorous guidelines from other research fields that have not yet become common practice in HRI are proposed. Furthermore, we explore the primary implications of the observed recent trends for the field more generally, in terms of both methodology and research directions. We propose that the interdisciplinary nature of HRI must be maintained, but that a common methodological approach provides a much needed frame of reference to facilitate rigorous future progress.

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.

How to Build a Supervised Autonomous System for Robot-Enhanced Therapy for Children with Autism Spectrum Disorder

Abstract Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Higher Nonverbal Immediacy Leads to Greater Learning Gains in Child-Robot Tutoring Interactions

Nonverbal immediacy has been positively correlated with cognitive learning gains in human-human interaction, but remains relatively under-explored in human-robot interaction contexts. This paper presents a study in which robot behaviour is derived from the principles of nonverbal immediacy. Both high and low immediacy behaviours are evaluated in a tutoring interaction with children where a robot teaches how to work out whether numbers are prime. It is found that children who interact with the robot exhibiting more immediate nonverbal behaviour make significant learning gains, whereas those interacting with the less immediate robot do not. A strong trend is found suggesting that the children can perceive the differences between conditions, supporting results from existing work with adults.

What a robotic companion could do for a diabetic child

Being a child with diabetes is challenging: apart from the emotional difficulties of dealing with the disease, there are multiple physical aspects that need to be dealt with on a daily basis. Furthermore, as the children grow older, it becomes necessary to self-manage their condition without the explicit supervision of parents or carers. This process requires that the children overcome a steep learning curve. Previous work hypothesized that a robot could provide a supporting role in this process. In this paper, we characterise this potential support in greater detail through a structured collection of perspectives from all stakeholders, namely the diabetic children, their siblings and parents, and the healthcare professionals involved in their diabetes education and care. A series of brain-storming sessions were conducted with 22 families with a diabetic child (32 children and 38 adults in total) to explore areas in which they expected that a robot could provide support and/or assistance. These perspectives were then reviewed, validated and extended by healthcare professionals to provide a medical grounding. The results of these analyses suggested a number of specific functions that a companion robot could fulfil to support diabetic children in their daily lives.