Pub Date : 2022-07-01DOI: 10.1109/ICALT55010.2022.00109
Xinyue Jiao, Zifeng Liu, Haitao Zhou, Su Cai
Augmented Reality (AR) has great potential in science education, and Collaborative Inquiry-based Learning (CIBL) in the AR environment is of great significance. However, there is a problem of low collaborative performance in technology-based CIBL. This study applied the strategy of role assignment to AR-based CIBL, aiming to explore the effect of role assignment on students’ collaboration. Forty-seven sixth-grade students in elementary school were randomly divided into Group A (without role assignment) and Group B (with role assignment) to participate in AR-based collaborative scientific inquiry activities. Data on students’ scientific knowledge achievement, attitudes toward science learning, cognitive load, and flow experience were collected. In addition, interviews were conducted to investigate students’ opinions on role assignments. It is found that the strategy of role assignment could significantly improve students’ science knowledge achievement. The interview results revealed how role assignments facilitate students’ collaboration from three aspects.
{"title":"The Effect of Role Assignment on Students’ Collaborative Inquiry-based Learning in Augmented Reality Environment","authors":"Xinyue Jiao, Zifeng Liu, Haitao Zhou, Su Cai","doi":"10.1109/ICALT55010.2022.00109","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00109","url":null,"abstract":"Augmented Reality (AR) has great potential in science education, and Collaborative Inquiry-based Learning (CIBL) in the AR environment is of great significance. However, there is a problem of low collaborative performance in technology-based CIBL. This study applied the strategy of role assignment to AR-based CIBL, aiming to explore the effect of role assignment on students’ collaboration. Forty-seven sixth-grade students in elementary school were randomly divided into Group A (without role assignment) and Group B (with role assignment) to participate in AR-based collaborative scientific inquiry activities. Data on students’ scientific knowledge achievement, attitudes toward science learning, cognitive load, and flow experience were collected. In addition, interviews were conducted to investigate students’ opinions on role assignments. It is found that the strategy of role assignment could significantly improve students’ science knowledge achievement. The interview results revealed how role assignments facilitate students’ collaboration from three aspects.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127370043","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00009
Mario Madureira Fontes, Daniela Pedrosa, Leonel Morgado, J. Cravino
Research data on the activities of student teams in online learning environments are relevant for evaluating instructional methods, strategies, tools, and materials. For research data sharing and publication purposes, these personal data must be anonymized or pseudonymized as recommended by data protection and privacy policies. This paper addresses issues related to anonymizing and pseudonymizing student data on the Slack teamwork platform, one often employed in educational and business settings. Issues are discussed from two perspectives: data extraction and data transformation. Difficulties and challenges concerning data extraction and transformation are described. The complexities of these two processes are considered, and a starting point for developing more efficient methods is put forward.
{"title":"Anonymizing student team data of online collaborative learning in Slack","authors":"Mario Madureira Fontes, Daniela Pedrosa, Leonel Morgado, J. Cravino","doi":"10.1109/ICALT55010.2022.00009","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00009","url":null,"abstract":"Research data on the activities of student teams in online learning environments are relevant for evaluating instructional methods, strategies, tools, and materials. For research data sharing and publication purposes, these personal data must be anonymized or pseudonymized as recommended by data protection and privacy policies. This paper addresses issues related to anonymizing and pseudonymizing student data on the Slack teamwork platform, one often employed in educational and business settings. Issues are discussed from two perspectives: data extraction and data transformation. Difficulties and challenges concerning data extraction and transformation are described. The complexities of these two processes are considered, and a starting point for developing more efficient methods is put forward.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127735030","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00077
Mario E. Aburto-Gutierrez, Gamar Azuaje, Vipul Mishra, Shaira Osmani, K. Ikeda
The Japanese language is an essential skill for many foreigners who plan to study or work in Japan, but it is very hard and time-consuming to learn. Given the current COVID19 pandemic, the use of online and computer-assisted tools for Japanese language learning is indispensable. However, many of the currently available tools do not offer personalized content based on the user’s performance and lack social interaction, which can lower the engagement level of the users. In this paper, we propose JaSenpai, a Japanese language E-learning platform that features an automatic generation of vocabulary exercises, a recommendation system based on previous answers, and a multiplayer game for social interaction. We believe these elements can provide a more engaging and effective learning experience.
{"title":"JaSenpai: Towards an Adaptive and Social Interactive E-Learning Platform for Japanese Language Learning","authors":"Mario E. Aburto-Gutierrez, Gamar Azuaje, Vipul Mishra, Shaira Osmani, K. Ikeda","doi":"10.1109/ICALT55010.2022.00077","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00077","url":null,"abstract":"The Japanese language is an essential skill for many foreigners who plan to study or work in Japan, but it is very hard and time-consuming to learn. Given the current COVID19 pandemic, the use of online and computer-assisted tools for Japanese language learning is indispensable. However, many of the currently available tools do not offer personalized content based on the user’s performance and lack social interaction, which can lower the engagement level of the users. In this paper, we propose JaSenpai, a Japanese language E-learning platform that features an automatic generation of vocabulary exercises, a recommendation system based on previous answers, and a multiplayer game for social interaction. We believe these elements can provide a more engaging and effective learning experience.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128710729","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}
This study used deep learning techniques with Moodle log data to predict student performance in introductory computer programming courses. Particularly, this study would like to use prediction results to identify potential low-performing students who may need assistance from teachers. The results suggested that deep learning models are promising to predict student performance and identify low-performing students in the researched context. What the prediction results provided by the models can inform teachers in learning settings was also further discussed in this paper.
{"title":"Using deep learning models to predict student performance in introductory computer programming courses","authors":"Yueh-hui Vanessa Chiang, Ying-Zu Lin, Nian-Shing Chen","doi":"10.1109/ICALT55010.2022.00060","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00060","url":null,"abstract":"This study used deep learning techniques with Moodle log data to predict student performance in introductory computer programming courses. Particularly, this study would like to use prediction results to identify potential low-performing students who may need assistance from teachers. The results suggested that deep learning models are promising to predict student performance and identify low-performing students in the researched context. What the prediction results provided by the models can inform teachers in learning settings was also further discussed in this paper.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"25 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114127219","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00011
Veronica Segarra-Faggioni, Audrey Romero Pelaez
Open Educational Resources (OER) are educational materials that are available in different repositories such as Merlot, SkillsCommons, MIT OpenCourseWare, etc. The quality of metadata facilitates the search and discovery tasks of educational resources. This work evaluates the metadata quality of 4142 OER from SkillsCommons. We applied supervised machine learning algorithms (Support Vector Machine and Random Forest Classifier) for automatic classification of two metadata: description and material type. Based on our data and model, performances of a first classification effort is reported with the accuracy of 70%.
开放教育资源(OER)是一种教育材料，可以在Merlot、SkillsCommons、MIT Open encourseware等不同的存储库中获得。元数据的质量促进了教育资源的搜索和发现任务。这项工作评估了SkillsCommons中4142 OER的元数据质量。我们应用监督机器学习算法(支持向量机和随机森林分类器)对描述和材料类型两个元数据进行自动分类。基于我们的数据和模型，报告了第一次分类工作的性能，准确率为70%。
{"title":"Automatic classification of OER for metadata quality assessment","authors":"Veronica Segarra-Faggioni, Audrey Romero Pelaez","doi":"10.1109/ICALT55010.2022.00011","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00011","url":null,"abstract":"Open Educational Resources (OER) are educational materials that are available in different repositories such as Merlot, SkillsCommons, MIT OpenCourseWare, etc. The quality of metadata facilitates the search and discovery tasks of educational resources. This work evaluates the metadata quality of 4142 OER from SkillsCommons. We applied supervised machine learning algorithms (Support Vector Machine and Random Forest Classifier) for automatic classification of two metadata: description and material type. Based on our data and model, performances of a first classification effort is reported with the accuracy of 70%.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127544052","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00015
Diana Andone, M. Frydenberg
This paper analyzes the results of two consecutive years (2020 and 2021) of an international collaboration between students at universities in the United States and Romania from the perspectives of comparing digital competencies and future skills. Offered annually since 2009, TalkTech is a project based learning scenario requiring students to use synchronous and asynchronous communication tools to research a topic and share their findings in a jointly-created digital artefact. During the last two years, 110 students researched topics related to international businesses and creative industries and presented their results using virtual reality. To complete the project, students made use of open educational practices and communicated, analyzed, developed, demonstrated, shared compared and discussed their work using several different digital tools. This paper investigates how students perceive their use of digital tools how these influenced them, especially during pandemic times.
{"title":"Developing Digital Competencies and Future Skills: An International Project-Based Learning through Open Virtual Mobilities in Pandemic Times","authors":"Diana Andone, M. Frydenberg","doi":"10.1109/ICALT55010.2022.00015","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00015","url":null,"abstract":"This paper analyzes the results of two consecutive years (2020 and 2021) of an international collaboration between students at universities in the United States and Romania from the perspectives of comparing digital competencies and future skills. Offered annually since 2009, TalkTech is a project based learning scenario requiring students to use synchronous and asynchronous communication tools to research a topic and share their findings in a jointly-created digital artefact. During the last two years, 110 students researched topics related to international businesses and creative industries and presented their results using virtual reality. To complete the project, students made use of open educational practices and communicated, analyzed, developed, demonstrated, shared compared and discussed their work using several different digital tools. This paper investigates how students perceive their use of digital tools how these influenced them, especially during pandemic times.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"535 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127640306","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00058
Yueyuan Zheng, Y. Que, Xiao Hu, J. Hsiao
Reading is an essential medium for learning, but it is challenging to measure learners’ cognitive processes during reading. Eye-tracking, as an approach in multimodal learning analytics (MmLA), can provide fine-grained data that reflect cognitive processes during reading. In this study, we investigated whether eye movements could predict passage reading performance in addition to language proficiency and cognitive abilities. In particular, we assessed learners’ eye movement pattern and consistency through a novel method, Eye Movement analysis with Hidden Markov Models (EMHMM), in addition to traditional eye movement measures. We found that longer saccade length predicted faster reading speed Also, higher English proficiency predicted faster reading speed through the mediation of longer saccade length. In contrast, reading comprehension accuracy was best predicted by a more consistent eye fixation at the beginning of reading engagement, which may result from a better developed visual routine due to higher reading expertise. These findings have important implications for ways to assess and facilitate learners’ reading through eye movement measures and to examine factors influencing reading performance. The methods adopted could further the development of MmLA and serve as an empirical example of understanding learners’ cognitive processes through collecting and modeling critical learner-centered metrics in novel modalities.
{"title":"Predicting Reading Performance based on Eye Movement Analysis with Hidden Markov Models","authors":"Yueyuan Zheng, Y. Que, Xiao Hu, J. Hsiao","doi":"10.1109/ICALT55010.2022.00058","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00058","url":null,"abstract":"Reading is an essential medium for learning, but it is challenging to measure learners’ cognitive processes during reading. Eye-tracking, as an approach in multimodal learning analytics (MmLA), can provide fine-grained data that reflect cognitive processes during reading. In this study, we investigated whether eye movements could predict passage reading performance in addition to language proficiency and cognitive abilities. In particular, we assessed learners’ eye movement pattern and consistency through a novel method, Eye Movement analysis with Hidden Markov Models (EMHMM), in addition to traditional eye movement measures. We found that longer saccade length predicted faster reading speed Also, higher English proficiency predicted faster reading speed through the mediation of longer saccade length. In contrast, reading comprehension accuracy was best predicted by a more consistent eye fixation at the beginning of reading engagement, which may result from a better developed visual routine due to higher reading expertise. These findings have important implications for ways to assess and facilitate learners’ reading through eye movement measures and to examine factors influencing reading performance. The methods adopted could further the development of MmLA and serve as an empirical example of understanding learners’ cognitive processes through collecting and modeling critical learner-centered metrics in novel modalities.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126509114","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00116
Jérôme Hernandez, Mathieu Muratet, Matthis Pierotti, T. Carron
Computational psychometrics data and soft skills recognition have become prevalent means in personnel selection processes. Likewise, companies have shown a growing interest in using computational data and machine learning to predict employee behavior. With the aim to enhance selection strategies and applicant reactions simultaneously, the human resources population is researching and developing reliable and valid tools to fit the right person with the right job. In an innovative approach, gamified situational judgment tests have recently received positive results in behavior assessment in combining the acknowledged traditional situation judgment test approach with the advantages of gamification. To pursue previous work in the field and explore this new area of research, we proposed a novel approach to enhance the reliability and validity of gamified situational judgment test’s scoring system based on computational psychometrics data. Our approach has been tested and compared to the initial scoring system of an existing gamified situational judgment test intended to assess bank managers across four soft skills.
{"title":"Enhancement of a Gamified Situational Judgment Test Scoring System for Behavioral Assessment","authors":"Jérôme Hernandez, Mathieu Muratet, Matthis Pierotti, T. Carron","doi":"10.1109/ICALT55010.2022.00116","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00116","url":null,"abstract":"Computational psychometrics data and soft skills recognition have become prevalent means in personnel selection processes. Likewise, companies have shown a growing interest in using computational data and machine learning to predict employee behavior. With the aim to enhance selection strategies and applicant reactions simultaneously, the human resources population is researching and developing reliable and valid tools to fit the right person with the right job. In an innovative approach, gamified situational judgment tests have recently received positive results in behavior assessment in combining the acknowledged traditional situation judgment test approach with the advantages of gamification. To pursue previous work in the field and explore this new area of research, we proposed a novel approach to enhance the reliability and validity of gamified situational judgment test’s scoring system based on computational psychometrics data. Our approach has been tested and compared to the initial scoring system of an existing gamified situational judgment test intended to assess bank managers across four soft skills.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125122071","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00123
Yankai Li, Zibo He
Custom training plans can significantly increase students’ athletic performance. However, the students’ private data, such as body index, is required to generate the training plan, during which there may be data leakage. This paper presents a Blockchain-aided Physical Education Information System (BPEIS), which is an Internet of Things (IoT)-based system for data security and management in physical education. B-PEIS seeks to provide a secure and flexible system that can be utilized in physical education (PE) for improving student fitness performance. To verify the system performance, an experiment is conducted. Experiment results show that the B-PEIS can meet the need of PE.
{"title":"B-PEIS: A Secure Blockchain-based Physical Education Information System","authors":"Yankai Li, Zibo He","doi":"10.1109/ICALT55010.2022.00123","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00123","url":null,"abstract":"Custom training plans can significantly increase students’ athletic performance. However, the students’ private data, such as body index, is required to generate the training plan, during which there may be data leakage. This paper presents a Blockchain-aided Physical Education Information System (BPEIS), which is an Internet of Things (IoT)-based system for data security and management in physical education. B-PEIS seeks to provide a secure and flexible system that can be utilized in physical education (PE) for improving student fitness performance. To verify the system performance, an experiment is conducted. Experiment results show that the B-PEIS can meet the need of PE.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128386299","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 : 2022-07-01DOI: 10.1109/ICALT55010.2022.00035
Tryfon Sivenas, G. Koutromanos
The aim of this study was the examination of the perceived affordances and constraints of drones for teaching and learning. The sample consisted of 44 in-service teachers who attended an introductory presentation on drones, their technology and control mechanisms and afterwards assembled, flew and programmed four multicopter drones. Data was collected through anonymous online questionnaires. Results from qualitative data analysis revealed seven affordances, namely programming through block-based languages, recording and bird’s-eye view, viewing places that are unseen from ground level and real-time photo and video streaming, drone assembly, data collection and processing, gamification, and development of several student skills. Additionally, they revealed four constraints, namely the necessity of teacher training, time restrictions regarding the drone’s battery life, infrastructural and personal data restrictions. These findings will contribute to a better understanding of the educational value of drones for teaching and learning and, at the same time, provide a base-layer for future research in using drones for educational purposes.
{"title":"Exploring the Affordances of Drones from an Educational Perspective","authors":"Tryfon Sivenas, G. Koutromanos","doi":"10.1109/ICALT55010.2022.00035","DOIUrl":"https://doi.org/10.1109/ICALT55010.2022.00035","url":null,"abstract":"The aim of this study was the examination of the perceived affordances and constraints of drones for teaching and learning. The sample consisted of 44 in-service teachers who attended an introductory presentation on drones, their technology and control mechanisms and afterwards assembled, flew and programmed four multicopter drones. Data was collected through anonymous online questionnaires. Results from qualitative data analysis revealed seven affordances, namely programming through block-based languages, recording and bird’s-eye view, viewing places that are unseen from ground level and real-time photo and video streaming, drone assembly, data collection and processing, gamification, and development of several student skills. Additionally, they revealed four constraints, namely the necessity of teacher training, time restrictions regarding the drone’s battery life, infrastructural and personal data restrictions. These findings will contribute to a better understanding of the educational value of drones for teaching and learning and, at the same time, provide a base-layer for future research in using drones for educational purposes.","PeriodicalId":221464,"journal":{"name":"2022 International Conference on Advanced Learning Technologies (ICALT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129794364","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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