Research on communication between parents and children has shown that parents in a teaching scenario adapt the strategy of the conversation to the level of understanding of the learner. A key factor in this is the adjustments made in response to the child's attempt at imitation. Emphasising relevant aspects of a movement or task, as well as additional verbal explanations of details, are possible such adaptations. Another important aspect is the association with common past experiences that can be recalled by the child.
A purposeful learning scenario also requires that the child is able to recognise his or her gaps in knowledge and ask specifically for missing information or contexts that are missing for correct imitation. A dynamic interplay of learning is thus created between the teacher and the pupils, shaped equally by both parties [Centre for teaching and learning].
Our goal is to develop a framework that allows such a frame of interactions (Pragmatic Frame) between a human and a robot in a learning scenario.
It is relevant for the intuitiveness of the learning scenario that all natural means of communication, such as gesticulative and verbal communication, can be used.
How the different input modalities can be stored in a uniform format and made semantically retrievable are the crucial questions to be answered on the way to the Pragmatic Frame. The appropriate link to given detailed information is just as important here as the mapping of simultaneous information influences such as verbal and gestural input. Finally, the intuitiveness of the developed framework is also relevant and will be investigated.
This project is part of the Co-Constructive Task Learning project.
Click here for Manuel Scheibl's Gitlab repository.