Browsing the literature shows that an increasing number of authors choose to use the learning by teaching approach in the field of educational robotics. The goal of this paper is, on the one hand, to produce a review of articles describing the effects of this approach on learning and, on the other hand, to review the literature in order to explore the characteristics at the core of this approach. We will only focus on the work using a humanoid robot. The areas of learning studied are writing, reading, vocabulary, and reasoning, but also there are some metacognitive abilities like task commitment and mental state attribution. Their targets are from very young children to preadolescents. We can already notice some studies on pupils with special educational needs. In all of these domains, the results show a nonnegligible effect of learning by teaching both on learning and on metacognitive abilities. If the concept of learning by teaching is clear, a careful investigation of the different studies shows that experimental paradigms do not use the same basic characteristics. For some, it is the robot’s weakness, the care that must be given to it, which is the main requirement for the approach, while for others it is the unbalanced distribution of knowledge which is at the heart of it. The learning by teaching approach we will study has two components: the robot and the child tutor. The characteristics of the robot and what is asked of the child to accomplish his or her task of the tutor will be analyzed.

Individuals with Autism Spectrum Disorder show deficits in communication and social interaction, as well as repetitive behaviors and restricted interests. Interacting with robots could bring benefits to this population, notably by fostering communication and social interaction. Studies even suggest that people with Autism Spectrum Disorder could interact more easily with a robot partner rather than a human partner. We will be looking at the benefits of robots and the reasons put forward to explain these results. The interest regarding robots would mainly be due to three of their characteristics: they can act as motivational tools, and they are simplified agents whose behavior is more predictable than that of a human. Nevertheless, there are still many challenges to be met in specifying the optimum conditions for using robots with individuals with Autism Spectrum Disorder.

The increasing presence of robots in our society raises questions about how these objects are perceived by users. Individuals seem inclined to attribute human capabilities to robots, a phenomenon called anthropomorphism. Contrary to what intuition might suggest, these attributions vary according to different factors, not only robotic factors (related to the robot itself), but also situational factors (related to the interaction setting), and human factors (related to the user). The present review aims at synthesizing the results of the literature concerning the factors that influence anthropomorphism, in order to specify their impact on the perception of robots by individuals. A total of 134 experimental studies were included from 2002 to 2023. The mere appearance hypothesis and the SEEK (sociality, effectance, and elicited agent knowledge) theory are two theories attempting to explain anthropomorphism. According to the present review, which highlights the crucial role of contextual factors, the SEEK theory better explains the observations on the subject compared to the mere appearance hypothesis, although it does not explicitly explain all the factors involved (e.g., the autonomy of the robot). Moreover, the large methodological variability in the study of anthropomorphism makes the generalization of results complex. Recommendations are proposed for future studies.

Previous research in the field of cognitive science has demonstrated the relevance of measuring reaction times to describe the cognitive cost of processing information, yet it has seldom been studied in the context of conversations and, to our knowledge, never in free flowing, interactive conversations. This study presents a way of analyzing entire online conversations in a protocol inspired by the Turing Test to investigate the relation between violations of Grice's Cooperation Principle and the response times of the participants. We hypothesized that response times are directly correlated to the cognitive cost required to generate implicatures from a statement. Our results show that violations of the maxim of Relation significantly increased the response time, especially for female participants. This confirms that measuring response times during a conversation can be a simple and relevant way of inferring the cognitive cost of processing an utterance.

Robots are increasingly used in scientific research. Given the multitude of existing robots, how to choose the most adapted robot to a research and above all, how to use it to study biases in reasoning or in decision making? We suggested studying well-known biases from a new point of view: social norms, including social behaviors, social context and pragmatics of language. How to measure the impact of implicit social factors on the term of an experimental interaction when the experimenter cannot control non-verbal social cues he emits? A robot, whose behavior can entirely be programmed, constitutes a useful tool for this level. Authors' purpose is to expose a new method, accessible to all and neophytes in computers, which can be applied to a humanoid reactive robot for scientific research. Harel's “statechart” bring a formalism allowing deriving from it a program in which the states of the artificial system can be modeled in terms of states-actions. The technics and advantages brought by this proposed method will be reviewed through the illustration of two studies: the first one focusing on inclusion processes in younger children, the second one on the endowment effect within a sample of adults.

In this experiment, a humanoid robot (NAO), for the first time, replaces the experimenter to study the endowment effect that describes the fact that individuals prefer an object or a service that belongs to them over an equivalent object or service. The traditional methodology used to observe the endowment effect was based on a simple experimental exchange paradigm. The effect is measured along the proportion of participants reluctant to accept the exchange. This robust effect of endowment is considered in the economic literature as a serious decisional bias that seems to exist since the younger age. Two explanations have been advanced in the literature. The first explanation refers to the aversion to the loss that individuals would have as it is detailed by the prospect theory. The second explanation, the most recent one, specifies that the willingness to possess is a consequence of the evolution. We propose an additional explanation; that social rules of the individuals can explain the reluctance to exchange an object or to prefer an object already possessed over the same object that these individuals do not possess. The paradigm of the exchange would implicitly favor a response in line with politeness norms at use in Western societies. In order to account for this third explanation, the use of NAO robot allows reproducing the exchange experimental paradigm in a neutral disambiguated context where the politeness norms are not prompted by the interaction experimenters/participants. This experiment concluded to no endowment effect. This procedure reveals a new paradigm to understand the emergence of social norms at play in an interaction robot-human researching what “behaviors” programmed in NAO triggers an endowment effect and favors the emergence of politeness norms.