Kazuhisa Miwa

Nagoya University, Nagoya-shi, Aichi-ken, Japan

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Publications (64)3.44 Total impact

  • 11/2013; 29(1).
  • 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.
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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.
  • 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.
  • 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. · 2.27 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: 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.
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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 01/2012; · 1.16 Impact Factor
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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.
    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: 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: Development of a Web-based Production System for Introductory Cognitive Science Classes
    Transactions of the Japanese Society for Artificial Intelligence 01/2011; 26:536-546.
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    Yugo Hayashi, Kazuhisa Miwa
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    ABSTRACT: A psychological experiment was conducted to capture the nature of Human-Human and Human-Agent Interactions where humans and computer agents coexist in a collaborative environment. Two factors were manipulated to investigate the influences of the ’schema’ about and the ’actual partner’ on the characteristics of communication. The first factor, expectation about the partner, was controlled by the experimenter’s instruction, manipulating with which partner (human or computer agent) participants believed to be collaborating. The second factor, the actual partner, was controlled by manipulating with which partner (human or computer agent) participants actually collaborated. The results of the experiments suggest that the degree of the refinement of the conversation controlled as the actual partner factor affected the emotional and cognitive characteristics of communication; however the schema about the opponent only affected the emotional characteristics of communication.
    Human-Computer Interaction. Ambient, Ubiquitous and Intelligent Interaction, 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Proceedings, Part III; 01/2009
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    ABSTRACT: The present study investigates participant learning processes in a cognitive science introductory class. The participants engaged in three sequential cognitive modeling tasks with a web-based production system that has several functions for helping individual learning of cognitive modeling. We analyzed the requests sent to the system's server during the period of the class (71 days) and confirmed the following: (1) increase of the number of the requests from the first to final tasks; (2) changes of the modeling processes along with the development of learning; and (3) significant correlations between the changes of the modeling processes and subjective evaluations of the achievements of the final task.
    01/2009;
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    ABSTRACT: 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.
    Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, Proceedings of the 14th International Conference on Artificial Intelligence in Education, AIED 2009, July 6-10, 2009, Brighton, UK; 01/2009
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    ABSTRACT: In learning cognitive science, students must learn how to handle an actual production system that runs on a computer. We developed a web-based production system for education that can be used from anywhere such as class rooms, offices, and homes. It furnishes students with learning support information for if-clause matching to facilitate learning. We confirmed that the learning support function effectively reduces participant trial-and-error behaviors based on empirical data. In this paper, we developed a learning support system for beginners of cognitive science to learn the model-based approach. This system is a web-based production system that can be used whenever and from anywhere by the Internet and offers a production system that can be easily used in introductory cognitive science classes in higher education. Our web-based learning support system absorbs the differences of computational facilities in learning environments. Users can experience model construction using the production system whenever and from anywhere (e.g., classrooms and homes) by accessing a web server using a browser without installing any particular software. From the viewpoint of instructors, since a fundamental learning environment is established only by providing personal computers connected to the Internet, a web-based application can lower the barriers for introducing the model-based approach into introductory cognitive science classes. Our system is expected to support not only students but also teachers. This paper describes our production system's advantages by establishing it as a web-based application and the system's characteristics as a learning support system. We also examine its utilities through a human experimentation.
    01/2009;
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    Kazuaki KOJIMA, Kazuhisa MIWA
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    ABSTRACT: Problem posing is identified as an important activity in mathematics education as well as problem solving is. While problem solving is a comprehension task, problem posing is regarded as a production task because it requires diverse thinking and generation of novel ideas in some ways. In problem posing, it is important but difficult for learners to generate diverse problems. In this study, we propose a strategy for learning from examples in problem posing in order to promote diverse problem posing by learners. We introduce an activity of imitation that is widely adopted in domains of creative generation tasks. We also implement a system that supports learning by imitation in a task of posing mathematical word problems. Our system presents a learner with cases of problems and their generation processes, and it then has the learner engage in reproducing cases by following the processes.
    01/2009;
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    ABSTRACT: Satoshi Hirose (hirose@cog.human.nagoya-u.ac.jp) Abstract We performed an experiment where participants engaged in the Prisoner's Dilemma game either with a human or a computer agent. In the experiment, we controlled two factors: (1) expectation about a partner, i.e., whether a partner is believed to be a human or computer agent, and (2) actual partner's behavior, i.e., whether (a) a partner performs with human-like sophisticated behavior or (b) simple mechanical behavior. Participant decision-making behavior showed that their defect actions greatly increased when instructed that their partner was a computer agent; the effect of the actual partner's behavior was limited. Personality impression tests showed that the partner's individual desirability correlated to the number of times defected by the partner, but the partner's social desirability correlated to the number of defect actions that the participants offered. Our conclusion is that humans actually generate social relationships with computer agents, as the Media Equation studies have insisted; however these relationships are relatively different from those with humans.
    01/2008;
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    Kazuaki Kojima, Kazuhisa Miwa
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    ABSTRACT: Problem posing is identified as an important activity in mathematics education. In problem posing, it is important but difficult for learners to generate diverse problems. In this study, we examine a method and implement a system for facilitating learners' diverse thinking in the task of posing mathematical word problems. Since we focus on an aspect of problem posing as a creative generation task, we utilize the presentation of problems as cases in supporting problem posing. We experimentally investigate the diversifying effect of presenting cases while controlling similarities and then implement a support system for problem posing that can present various cases. We also conduct experimental evaluations to verify the effectiveness of our system.
    I. J. Artificial Intelligence in Education. 01/2008; 18:209-236.

Publication Stats

99 Citations
3.44 Total Impact Points

Institutions

  • 2001–2012
    • Nagoya University
      • Graduate School of Information Science
      Nagoya-shi, Aichi-ken, Japan
  • 2008
    • Tokyo Denki University
      Edo, Tōkyō, Japan
  • 2007
    • Aichi University of Education
      Kariya-chō, Aichi, Japan