Research of tutoring in parent-infant interaction has shown that tutors – when presenting some action – modify both their verbal and manual performance for the learner (‘motherese’, ‘motionese’). Investigating the sources and effects of the tutors’ action modifications, we suggest an interactional account of ‘motionese’. Using video-data from a semi-experimental study in which parents taught their 8- to 11-month old infants how to nest a set of differently sized cups, we found that the tutors’ action modifications (in particular: high arches) (...) functioned as an orienting device to guide the infant’s visual attention (gaze). Action modification and the recipient’s gaze can be seen to have a reciprocal sequential relationship and to constitute a constant loop of mutual adjustments. Implications are discussed for developmental research and for robotic ‘Social Learning’. We argue that a robot system could use on-line feedback strategies (e.g. gaze) to pro-actively shape a tutor’s action presentation as it emerges. (shrink)

This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these (...) capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots. (shrink)

Research of tutoring in parent-infant interaction has shown that tutors – when presenting some action – modify both their verbal and manual performance for the learner (‘motherese’, ‘motionese’). Investigating the sources and effects of the tutors’ action modifications, we suggest an interactional account of ‘motionese’. Using video-data from a semi-experimental study in which parents taught their 8- to 11-month old infants how to nest a set of differently sized cups, we found that the tutors’ action modifications (in particular: high arches) (...) functioned as an orienting device to guide the infant’s visual attention (gaze). Action modification and the recipient’s gaze can be seen to have a reciprocal sequential relationship and to constitute a constant loop of mutual adjustments. Implications are discussed for developmental research and for robotic ‘Social Learning’. We argue that a robot system could use on-line feedback strategies (e.g. gaze) to pro-actively shape a tutor’s action presentation as it emerges. (shrink)

The paper investigates the effects of a humanoid robot’s online feedback during a tutoring situation in which a human demonstrates how to make a frog jump across a table. Motivated by micro-analytic studies of adult-child-interaction, we investigated whether tutors react to a robot’s gaze strategies while they are presenting an action. And if so, how they would adapt to them. Analysis reveals that tutors adjust typical “motionese” parameters. We argue that a robot – when using adequate online feedback strategies – (...) has at its disposal an important resource with which it could proactively shape the tutor’s presentation and help generate the input from which it would benefit most. These results advance our understanding of robotic “Social Learning” in that they suggest a paradigm shift towards considering human and robot as one interational learning system. Keywords: human-robot-interaction; feedback; adaptation; multimodality; gaze; conversation analysis; social learning; pro-active robot conduct. (shrink)

Social robots are designed to interact with humans. That is why they need interaction models that take social behaviors into account. These usually influence many of a robot’s abilities simultaneously. Hence, when designing robots that users will want to interact with, all components need to be tested in the system context, with real users and real tasks in real interactions. This requires methods that link the analysis of the robot’s internal computations within and between components with the interplay between robot (...) and user. This article presents Systemic Interaction Analysis as an integrated method to derive prototypical courses of interaction based on system and interaction level, identify deviations from these, infer the causes of deviations by analyzing the system’s operational sequences, and improve the robot iteratively by adjusting models and implementations. Keywords: analysis tools, user studies, autonomous robots. (shrink)

Research of tutoring in parent-infant interaction has shown that tutors – when presenting some action – modify both their verbal and manual performance for the learner (‘motherese’, ‘motionese’). Investigating the sources and effects of the tutors’ action modifications, we suggest an interactional account of ‘motionese’. Using video-data from a semi-experimental study in which parents taught their 8- to 11-month old infants how to nest a set of differently sized cups, we found that the tutors’ action modifications (in particular: high arches) (...) functioned as an orienting device to guide the infant’s visual attention (gaze). Action modification and the recipient’s gaze can be seen to have a reciprocal sequential relationship and to constitute a constant loop of mutual adjustments. Implications are discussed for developmental research and for robotic ‘Social Learning’. We argue that a robot system could use on-line feedback strategies (e.g. gaze) to pro-actively shape a tutor’s action presentation as it emerges. (shrink)

The paper investigates the effects of a humanoid robot’s online feedback during a tutoring situation in which a human demonstrates how to make a frog jump across a table. Motivated by micro-analytic studies of adult-child-interaction, we investigated whether tutors react to a robot’s gaze strategies while they are presenting an action. And if so, how they would adapt to them. Analysis reveals that tutors adjust typical “motionese” parameters (pauses, speed, and height of motion). We argue that a robot – when (...) using adequate online feedback strategies – has at its disposal an important resource with which it could proactively shape the tutor’s presentation and help generate the input from which it would benefit most. These results advance our understanding of robotic “Social Learning” in that they suggest a paradigm shift towards considering human and robot as one interational learning system. Keywords: human-robot-interaction; feedback; adaptation; multimodality; gaze; conversation analysis; social learning; pro-active robot conduct. (shrink)