The Competence of Learning Companion Agents

One recent approach in developing computer-based learning environments advocates the idea of creating a social context inside the computer. It is claimed that when the learner is engaged into a meaningful dialogue with the software actors his/her learning will benefit. In this paper we concentrate on the collaboration with artificial social actors as peer learners. How ”able” should the learning companion agent be in order to maintain the motivation of the human learner to collaborate? It has been argued that “too strong” or “too weak” companion agents may frustrate the human learner to quit the collaboration altogether. This paper describes an empirical study where the learner is able to work with several artificial learning companions both strong and weak ones. Our empirical data deals with young school children working on elementary mathematics. On the basis of this study we put forward that a group of heterogeneous companion agents at the learner’s disposal will increase his/her motivation to collaborate with the agents. This study also suggests that besides the competence of the learning companion agents it is essential to pay special attention to the personal voice of the companion agents in order to keep the human learner interested.