Kazuhisa Miwa

Nagoya University, Nagoya, Aichi, Japan

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Publications (73)9.56 Total impact

  • Akihiro Maehigashi, Kazuhisa Miwa
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    ABSTRACT: When people engage in a task, they often take preliminary actions (preprocessing) to simplify primary processing. Usually, a trade-off is made between the costs of preprocessing and primary processing. We conducted three experiments to find out whether people could adaptively estimate the utility of preprocessing depending on the task situation. The result demonstrated that in performing a high-complexity task, almost all the participants reduced their overall task performance cost by conducting cost-adaptive preprocessing. However, for a low-complexity task, participants tended to conduct preprocessing even though this increased overall task performance cost. Based on these results, we discuss human nature from the viewpoint of the influence of cognitive effort.
    Japanese Psychological Research 07/2015; DOI:10.1111/jpr.12087 · 0.33 Impact Factor
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    ABSTRACT: Data interpretation based on theory is one of most important skills in scientific discovery learning, but to achieve this process is difficult for learners. In this study, we propose that model construction and execution could support data interpretation based on theory. We used the web-based production system ``DoCoPro'' as an environment for model construction and execution, and we designed and evaluated class practice in cognitive science domain to confirm our ideas. Fifty-three undergraduate students attended the course in Practice 1 in 2012. During class, students constructed a computational model on the process of semantic memory and conducted simulations using their model from which we evaluated any changes in learner interpretation of experimental data from pretest to posttest. The results of comparing pretest with posttest showed that the number of theory-based interpretations increase from pretest to posttest. However, we could not confirm the relationship between students' interpretations and their mental models acquired through learning activities and whether the students could transfer their understanding of theory to other different experimental data. Therefore, we conducted Practice 2 in 2013, in which 39 undergraduate students attended the course. Instruction in Practice 2 was same as in Practice 1. We improved pretest and posttest to assess students' mental model of theory and whether they transfer their understanding to another experiment. Comparing the pretest and posttest results showed that students acquired more sophisticated mental models from pretest to posttest, and they could apply their understanding of theory to their interpretations of near transfer experimental data. The results also indicated that students who shifted their interpretations from non theory-based to theory-based acquired more superior mental models on theory. Finally, we discuss applicability of our findings to scientific education.
    Transactions of the Japanese Society for Artificial Intelligence 01/2015; 30(3):547-558. DOI:10.1527/tjsai.30.547
  • Jun Ichikawa, Kazuhisa Miwa, Hitoshi Terai
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    ABSTRACT: For skill acquisition that needs periodic body movements as cascade juggling, the establishment of stable body movements seems crucial. We investigated them in each of the learning stages defined by the Beek and van Santvoord (1992) framework. In addition, we investigated participants' verbal reports about what was intentionally concerned for achieving optimum learning in practice. In the experiment, novices practiced three-ball cascade juggling over a period of one week. We focused on two types of stabilities: the stability of chest movement representing torso movement, and another stability of wrist movement representing arm swing. The result revealed that the skills for establishing stabilities of torso movement and arm swing were acquired sequentially. In this case, the stability of arm swing emerged between Stage 2 (by 50 successive catches) and Stage 3 (by over 100 successive catches), and another stability of torso movement emerged between Stage 3 and the expert stage in which jugglers had acquired complete skills for performing five-ball cascade juggling. The result also showed that in the establishment of stable arm swing, the development of the stability occurred only in passive catching behavior, but did not in active tossing behavior. Additionally, we found that the participants who did not develop beyond Stage 1 (by 10 successive catches) trained themselves while focusing on their specific physical movements.
    Transactions of the Japanese Society for Artificial Intelligence 01/2015; 30(3):585-594. DOI:10.1527/tjsai.30.585
  • Kazuhisa Miwa, Hitoshi Terai, Shoma Okamoto
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    ABSTRACT: We developed a learning environment to support participants' problem posing in a formal logic system, natural deduction, by combining problem-posing and problem-solving activities. In the problem posing-phase, the participants posed original problems and presented them on a shared problem database called ``Forum,'' which was accessible to other group members. During the problem-solving phase, the participants solved the problems presented on Forum. This first round of problem posing and solving was followed by a second round of problem posing. We performed two practices: one for undergraduates in a liberal arts college and the other for graduates in a graduate school of information science. The results showed that the participants successfully posed more advanced problems in the second round of problem posing as compared to the first. The empirical data gathered from the two practices indicated a significant relationship between problem-solving and problem-posing abilities.
    Transactions of the Japanese Society for Artificial Intelligence 01/2015; 30(3):526-535. DOI:10.1527/tjsai.30.
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    ABSTRACT: When people understand an object, they construct a mental model of the object. A mental model is a structural, behavioral, or functional analog representation of a real-world or imaginary situation, event, or process. We conducted a class practice in which newcomers to cognitive science constructed a mental model by implementing and simulating a computational model of cognitive information processing, i.e., a cognitive model. We quantitatively evaluated the learning outcomes of the class. The participants were required to implement a complete cognitive model of subtraction processing. Furthermore, they were required to implement bug models, which are cognitive models with bug rules that cause several types of errors. Pre- and post-tests were performed before and after implementing and using these models, respectively. The results indicate that the class intervention led to the increase of the number of the participants who constructed the correct mental model and promoted more accurate mental simulations. However, the significant effects were confirmed only with participants who correctly completed the bug model, but the effects were limited with those who failed.
    Transactions of the Japanese Society for Artificial Intelligence 01/2015; 30(3):536-546. DOI:10.1527/tjsai.30.536
  • Transactions of the Japanese Society for Artificial Intelligence 11/2013; 29(1). DOI:10.1527/tjsai.29.148
  • Hitoshi Terai, Kazuhisa Miwa, Kazuaki Asami
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    ABSTRACT: The Remote Associates Test (RAT) is one of the most popular tasks in experimental studies of insight in psychological and neuroscience studies. Since the RAT was originally developed for English-speaking countries, we developed a Japanese version of the RAT. This paper provides a brief overview of the structure of the task based on chunk decomposition using Japanese kanji characters and a list of sets of words as experimental stimuli, with representative data for experimental studies of insight.
    Shinrigaku kenkyu: The Japanese journal of psychology 10/2013; 84(4):419-28. DOI:10.4992/jjpsy.84.419
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    ABSTRACT: Problem posing, by which learners create new problems by themselves, is an important activity in mathematics education. However, novice learners have difficulty in posing problems, particularly when formulating appropriate solution structures of problems. Although they are provided with example problems that can serve as hints for composing novel problems, they do not necessarily understand the key ideas used to generate the examples. To improve problem posing for novices, this study discusses an approach that supports learning from examples as a production task. We propose a method of learning from examples through imitation, where a learner reproduces problems identical to given examples. We implement a system that presents examples of problem posing and supports learners in understanding the examples by having the learners reproduce them. We conducted an experimental evaluation in which learners learned from an example that embeds useful ideas to alter solution structures in the system. The results demonstrated that the learners successfully adapted the example when posing their own problems if they learned the example by the reproduction method. Thus, learning from examples through reproduction appears to be effective in the domain of problem posing as a production task.
    International Journal of Artificial Intelligence in Education 10/2013; 22(4):161-190. DOI:10.3233/JAI-130035
  • IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences 01/2013; E96.A(7):1625-1636. DOI:10.1587/transfun.E96.A.1625 · 0.23 Impact Factor
  • Nana Kanzaki, Kazuhisa Miwa
    Japanese Journal of Educational Psychology 01/2013; 61(2):121-132. DOI:10.5926/jjep.61.121 · 0.09 Impact Factor
  • Nana Kanzaki, Kazuhisa Miwa
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    ABSTRACT: The comprehension of graphs is achieved through interaction between bottom-up and top-down processing. This study experimentally investigated the interaction between the graph representations determining bottom-up processing and the reader's perspective relating to top-down processing. Different representations on graphs generated from an identical data set elicited different interpretations of the graphs. We call this the "representation effect" on graph comprehension. In Experiment 1, we confirmed the characteristic of the bottom-up process of graph comprehension by using a set of line graphs which were identical in perceptual characteristics. In Experiments 2A and 2B, the participants were given a perspective for reading the graphs, and then they interpreted the graphs. The results showed that this perspective affected their comprehension of the graphs. Previous studies have shown that top-down processing may not be compatible with bottom-up processing in graph comprehension. However, our result indicated that top-down processing controlled by a perspective for reading the graph was not inconsistent with bottom-up processing, and therefore does not violate bottom-up processing.
    Shinrigaku kenkyu: The Japanese journal of psychology 08/2012; 83(3):163-73. DOI:10.4992/jjpsy.83.163
  • Kazuhisa Miwa, Hitoshi Terai
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    ABSTRACT: Participants engaged in the Prisoner’s dilemma game with a partner through a computer terminal. We define two types of partner: a perceived partner and an actual partner, and manipulated the two factors independently. A perceived partner means a partner with whom participants imagined themselves to be interacting; instruction given by an experimenter controls the image of the perceived partner. An actual partner can change its behavior. In one scenario participants actually interacted with a human partner, in another scenario their partner was either a mostly cooperating computer agent or a mostly defecting computer agent. Three experiments were performed. The result suggested that the participants’ selection behavior was largely influenced by the instruction given about the partner by the experimenter and not influenced by the partner’s actual behavior. The analysis of the participants’ impressions of the partner showed that the effect of instruction about the partner disappeared. Individual likeability for a partner was very influenced by the partner’s behavior; as the participants incurred more defect actions from the partner, individual likeability for the partner decreased. On the other hand, social likeability for a partner was not so influenced by the partner’s behavior, but rather related to the participants’ own behavior. The participants who made more defect actions rated their partner’s social likeability lower.
    Computers in Human Behavior 07/2012; 28(4):1286–1297. DOI:10.1016/j.chb.2012.02.012 · 2.69 Impact Factor
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    ABSTRACT: We investigated whether students behave adaptively in hint-seeking from the viewpoint of self-fading. To let students effectively learn, scaffolding should be eliminated gradually with the progress of learning. We define self-fading as fading behavior lowing the levels of support by students themselves. We investigated the relation between such metacognitive behavior and learning effects through two experiments in a laboratory setting and in actual class activities. The results showed that our participants successfully faded help supports, and also confirmed that those who lowered the levels of support and learned with their own efforts gained larger learning effects.
    Proceedings of the 11th international conference on Intelligent Tutoring Systems; 06/2012
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    ABSTRACT: Cognitive modelling is one of the representative research methods in cognitive science. It is believed that creating cognitive models promotes learners’ meta-cognitive activities such as self-monitoring and reflecting on their own cognitive processing. Preceding studies have confirmed that such meta-cognitive activities actually promote learning effects. However, there are some difficulties in bringing about learning by creating cognitive models in an educational context. To overcome the difficulties, we propose an innovative learning design, ‘learning through intermediate problems’ and also developed a web-based production system called DoCoPro that can be used anywhere and anytime in an environment connected to the Internet. We performed three introductory cognitive science classes in which the participants learned cognitive modelling and constructed running computer models using our system. In the first and second classes, the participants were required to construct production system models that solve pulley problems. They also posed their original pulley problems that their own models were subsequently able to solve. These generated problems were distributed to the other members. The participants were able to find incompleteness in their cognitive models, revise them to remove the incompleteness, and improve their models while solving the given problems. The participants, by successfully creating sophisticated models, acquired a deeper knowledge of the learning domain. The class practices confirmed the utility of ‘learning through intermediate problems’ when constructing an educational environment for learning creating cognitive models. In the third class, the participants constructed cognitive models solving addition and subtraction problems using DoCoPro. The cognitive processing underlying such problem solving is automated, therefore it may be difficult to verbalize and externalize such cognitive processes. The post-questionnaire showed evidence that the participants actually performed meta-cognitive activities while monitoring their own internal information processing.
    Interactive Learning Environments 05/2012; DOI:10.1080/10494820.2012.666668 · 1.16 Impact Factor
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    ABSTRACT: We constructed an innovative experimental platform to study cross-situational consistency in driving behavior, conducted behavioral experiments, and reported the data obtained in the experiment. To discuss cross-situational consistency, we separated situations in which people use some systems to conduct tasks into three independent conceptual factors: environment, context, and system. We report the experimental results with the following systems: a laboratory system with a gaming controller and steering/pedal controllers and a real system, COMS an instrumented vehicle. The results are summarized as follows. 1) The individual behaviors in each system were stable, and consistency was retained. 2) The consistency of the behaviors was also confirmed when the participants drove using different interfaces in identical systems. 3) However, only slight correlation was observed across different systems in a specific situation where a strong high-order cognitive constraint (i.e., rapid driving) and a weak low-order cognitive constraint (driving with easy handling toward a straight-line course) were given.
    Work 01/2012; 41:1471-1476. DOI:10.3233/WOR-2012-0340-1471 · 0.52 Impact Factor
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    ABSTRACT: We designed and practiced a cognitive science class for graduate students. In the class, the participants were required to build three cognitive models: a bug model, a trace model, and an individual model. In the construction of the bug model, the participants learn to construct a cognitive model by monitoring their mental processing. The participants confirmed that the trace model can explain human normative behavior; and also understood that the individual model can explain various patterns of human behavior that are generated by different problem solving strategies. The post questionnaire analysis shows that the participants successfully understood various aspects of advantages of the mode-based approach in cognitive science and important features of human cognitive processing.
    Transactions of the Japanese Society for Artificial Intelligence 01/2012; 27(2):61-72. DOI:10.1527/tjsai.27.61
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    ABSTRACT: In this study, we experimentally investigated human use of automation systems and the selection strategies of such usage. We used two different types of tracking tasks. As a result, we found that the participants neither tended to misuse nor disuse the automation system. Also, we confirmed that they tended to select to use the automation system depending on their manual performance rather than the system performance. Moreover, we found that there is a relationship between the tendency to use the automation system and the selection strategy.
    Human-Computer Interaction. Users and Applications - 14th International Conference, HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part IV; 01/2011
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    ABSTRACT: Small talk can be used in order to build a positive relationship towards a virtual character. However the choice of topics in a conversation can be dependent on social background. In this paper, we explore culture-related differences in small talk for ...
    Intelligent Virtual Agents - 11th International Conference, IVA 2011, Reykjavik, Iceland, September 15-17, 2011. Proceedings; 01/2011
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    ABSTRACT: An experiment was conducted to capture characteristics of Human-Agent Interactions in a collaborative environment. The goal was to explore the following two issues: (1) Whether the user’s emotional state is more stimulated when the user has a human schema, as opposed to a computer agent schema, and (2) Whether the user’s emotional state is more stimulated when the user interacts with a human-like ECA (Embodied Conversational Agent), as opposed to a non human-like ECA or when there is no ECA. Results obtained in the experiment suggest that: (a) participants with a human schema produce higher ratings, compared to those with a computer agent schema, on the emotional (interpersonal stress and affiliation emotion) scale of communication; (b) A human-like interface is associated with higher ratings, compared to the cases of a robot-like interface and a no ECA interface, on the emotional (e.g., interpersonal stress and affiliation emotion) scale of communication.
    Human-Computer Interaction. Interaction Techniques and Environments - 14th International Conference, HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part II; 01/2011
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    ABSTRACT: Automation is a necessity in modern society. People sometimes are inclined to trust automation too much. On the other hand, they sometimes tend to not be willing to use automation. To prevent these mistakes, this study explores factors of reaching an appropriate reliance on automation systems by using cognitive modeling. We have conducted psychological experiments on this problem using a simple line-tracing (driving) task where the participants had to track the line with a circle by pressing the arrow key on the keyboard (manual control) or rely on automation (auto control). They could switch between auto and manual control during the task. The success probabilities of each control mode were systematically varied. The ACT-R model that simulates these experiments was constructed by representing the reliance on the automation as utilities of rules. The model performs this task by firing rules that manage the perceptual/motor modules. The perceptual module finds and attends to the vehicle and the road on the screen, and the motor module press the keys depending on the current controlling modes or the current positional relation between the vehicle and the road. The utilities of these rules are updated based on the rewards in every screen update. This utility module is also compatible to a previous computational model of automation reliance. A preliminary run of this model simulated several qualitative features of the behavioral data. The ways it does not fit suggest that the model should be more sophisticated in its representation of space and process.