This is the first handbook where the world’s foremost “experts on expertise” review our scientific knowledge on expertise and expert performance and how experts may differ from non-experts in terms of their development, training, reasoning, knowledge, social support, and innate talent. Methods are described for the study of experts’ knowledge and their performance of representative tasks from their domain of expertise. The development of expertise is also studied by retrospective interviews and the daily lives of experts are studied with diaries. In 15 major domains of expertise, the leading researchers summarize our knowledge of the structure and acquisition of expert skill and knowledge and discuss future prospects. General issues that cut across most domains are reviewed in chapters on various aspects of expertise, such as general and practical intelligence, differences in brain activity, self-regulated learning, deliberate practice, aging, knowledge management, and creativity.

The Cambridge Handbook of Expertise and Expert Performance

Social robots can be used in education as tutors or peer learners. They have been shown to be effective at increasing cognitive and affective outcomes and have achieved outcomes similar to those of human tutoring on restricted tasks. This is largely because of their physical presence, which traditional learning technologies lack. We review the potential of social robots in education, discuss the technical challenges, and consider how the robot's appearance and behavior affect learning outcomes.

Social robots for education: A review

We present the first gesture recognition system implemented end-to-end on event-based hardware, using a TrueNorth neurosynaptic processor to recognize hand gestures in real-time at low power from events streamed live by a Dynamic Vision Sensor (DVS). The biologically inspired DVS transmits data only when a pixel detects a change, unlike traditional frame-based cameras which sample every pixel at a fixed frame rate. This sparse, asynchronous data representation lets event-based cameras operate at much lower power than frame-based cameras. However, much of the energy efficiency is lost if, as in previous work, the event stream is interpreted by conventional synchronous processors. Here, for the first time, we process a live DVS event stream using TrueNorth, a natively event-based processor with 1 million spiking neurons. Configured here as a convolutional neural network (CNN), the TrueNorth chip identifies the onset of a gesture with a latency of 105 ms while consuming less than 200 mW. The CNN achieves 96.5% out-of-sample accuracy on a newly collected DVS dataset (DvsGesture) comprising 11 hand gesture categories from 29 subjects under 3 illumination conditions.

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A Low Power, Fully Event-Based Gesture Recognition System

Robots are becoming an integral component of our society and have great potential in being utilized as an educational technology. To promote a deeper understanding of the area, we present a review of the field of robots in education. Several prior ventures in the area are discussed (post-2000) with the help of classification criteria. The dissecting criteria include domain of the learning activity, location of the activity, the role of the robot, types of robots and types of robotic behaviour. Our overview shows that robots are primarily used to provide language, science or technology education and that a robot can take on the role of a tutor, tool or peer in the learning activity. We also present open questions and challenges in the field that emerged from the overview. The results from our overview are of interest to not only researchers in the field of human–robot interaction but also administration in educational institutes who wish to understand the wider implications of adopting robots in education.

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A review of the applicability of robots in education

This article reviews the state of the art in social eye gaze for human-robot interaction (HRI) It establishes three categories of gaze research in HRI, defined by differences in goals and methods: a human-centered approach, which focuses on people's responses to gaze; a design-centered approach, which addresses the features of robot gaze behavior and appearance that improve interaction; and a technology-centered approach, which is concentrated on the computational tools for implementing social eye gaze in robots This paper begins with background information about gaze research in HRI and ends with a set of open questions

Social eye gaze in human-robot interaction: a review

Teaching is inherently a social interaction between teacher and student. Despite this knowledge, many educational tools, such as vocabulary training programs, still model the interaction in a tutoring scenario as unidirectional knowledge transfer rather than a social dialog. Therefore, ongoing research aims to develop virtual agents as more appropriate media in education. Virtual agents can induce the perception of a life-like social interaction partner that communicates through natural modalities such as speech, gestures and emotional expressions. This effect can be additionally enhanced with a physical robotic embodiment. This paper presents the development of social supportive behaviors for a robotic tutor to be used in a language learning application. The effect of these behaviors on the learning performance of students was evaluated. The results support that employing social supportive behavior increases learning efficiency of students.

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Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor

Recent methods and databases in vision-based hand gesture recognition

Nonverbal behaviors serve as a rich source of information in inter human communication. In particular, motion cues can reveal details on a person's current physical and mental state. Research has shown, that people do not only interpret motion cues of humans in these terms, but also the motion of animals and inanimate devices such as robots. In order to successfully integrate mobile robots in domestic environments, designers have therefore to take into account how the device will be perceived by the user. In this study we analyzed the relationship between motion characteristics of a robot and perceived affect. Based on a literature study we selected two motion characteristics, namely acceleration and curvature, which appear to be most influential for how motion is perceived. We systematically varied these motion parameters and recorded participants interpretations in terms of affective content. Our results suggest a strong relation between motion parameters and attribution of affect, while the type of embodiment had no effect. Furthermore, we found that the level of acceleration can be used to predict perceived arousal and that valence information is at least partly encoded in an interaction between acceleration and curvature. These findings are important for the design of behaviors for future autonomous household robots.

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Perception of affect elicited by robot motion

Previous research has shown that autonomous robots tend to induce the perception of a personality through their behavior and appearance. It has therefore been suggested that the personality of a robot can be used as a design guideline. A welldefined and clearly communicated personality can serve as a mental model of the robot and facilitate the interaction. From design perspective, this raises the question what kind of personality to design for a robot and how to express this personality? In this paper, we describe a process to design and evaluate personality and expressions for products. We applied this to design the personality and expressions in the behavior of a domestic robot.

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Iterative design process for robots with personality

Robots use their movement to interact with the user. Their movement is a crucial part in designing the interfaces of personal robots. It has a major impact on how a robot is perceived by the user interacting with it. Subtle flaws in the movement can create a repelling feeling and therefore affect negatively the interaction. On the other hand, carefully designed little quirks can give the robot personality and make it more interesting. A possible relationship between appearance and motion on how a device is perceived is described by the 'Uncanny Valley' conceived by Prof. M. Mori in 1970. It is widely used as a design guideline for creating humanoid interface robots. It does not, however, describe the impact that the quality of movements has on the perception and the believability of a character. Conclusive frameworks for the animation of robots are rare and are often adapted from cartoon or computer animation. This paper presents a refined design guideline for the motion of robotic characters with respect to the design requirements naturalness, adequateness and development over time. Furthermore, we created a set of tools that eases the process of designing the movement by improving on common animation techniques such as key-framed or scripted animations. The tools preserve the freedom of the animator to define specific expressive motions while at the same time offering the full power of scripting technology.

Martin Saerbeck

Papers

Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor

Recent methods and databases in vision-based hand gesture recognition

Perception of affect elicited by robot motion

Iterative design process for robots with personality

Design guidelines and tools for creating believable motion for personal robots