This study aims to investigate the characteristics of effective interaction between a therapist and his/her child client with autism spectrum disorder during a session of occupational therapy. Four sessions were video-recorded and analyzed, including one conducted by a novice therapist and three by expert therapists. Three children with autism spectrum disorder who were able to take part in everyday conversations also participated in this study. In study 1, we coded the therapists’ utterances according to their function in the context through a session. In study 2, we segmented the video-recording of a session based on the goal of child behavior, recorded the therapists’ physical support, and examined not only the temporal relationship between the therapists’ utterances and physical support but also the children’s proactive behavior. The results indicated that the expert therapists appropriately provided attentive utterances and physical support according to the children’s actions. We discuss a new and useful framework for understanding therapist support and children with developmental disabilities.

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 This study aims at revealing the process and mechanism of meta learning in acquiring expertise in the field of insight problem solving. We gave a participant a series of ten geometric insight problems and analyzed the processes microscopically. During solving a series of problems, the participant’s performance was greatly improved. This improvement seems due to three factors. The first factor is increasing variety of combination patterns. The second factor is increasing appropriateness of evaluation, which enables the participant to quickly discriminate feasible trials from unfeasible ones. The third and most important factor is distribution of problem solving load to the environment. Instead of memorizing the goal pattern and mentally evaluating the fitness of a current combination pattern to the goal, the participant recruits external resources on the spot to offload the cognitive burden. These mechanisms are very different from elaborating and sophisticating individual operations. Rather, they contribute to establish the meta level knowledge that enables the participant to improve his performance.

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 Recent research has indicated that people spontaneously infer traits from observed behaviors and use these traits to predict the actor’s future behaviors. The construal level theory contends that the spontaneous trait inference (STI) would more likely occur as the psychological distance (in terms of temporal or spatial dimensions) from the behavioral events increases. In the present study, we conducted four experiments to investigate what happens if psychological distance changes between the time of observation and prediction. It was shown that once participants made an STI from observed behaviors elicited by a distant actor, they continued to rely on the STI to make behavioral predictions even if the temporal distance from the actor changed from far to near (Experiment 1a). On the other hand, they did make behavioral predictions in terms of an implied trait when the temporal distance changed from near to far, though they had hardly formed an STI at the time of observation (Experiment 1b). The results were somewhat different in the dimension of spatial distance. Participants inhibited the use of initially inferred traits for behavioral predictions when the spatial distance changed from far to near (Experiment 2a). However, participants were unresponsive when the spatial distance changed from near to far (Experiment 2b). These results suggest that people are capable of shifting construal levels (abstractness) and reinterpreting behavioral events according to the changes in psychological distance from the actors, but the underlying mechanisms are somewhat different across the temporal and spatial dimensions.

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We can imagine anything — not just an object at our hand, but also something we have never seen in our life, such as a dragon, number, heaven, and so on. In this article, we discuss a potential methodology to characterize such imagination as a conscious process, which we cannot sufficiently associate to the corresponding external stimuli. As one of such conscious processes, here we take reading of text, in which the reader construct a rich imaginary world along the storyline from looking at a quite limited visual stimulus, namely just a series of letters on a text. In particular, in the state of absorption, the reader often feels oneself into the imaginary world as a character. By reviewing past research on the absorption in reading, we propose a hypothesis, in which both conscious process itself and something in the conscious experience are objects, that is defined by the consistency between its intention and extension (inductive and deductive way of definition). In this hypothesis, difference between absorption and non-absorption is considered analogously as difference in the point of view of an object in consciousness. On the basis of the prediction of this hypothesis, we discuss empirical tests on our hypothesis.

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 In this paper, the author presents a new research area called “narratology of narrative generation” that covers humanities, such as narratology, information sciences, including artificial intelligence and cognitive science, and social sciences, such as economics. The narratology of narrative generation is also called “post-narratology” in the sense that it shows various possibilities or a vision of a novel narratology using narrative generation machines. The first and second sections show the importance of narrative generation and discusses approaches to the narratology of narrative generation or post-narratology by dividing into several themes, including narrative genres and the necessity of cultural narratology. The third section provides a part of the recent narrative generation studies. In the fourth section, the author overviews a basic framework for showing narrative communication structures and discusses the correspondence relations between various elements in a narrative generation process and the implementation methods, theories and techniques based on artificial intelligence and cognitive science.

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