Pub Date : 2021-12-01DOI: 10.1109/ICA54137.2021.00007
Nobuyuki Hirose, Shun Shiramatsu, S. Okuhara
We have developed a chatbot that advises design students on their learning strategies through automatic interactions. We implemented a prototype of the chatbot in a sketchbook application that students utilized to receive advice during their design studies and evaluated whether it could help them to facilitate their learning strategies. The results demonstrated that, while the chatbot was generally able to create a natural dialogue flow with the students and helped to increase some learning strategies, there was still significant room for improvement. We analyzed the data on learning strategies and self-efficacy obtained from the experiments in detail and came up with a new hypothesis. That is, the experimental result indicated that chatbots can increase strategies for understanding learning progress, reflecting on learning, and devising learning methods by interacting with students in a way that gives them confidence, and we will empirically verify it in our future work.
{"title":"Development of chatbot to support student learning strategies in design education","authors":"Nobuyuki Hirose, Shun Shiramatsu, S. Okuhara","doi":"10.1109/ICA54137.2021.00007","DOIUrl":"https://doi.org/10.1109/ICA54137.2021.00007","url":null,"abstract":"We have developed a chatbot that advises design students on their learning strategies through automatic interactions. We implemented a prototype of the chatbot in a sketchbook application that students utilized to receive advice during their design studies and evaluated whether it could help them to facilitate their learning strategies. The results demonstrated that, while the chatbot was generally able to create a natural dialogue flow with the students and helped to increase some learning strategies, there was still significant room for improvement. We analyzed the data on learning strategies and self-efficacy obtained from the experiments in detail and came up with a new hypothesis. That is, the experimental result indicated that chatbots can increase strategies for understanding learning progress, reflecting on learning, and devising learning methods by interacting with students in a way that gives them confidence, and we will empirically verify it in our future work.","PeriodicalId":273320,"journal":{"name":"2021 IEEE International Conference on Agents (ICA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121080143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICA54137.2021.00019
Takumi Satō, Tohru Itoh, Naoki Fukuta, Hiroko Watanabe, Kou Hiroe, Satoshi Takayama, Yukiko Higashimoto, T. Ogawa, A. Shinjo, Satoshi Wada
Home cares and facility cares are important in Japan because of aging issues in Japan. One of the most important things in a care is Quality of Life (QOL) of patients. However, QOL of caregivers is also important and increasing a turnover by a low level of QOL is becoming an issue in japan. To solve the lack of caregivers, some research indicates the importance of improving QOL of caregivers. However, in most situations, giving better QOL of patients and caregivers is a trade-off. We propose a prototype system for a care matching to optimize QOL of patients and caregivers considering their care categories and relationships of patients and caregivers.
{"title":"Toward a care matching system to optimize QOL of patients and caregivers","authors":"Takumi Satō, Tohru Itoh, Naoki Fukuta, Hiroko Watanabe, Kou Hiroe, Satoshi Takayama, Yukiko Higashimoto, T. Ogawa, A. Shinjo, Satoshi Wada","doi":"10.1109/ICA54137.2021.00019","DOIUrl":"https://doi.org/10.1109/ICA54137.2021.00019","url":null,"abstract":"Home cares and facility cares are important in Japan because of aging issues in Japan. One of the most important things in a care is Quality of Life (QOL) of patients. However, QOL of caregivers is also important and increasing a turnover by a low level of QOL is becoming an issue in japan. To solve the lack of caregivers, some research indicates the importance of improving QOL of caregivers. However, in most situations, giving better QOL of patients and caregivers is a trade-off. We propose a prototype system for a care matching to optimize QOL of patients and caregivers considering their care categories and relationships of patients and caregivers.","PeriodicalId":273320,"journal":{"name":"2021 IEEE International Conference on Agents (ICA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126948133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ICA54137.2021.00009
Wen Gu, Shohei Kato, F. Ren, Guoxin Su, Takayuki Ito
With the development of the automated facilitation support for online forum, influential user detection becomes a critical issue for supporting human facilitator. Influential maximization (IM) aiming at choosing a set of users that maximize the influence propagation from the entire social network users is one of the key approaches to detect influential users in online social network. However, conventional IM algorithms cannot be applied to online forum because of the lack of existing social network. In addition, they neglect many real-world factors such as the characteristics of individual users and relation between users that should be considered in online forums influential user detection. In this paper, we propose a novel IM-based approach to detect influential users in online forum. The online forum influence propagation network (OFIPN) is modeled with the consideration of both individual contribution and relevance between users, and a heuristic algorithm that aims to find influential users in OFIPN is proposed. Experiments are conducted by utilizing a real-world social network. Our empirical results show the effectiveness of the proposed algorithm.
{"title":"Influential Online Forum User Detection Based on User Contribution and Relevance","authors":"Wen Gu, Shohei Kato, F. Ren, Guoxin Su, Takayuki Ito","doi":"10.1109/ICA54137.2021.00009","DOIUrl":"https://doi.org/10.1109/ICA54137.2021.00009","url":null,"abstract":"With the development of the automated facilitation support for online forum, influential user detection becomes a critical issue for supporting human facilitator. Influential maximization (IM) aiming at choosing a set of users that maximize the influence propagation from the entire social network users is one of the key approaches to detect influential users in online social network. However, conventional IM algorithms cannot be applied to online forum because of the lack of existing social network. In addition, they neglect many real-world factors such as the characteristics of individual users and relation between users that should be considered in online forums influential user detection. In this paper, we propose a novel IM-based approach to detect influential users in online forum. The online forum influence propagation network (OFIPN) is modeled with the consideration of both individual contribution and relevance between users, and a heuristic algorithm that aims to find influential users in OFIPN is proposed. Experiments are conducted by utilizing a real-world social network. Our empirical results show the effectiveness of the proposed algorithm.","PeriodicalId":273320,"journal":{"name":"2021 IEEE International Conference on Agents (ICA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-01DOI: 10.1109/ica54137.2021.00003
{"title":"Copyright","authors":"","doi":"10.1109/ica54137.2021.00003","DOIUrl":"https://doi.org/10.1109/ica54137.2021.00003","url":null,"abstract":"","PeriodicalId":273320,"journal":{"name":"2021 IEEE International Conference on Agents (ICA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130809479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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