Recent technological advances have introduced autonomous mobile robots into public areas that were previously occupied only by pedestrians. When pedestrians and mobile robots coexist, the collision avoidance algorithm in which the robots can reach their goals without causing collisions or significant delays is important. One approach is to incorporate human sensation into the avoidance algorithm, and the braking index representing human braking sensation in two-dimensional environments was developed. The goal of this study was to verify whether the collision avoidance algorithm based on the braking index could work efficiently in a congested environment using agent simulations. The results showed that agents using the avoidance algorithm with the braking index achieved smoother and safer movement than those without it in a congested environment. Additionally, we found a traditional traffic density-flow relationship between congestion and movement smoothness. This finding implies that this relationship could be applied to two-dimensional environments, such as shopping malls or airports.

Smooth and safe interactions between pedestrians and Autonomous Mobile Robots (AMRs) are crucial for integrating robotic systems into shared environments. Previous studies on external Human-Machine Interfaces (eHMIs) often employed static information presentation, neglecting dynamic interaction contexts. This study investigates the effectiveness of gaze-based nudge-intuitive and unconscious communication via gaze behavior—in facilitating pedestrian role selection (leader or follower) during perpendicular crossing interactions with AMRs. Virtual reality (VR) experiments using Unity and Cybershoes are conducted to evaluate two gaze patterns generated by the AMR: ‘Leader’s gaze’, a brief gaze directed toward pedestrians in the early stages of interactions, and ‘Follower’s gaze’, a gaze keeping track of pedestrians throughout the interaction until crossing completion. The impact of gaze timing (Early/Late) and initial positional relationships between pedestrians and AMRs (initial ∆TTCP) are systematically analyzed. The results indicate that gaze nudging significantly enhances pedestrians’ subjective ratings of safety, smoothness, and understanding of the robot’s intention compared to no-gaze conditions. Leader’s gaze effectively encourages pedestrians to adopt the follower role under conditions favoring AMR priority (small or negative ∆TTCP), whereas Follower’s gaze promotes pedestrians to adopt the leader role under conditions naturally favoring pedestrian priority (larger ∆TTCP). Additionally, the effectiveness of gaze nudging strongly depends on interaction timing, with early-stage gaze presentations exhibiting greater influence. These findings confirm the potential of gaze-based nudging as a non-intrusive, context-sensitive strategy for pedestrian-AMR interactions, emphasizing the importance of precisely timed gaze presentations for facilitating pedestrians’ natural and intuitive role selection.

This study examines the effects of self and other's intentions on their moving performance in crossing interactions with multiple agents. An experimental task paradigm was developed to verify self and other's effects simultaneously. Different intentions were assigned to self and other in the 2-person crossing situation and to the minority and majority in the 4-person crossing situation. Further, performance was assessed based on completion time, amount of operations, and interruptions. The results show that the effects of self-intention on self-performance were generally found, but the minority's intention does not affect its interruption. For completion time and operation, the effect of other's intention decreased in the order of the self in the 2-person crossing situation, minority, and majority in the 4-person crossing situation. Noteworthy, for the interruption, the other's intention affected the majority's interruption, but it did not affect the minority's interruption. These findings emphasize the significance of simultaneously considering self and other's intentions simultaneously when analyzing crossing interactions in shared space.

Safety and acceptability are the main concerns in the design of driver assistance systems. However, these two requirements sometimes conflict with each other depending on the situation and the driver. This conflict is particularly emphasized in the case of elderly drivers. To solve this problem, this paper proposes a driver-vehicle cooperation scheme, an "instructor-like assisting control" consisting of model predictive constraint satisfaction and a multi-modal human-machine inter-face. The proposed assisting scheme is expected to improve the drivers’ inherent driving characteristics, which is recognized as a "coaching effect" in cognitive science. This effect was verified by long-term experiments over one month using a driving simulator.

Literature on education has paid considerable attention to computational thinking (CT), thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent. Many attempts to develop CT in problem-solving education have been made in K-12 education. This study proposes an approach to foster CT in curricula for general undergraduate students: students construct rule-based computational models of problem solving. We empirically investigated effects of construction of a rule-based model on externalizing a solution in problem-solving in terms of problem decomposition, one aspect of CT. Undergraduate students described knowledge required to solve a simple problem in the format of rule-based models before and after they constructed models of the problem for a production system. Results indicate that model construction improved student decomposition in knowledge externalization of the solution.

For practice-based science education, the authors developed a cognitive simulator that demonstrates the human memory process and simulates the serial position effect in different experimental situations. Our cognitive simulator as a learning tool is established on the basis of the dual storage model; it visualizes the items stored in the short-term and long-term memories. The participants learn how the model works while confirming which items are rehearsed in the short-term memory, encoded into the long-term memory, or overflowed from the memory. We designed and performed practice-based psychological training through two university class sessions of the author’s cognitive science class. The results of the practice showed that participants’ data interpretation and data prediction were improved through class activities. More specifically, the participants explained the observed data using naïve concepts prior to the learning phase, but they subsequently explained them using theoretically defined concepts of the dual storage model. Further more, the participants were successfully guided to predict the experimental results more accurately by the learning activities using the cognitive simulator.

Interpreting experimental data based on a psychological theory requires understanding the mechanisms or factors underlying cognitive processes and acquiring an attitude for interpreting evidence from a theoretical perspective. In this study, we designed and practiced teaching and learning activities using cognitive models to foster both requirements in an introductory course of cognitive science. Fifty-three undergraduate students attended the course. During practice, students constructed a computational model on the process of semantic memory and conducted simulations using their model. We evaluated changes in learner interpretation of experimental data from pretest to posttest. The results of the practice showed that students’ interpretations of experimental results for semantic memory changed from pretest to posttest. However, their interpretations of the results of other experiments did not show much difference between pretest and posttest.

We present an intelligent tutoring system that teaches natural deduction to undergraduates. Our system was implemented on a client-server framework. An expert problem solver in the system provides basic instructional help, such as suggesting the use of a rule in the next step of solving a problem and indicating the inference drawn by applying the rule. Students learning with our tutoring system can vary the degree of help they receive (from low to high and vice versa). Empirical evaluation showed that the system enhanced the problem-solving performance of participants during the learning phase, and these performance gains were carried over to the post-test phase.

Problem posing is identified as an important activity in mathematics education. Although it is difficult for novice learners to pose diverse problems, they must do so. Such novices particularly have difficulty in appropriately composing mathematical structures of solutions when posing new problems. This paper discussed and experimentally studied an approach to support learning of problem posing as a production task. We designed support for learning by imitation of examples, in which learners reproduce problems presented as examples. That is expected to facilitate learners’ understanding ideas used in generation of the examples, and to stimulate new idea generation in learners’ own problem posing. We then verified the effects of learning an example through imitation, with the results indicating that learning by imitation can facilitate adaptation of ideas used in an example into learners' problem posing, whereas it cannot necessarily facilitate appropriate problem posing when they try to diversify.

We experimentally investigated the assistance dilemma with a learning system that can control levels of support (LOS). Our system supports learning of natural deduction (ND) and was established based on the client-server framework. An experiment was performed. In the first, half of the participants learned ND in the high LOS condition, and the other half learned in the low LOS. In the learning phase, the solution time was shorter and the trial and error steps until solution were greater in the high LOS group than in the low LOS group. However, in the posttest, more participants successfully reached the solution in the low LOS group.

In the learning of problem posing, even though it is difficult for learners to generate diverse problems by associating and combining various situations expressed in problem texts and mathematical structures of solutions, they must do so. To design supporting methods for expanding the variety of problems, it is crucial to understand the types of problems that learners have difficulty in posing, and to draw crucial elements to facilitate diverse problem posing. We conducted an experimental investigation to obtain the empirical data of the variety of mathematical word problems posed by novice participants. The results indicated that the participants posed only a few problems that had situations identical to and solutions different from given base problems. It was also revealed that the problems constructed by the participants based on their own ideas were relatively simple and inappropriate. These results suggest that idea generation support for constructing solution structures of problems is effective in expanding the variety of problem posing.

The authors have developed a web-based production system that users can use whenever and anywhere by the Internet. The authors held two cognitive science introductory classes with the system. In our class activities, participants were required to construct running cognitive models on the production system architecture that can solve pulley problems. The participants not only constructed cognitive models but also produced original problems, which were distributed to the other class members. The participants found the defects in their models while trying to solve the problems from other members and trying to improve their models. A posttest indicated that the participants who successfully constructed high performance models revealed deeper understanding of pulley systems.

In this study, we design a learning environment to foster participants' creative attitude and evaluate its effectiveness in a university class. Our educational program consists of the following three phases: (1) introduction (studying the basics of Mindstorms used as a tool), (2) creative activities (producing playground equipment using Mindstorms), and (3) self-reflective activities on the creative processes (each group constructing a diagram describing their own creative processes and discussing the processes). We evaluate the effectiveness based on comparisons of pre- and post-tests and the contents of the participants' discussions. In particular, we confirm the following three learning activities: (1) the participants discussed their creative activities from various viewpoints, (2) they also discussed the viewpoints considered to be important for creative activities, and (3) they realized the importance of idea generation, idea embodiment, and collaboration in creative activities.

Prior studies of creativity, in the field of cognitive psychology, have mainly dealt with only the process of mentally thinking of ideas. We investigated, through a cognitive psychological experiment and its protocol analysis, experts' and novices' interactive process between the mental operation by which participants considered their ideas and the external operations by which they actually produced physical objects in creative activity. In our experiment, the participants were required to build a creative robot with LEGO Mindstorms. The experimental results showed that the experts could create work that fulfilled both high originality and practicality simultaneously. Moreover, the following four points were confirmed as characteristics of the experts' creative process: (1) the experts globally considered their initial ideas, (2) the experts reconstructed their ideas by considering comprehensively the relationship among the elements constructing their plans, (3) the experts reconstructed their ideas more actively, and (4) the experts were able to embody successfully their ideas by focusing on various aspects of important viewpoints.

We investigated, through a cognitive psychological experiment and its protocol analysis, human cognitive processes of seeking information on the WWW and the effects of a subject's knowledge and experience on the information seeking processes and performance. In our experiment, the subjects were divided into two groups: one comprising expert subjects and the other novice subjects. All subjects were given a general search task and a specific search task. In the experimental results, except for one exceptional subject, we could confirm significant differences between the two groups in the solution time, the number of pages searched, and the kind of pages accessed. We also propose a behavioral schema for tracing a subject's searching processes. The behavioral schema consists of four behavior levels on the WWW: search, results-of-search, page-following results, and page-following pages. Each subject's behavior was described as a transition of nodes, each representing the subject's behavioral state, and six kinds of operator connecting two nodes: search, link, return, jump, browse, and next among the four behavior levels. The results of an analysis using the schema showed distinctive subject behavior such as a breadth-first search or depth-first search.