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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Institute of Electrical and Electronics Engineers (IEEE)  

DOI： 10.1109/tlt.2020.2989776

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1007/s40593-018-0171-6

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Other Link： http://link.springer.com/content/pdf/10.1007/s40593-018-0171-6.pdf

Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

Willingness to Communicate (WTC) in a second language (L2) is believed to have a direct and sustained influence on learners’ actual usage frequency of the targeted language. To help overcome the lack of suitable environments to increase L2 learners WTC, our approach is to implement a WTC model based conversational agent. In this paper, we propose a dialogue management model based on set of communication strategies and affective backchannels in order to foster the agent’s ability to carry on natural and WTC friendly conversations with L2 learners. We expect that combining communication strategies with affective backchannels can empower conversational agents to the extent to effectively help L2 learners recover from eventual communication pitfalls and create a warm conversation atmosphere.

DOI： 10.1007/978-3-319-61425-0_40

Scopus

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Publishing type：Research paper (scientific journal)   Publisher：Asia-Pacific Society for Computers in Education  

Fostering creativity in programming tasks is a challenging endeavor, especially when working alone. Traditional programming environments often lack support for stimulating creative thinking and idea generation. This paper presents an interactive augmented reality (AR) system that aims to enhance creativity in Internet of Things (IoT) programming tasks. The proposed system leverages Interactive Evolutionary Computation (IEC) and AR technologies to facilitate the collaborative exploration and evolution of IoT device programs (MESH programs). Users can create, evaluate, and iteratively refine MESH programs through an immersive AR interface, while being inspired by the system's suggestions and other users' creations. The system employs a genetic algorithm to evolve MESH programs based on user evaluations, and utilizes natural language processing to generate program descriptions that can trigger new ideas. A user study (n=16) was conducted to evaluate the system's effectiveness in stimulating creativity and promoting collaboration. Quantitative analysis revealed a significant increase in idea generation over time and a greater impact on inspiration for novice programmers. Qualitative findings highlighted the system's ability to foster a creative and collaborative environment. The insights gained from this study inform the design of future tools and experiences that support creative thinking and collaboration in the IoT domain.

DOI： 10.58459/icce.2024.4831

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Publishing type：Research paper (scientific journal)   Publisher：Asia-Pacific Society for Computers in Education  

As English becomes increasingly important globally, many agent-based conversation practice environments struggle to maintain learner motivation due to a lack of personalized behavior. This study proposes optimizing a conversational agent's non-verbal cues—such as nodding and voice characteristics—through interactive evolutionary computation to enhance learners' motivation. Participants engaged in role- play scenarios across eight settings, providing feedback after each interaction. The agent's behavior was iteratively optimized, and approximately 90% of participants reported increased willingness to interact, suggesting that personalizing non-verbal behavior can significantly improve motivation in language learners.

DOI： 10.58459/icce.2024.5008

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Publishing type：Research paper (scientific journal)   Publisher：Asia-Pacific Society for Computers in Education  

This study investigates the impact of introducing conversational pauses and self-adaptor gestures in robots to enhance human-likeness during English conversation practice. As globalization increases the demand for English proficiency, there is increasing interest in using conversational robots for language practice. However, conventional robots often lack natural disfluencies, making interactions feel overly artificial, especially for beginners. This study focuses on enhancing the robot's non-verbal behaviors by implementing conversational pauses and self-adaptor gestures such as fidgeting at predetermined intervals during scripted conversational scenarios. The experiment involved 22 men and women in their 20s. An experimental evaluation revealed that approximately 90% of participants perceived an increased sense of human-likeness when the robot exhibited these pausing and hesitation behaviors. These results suggest that strategically incorporating naturalistic disfluencies and human-like self-adaptor gestures into a conversational robot's non- verbal repertoire can significantly increase its perceived anthropomorphism and potentially improve user engagement in language learning contexts.

DOI： 10.58459/icce.2024.5010

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Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

Serendipitous learning, characterized by the discovery of new insights and unexpected connections, is recognized as a valuable educational experience that stimulates critical thinking and self-regulated learning. While there have been limited efforts to develop serendipity-oriented recommender systems in education, these systems often fall short in supporting learners’ agency, that is, the sense of ownership and control over their learning journey. In this paper, we introduce an Interactive Evolutionary Computation (IEC)-driven recommender system designed to empower learners by granting them control over their learning experiences while offering recommendations that are both novel and unexpected yet aligned with their interests. Our proposed system leverages an Interactive Genetic Algorithm in conjunction with Knowledge Graphs to dynamically recommend learning content, with a focus on the history of scientific discoveries. We conducted both numerical simulations and experimental evaluations to assess the effectiveness of our content optimization algorithm and the impact of our approach on inducing serendipity in informal learning environments. The results indicate that a significant number of participants found certain recommended learning materials to be engaging and surprising, providing evidence that our system has the potential to facilitate serendipitous learning experiences within informal learning contexts.

DOI： 10.3390/mti8110103

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/scisisis61014.2024.10760027

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/scisisis61014.2024.10760170

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/scisisis61014.2024.10760069

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Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

DOI： 10.1109/scisisis61014.2024.10759906

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Publishing type：Part of collection (book)   Publisher：Springer Nature Switzerland  

DOI： 10.1007/978-3-031-60412-6_7

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Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Kansei Engineering  

DOI： 10.5057/ijae.ijae-d-24-00001

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Publishing type：Part of collection (book)   Publisher：Springer International Publishing  

DOI： 10.1007/978-3-031-05409-9_35

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Publishing type：Part of collection (book)   Publisher：Springer International Publishing  

DOI： 10.1007/978-3-031-06391-6_2

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Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Kansei Engineering  

DOI： 10.5057/isase.2022-c000034

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Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Kansei Engineering  

DOI： 10.5057/isase.2022-c000028

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Publishing type：Research paper (scientific journal)   Publisher：Japan Society of Kansei Engineering  

DOI： 10.5057/isase.2022-c000029

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (conference, symposium, etc.)  

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Science and Business Media Deutschland GmbH  

Kansei is a Japanese word that refers to feeling, sensitivity, intuition, among others. In this paper, we propose a system that facilitates the perception of other people’s Kansei to promote daily life awareness. To this end, our approach consists of providing users with the opportunity to visualize other people’s Kansei through observation of emoticons attached to various objects in daily scenery. To achieve an immersive experience, we designed a virtual reality environment displaying scenery that subjects are already familiar with. The proposed system is equipped with two modes: Mode 1, where users just add their Kansei to the displayed scenery, and Mode 2, where they are prompted to infer another user’s Kansei by finding objects on which emoticons may have been added. We conducted an experiment to evaluate the effectiveness of the proposed system. During the experiment, subjects interacted with the system in Mode 1, Mode 2, and then Mode 1 again, so that we could measure the influence of inferring other’s Kansei on their own. The results showed that users could gain new insights by adopting others’ Kansei. Besides, we obtained that they were keener to explore the scenery more proactively to gain new awareness.

DOI： 10.1007/978-3-030-78642-7_32

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Science and Business Media Deutschland GmbH  

This paper proposes a system that uses Interactive Evolutionary Computation (IEC) to recommend eyeglasses based on user aesthetic preference and suitability. The system presents the user with various eyeglasses, and the user evaluates the design based on aesthetic preference. Then, the system uses an Interactive Genetic Algorithm (IGA) to optimize the design based on the user and suitability evaluation. An experiment was conducted to determine the effectiveness of the proposed system toward optimizing eyeglass design. In the experiment, subjects were presented with two versions of the proposed system, which differed in the selection process adopted for the IGA. After system interaction, the subjects answered a questionnaire to determine any differences between the two versions. As new designs were generated, the system was could optimize the eyeglass design, to improve preference and suitability evaluations. We also found a difference in the optimization performance and user satisfaction of the two proposed methods.

DOI： 10.1007/978-3-030-78635-9_47

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer International Publishing  

DOI： 10.1007/978-3-030-50017-7_10

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (conference, symposium, etc.)  

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Springer Verlag  

This study reports on differences observed among learners’ preferences of two conversational strategies embedded in a dialogue agent dedicated to enhancing their willingness to communicate (WTC) in a second language. We found that the combination of both strategies is, in general, the most preferred by learners. However, perception, as well as effects of the support provided by these strategies seem to vary according to learners’ level of willingness to communicate. Lower WTC learners tended to prefer affective backchannels while their counterparts seem rather favor communication strategies. These results were also in line with posttest results which revealed that learners’ expected WTC tended to be higher after interacting with dialogue agents embedding their preferred strategies. In sum, these results can be viewed as preliminary evidence of the meaningfulness to account for second language learners’ preferences towards balancing adaptively the type of strategies employed by dialogue agents to motivate learners towards communication in the target second language.

DOI： 10.1007/978-3-030-23207-8_4

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Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：Asia-Pacific Society for Computers in Education  

Willingness to communicate (WTC) in a second language (L2) is believed to have a direct and sustained influence on learners' actual usage frequency of the targeted language. To help overcome the lack of suitable environments to increase L2 learners' WTC, our approach is to build conversational agents that can help L2 learners overcome their apprehension towards communication in L2. In this paper, we focus on the dialogue management aspects of our approach and propose a model based on set of communication strategies (CS) and affective backchannels (AB) in order to foster agents' ability to carry on natural and WTC friendly conversations with L2 learners. An evaluation of the proposed method led to two main findings. First, combining CS and AB empowers the conversational agent, making possible highly significant WTC gains among L2 learners in English as a foreign language context. Secondly, even a single implementation of AB proved to have the potential to enhance L2 learners' WTC to some extent.

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Japanese Society for Information and Systems in Education  

<p>In this paper, we propose an embodied conversational agent based on the willingness to communicate (WTC) model in L2 to help increase WTC in the context of English as a foreign language (EFL) by providing users with various daily conversation contexts. To simulate realistic and efficient conversations, we adopted a semantic approach in the response generation and created a system with flexible and adaptable domain knowledge, user's intent detection, and mixed-initiative conversation strategy. Our evaluation of the proposed system demonstrated its potential to simulate efficiently natural conversations in a specific context as well as the feasibility of improving learners' WTC using a computer-based environment.</p>

DOI： 10.12937/ejsise.15.15

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：ELSEVIER SCIENCE BV  

We propose an embodied conversational agent based on the willingness to communicate (WTC) model in L2 to help increase WTC in the context of English as a Foreign Language (EFL) by providing users with various daily conversation contexts. To simulate realistic and efficient conversations, we adopted a semantic approach in the response generation and created a system with flexible and adaptable domain knowledge, user's intent detection, and mixed-initiative conversation strategy. Our evaluation of the proposed system demonstrated its potential to increase WTC in the EFL context. (C) 2015 The Authors. Published by Elsevier B.V.

DOI： 10.1016/j.procs.2015.08.219

Web of Science

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Country：Japan

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